Projects
| Project | Abstract | Prime Company | Domain | Tags | Full text |
|---|---|---|---|---|---|
| 3D-Earth | The goal of this project is establish a global 3D reference model model of the crust and upper mantle based on the analysis of satellite gravity and (electro-)magnetic missions in combination with seismological models and analyse the feedback [...] | UNIVERSITY OF KIEL (DE) | Science | science, solid earth | The goal of this project is establish a global 3D reference model model of the crust and upper mantle based on the analysis of satellite gravity and (electro-)magnetic missions in combination with seismological models and analyse the feedback between processes in Earth’s deep mantle and the lithosphere. Selected case examples will provide the possibility to test these approaches on a global and regional scale. This will result in a framework for consistent models that will be used to link the crust and upper mantle to the dynamic mantle. The prime objective is to integrate, for the first time, seismological models and satellite observation towards a consistent image of the crust and upper mantle in 3D. Satellite gravity and (electro-) magnetic data help to transfer velocity images towards composition and temperature that reflect the tectonic state and evolution of the Earth and offer a novel understanding of the processes that shape our planet. The limitations and sensitivity of the different geophysical methods in context of their imaging capability are analysed and combined with forward and inverse modelling to be able to evaluate the possibilities of these approaches to reveal the Earth’s structure. For the inverse modelling, we will explore the sensitivity of joint inversion to the individual data sets and compare these to inversions relying on only a single or a few data sets. To analyse the structure of the deep mantle, we will try to combine knowledge about mantle conductivity and mineral physics with the geophysical observations. We will assess the role of Earth’s internal layering and mantle convection on the evolution of the Earth’s surface (dynamic topography). The data and methods we propose to use in this study will significantly supersede previous attempts and will be a first step towards an understanding of the Earth in space and time, a necessary step towards the development of a 4D Earth model.We will analyse the limitations and sensitivities of the different geophysical methods in the context of their imaging capability and plan to combine forward and inverse modelling to be able to evaluate the possibilities of these approaches to reveal the Earth’s structure. For the inverse modelling, we will explore the sensitivity of joint inversion to the individual data sets and compare these to inversions relying on only a single or a few data sets. Selected case examples will provide the possibility to test these approaches on a global and regional scale. This will result in a framework for consistent models that will be used to link the crust and upper mantle to the dynamic mantle. To analyse the structure of the deep mantle, we will attempt to combine knowledge about mantle conductivity and mineral physics with the geophysical observations. We will assess the role of Earth’s internal layering and mantle convection on the evolution of the Earth’s surface (dynamic topography). The data and methods we propose to use in this study will significantly supersede previous attempts and will be a first step towards an understanding of the Earth in space and time, a necessary step towards the development of a 4D Earth model. |
| 3DCTRL | 3DCTRL project aims to evaluate cloud correction methodologies in Copernicus Sentinel-4, Sentinel-5 and Sentinel-5p trace gas retrieval schemes and to explore ways to improve handling of realistic clouds in the retrievals of atmospheric species. [...] | ARISTOTLE UNIV. OF THESSALONIKI (GR) | Science | atmosphere, atmosphere science cluster, clouds, permanently open call, science, Sentinel-5P, TROPOMI | 3DCTRL project aims to evaluate cloud correction methodologies in Copernicus Sentinel-4, Sentinel-5 and Sentinel-5p trace gas retrieval schemes and to explore ways to improve handling of realistic clouds in the retrievals of atmospheric species. Cloud shadow fraction, cloud top height, cloud optical depth, solar zenith and viewing angles, were identified as the metrics being the most important in identifying 3D cloud impacts on NO2 TVCD retrievals. For a solar zenith angle less than about 40° the synthetic data show that the NO2 TVCD bias is typically below 10%. For larger solar zenith angles both synthetic and observational data often show NO2 TVCD bias on the order of tens of %. In 3DCTRL, fast retrieval algorithms for 3D cloudy scenes will be designed. Very promising is a retrieval algorithm based on a linearized one-dimensional radiative transfer model, in which the direct beam and its derivative with respect to the total column are computed in a three-dimensional atmosphere. The performance of new methods for cloud correction will be evaluated against the present operational products and independent measurements. 3DCTRL project has the following main objectives: (a) Generate synthetic reference datasets in which true cloud properties including their 3D structure and vertical distribution are known by means of 3D radiative transfer simulations, realistic synthetic data of cloud properties will be obtained from large-eddy simulation (LES) model (b) Explore ways to improve the handling of realistic clouds in trace gas retrievals, specifically for NO2 (c) Testing and evaluation of improved approaches for cloud correction by application on synthetic and real TROPOMI-S5P data |
| 4DANTARCTICA | Ice sheets are a key component of the Earth system, impacting on global sea level, ocean circulation and bio-geochemical processes. Significant quantities of liquid water are being produced and transported at the ice sheet surface, base, and [...] | UNIVERSITY OF EDINBURGH (GB) | Science | CryoSat, cryosphere, polar science cluster, science, Sentinel-1, Sentinel-2, SMOS | Ice sheets are a key component of the Earth system, impacting on global sea level, ocean circulation and bio-geochemical processes. Significant quantities of liquid water are being produced and transported at the ice sheet surface, base, and beneath its floating sections, and this water is in turn interacting with the ice sheet itself. Surface meltwater drives ice sheet mass imbalance; for example enhanced melt accounts for 60% of ice loss from Greenland, and while in Antarctica the impacts of meltwater are proportionally much lower, its volume is largely unknown and projected to rise. The presence of surface melt water is also a trigger for ice shelf calving and collapse, for example at the Antarctic Peninsula where rising air and ocean temperatures have preceded numerous major collapse events in recent decades. Meltwater is generated at the ice sheet base primarily by geothermal heating and friction associated with ice flow, and this feeds a vast network of lakes and rivers creating a unique bio-chemical environment. The presence of melt water between the ice sheet and bedrock also impacts on the flow of ice into the sea leading to regions of fast-flowing ice. Meltwater draining out of the subglacial system at the grounding line generates buoyant plumes that bring warm ocean bottom water into contact with the underside of floating ice shelves, causing them to melt. Meltwater plumes also lead to high nutrient concentrations within the oceans, contributing to vast areas of enhance primary productivity along the Antarctic coast. Despite the key role that hydrology plays on the ice sheet environment, there is still no global hydrological budget for Antarctica. There is currently a lack of global data on supra- and sub-glacial hydrology, and no systems are in place for continuous monitoring of it or its impact on ice dynamics. The overall aim of 4DAntarctica is to advance our understanding of the Antarctic Ice Sheet’s supra and sub-glacial hydrology, its evolution, and its role within the broader ice sheet and ocean systems. We designed our programme of work to address the following specific objectives: Creating and consolidating an unprecedented dataset composed of ice-sheet wide hydrology and lithospheric products, Earth Observation datasets, and state of the art ice-sheet and hydrology models Improving our understanding of the physical interaction between electromagnetic radiation, the ice sheet, and liquid water Developing techniques and algorithms to detect surface and basal melting from satellite observations in conjunction with numerical modelling Applying these new techniques at local sites and across the continental ice sheet to monitor water dynamics and derive new hydrology datasets Performing a scientific assessment of Antarctic Ice Sheet hydrology and of its role in the current changes the continent is experiencing Proposing a future roadmap for enhanced observation of Antarctica’s hydrological cycle To do so, the project will use a large range of Earth Observation missions (e.g. Sentinel-1, Sentinel-2, SMOS, CryoSat-2, GOCE, TanDEM-X, AMSR2, Landsat, Icesat-2) coupled with ice-sheet and hydrological models. By the end of this project, the programme of work presented here will lead to a dramatically improved quantification of meltwater in Antarctica, an improved understanding of fluxes across the continent and to the ocean, and an improved understanding of the impact of the hydrological cycle on ice sheet’s mass balance, its basal environment, and its vulnerability to climate change. |
| 4DATLANTIC Dust-Ocean Modelling & Observing Study (DOMOS) | The Dust-Ocean Modelling & Observing Study (DOMOS) will advance the understanding of dust and ocean interactions in a changing climate through an innovative use of model and observations. The project will develop a new retrieval of dust [...] | ECMWF (GB) | Science | Aeolus, Aerosols, Atlantic, climate, Ecosystems, marine environment, oceans, regional initiatives | The Dust-Ocean Modelling & Observing Study (DOMOS) will advance the understanding of dust and ocean interactions in a changing climate through an innovative use of model and observations. The project will develop a new retrieval of dust deposition from satellite lidar data (CALIPSO and Aeolus), will validate the dust deposition field from the CAMS reanalysis and will also provide assimilation tests of IASI and Aeolus aerosol products with the goal of providing a better description of the dust aerosols, for applications in aerosol radiative impacts and ocean biogeochemistry. An improved representation of the physical and chemical characteristics of dust deposition over the ocean is crucial to interpret the observed climatic change responses and to better describe the future ones. This includes a better understanding and quantification of the deposition of soluble iron from natural and anthropogenic dust and of its contribution relative to biomass burning and anthropogenic aerosols which will be one of the main deliverables of the project. A scientific roadmap to highlight the findings of the project and identify possible gaps in the modelling and the observing approaches will also be provided. DOMOS aims to answer the following questions. To what extent dust deposition over the Atlantic has changed over the last 20 years? Can we identify robust trends in the reanalysis and model datasets and if yes, how can we verify them? Although estimates have been attempted before, there is the need to look at longer time-series such as those provided by atmospheric composition reanalysis and climate models and develop tailor-made satellite retrievals from multiple sensors and platforms, aimed at quantifying dust deposition. This is a challenge as dust deposition is not directly observable from satellite. Observations must be complemented with model-based information. Also, independent observations of dust deposition are needed to quantify the quality of the model-based and reanalysis-based reconstructions as well as to evaluate the performance of the bespoken satellite retrievals. What is the contribution of anthropogenic and natural sources of dust compared to biomass burning and anthropogenic aerosols to soluble iron deposition over the Atlantic? While dust is the largest contributor to total iron deposition by far, it is unclear what its contribution to soluble iron deposition is. What are the impacts of changes in dust deposition on marine biogeochemistry and their potential effects on ecosystems? The connection between changes in dust deposition and the nutrients available for marine ecosystems needs further investigation with a concerted synergy of modelling and observations. |
| 4DATLANTIC EBUS PRIMUS | Primary productivity in upwelling systems (PRIMUS) aims to provide the best possible characterisation of net primary productivity (NPP) and its relationship to upwelling in Atlantic Eastern Boundary Upwelling Systems (EBUS). Funded through ESA’s [...] | Plymouth Marine Laboratory (GB) | Science | Atlantic, climate, MERIS, oceans, OLCI, regional initiatives | Primary productivity in upwelling systems (PRIMUS) aims to provide the best possible characterisation of net primary productivity (NPP) and its relationship to upwelling in Atlantic Eastern Boundary Upwelling Systems (EBUS). Funded through ESA’s Regional Initiative, PRIMUS will produce a 25-year time series of 1-km NPP in all Atlantic EBUS, and experimentally, at higher-resolution (300m) using the unique capabilities of the MERIS and OLCI sensors. These data, together with upwelling indices from different data sources, existing in-situ data, and ocean circulation modelling, will enable investigation of EBUS impacts on Earth system processes and socio-economically important activities such as: aquaculture in Galicia; fiand eutrophication in the Portuguese upwelling region; impacts on ocean carbon pools; Lagrangian estimates of NPP; and air-sea interaction and acidification impacts. Science cases will make use of EO data, in situ data as well as numerical model outputs to investigate the 4D character of EBUS, for example linking Lagrangian NPP with sediment traps samples at depth. Finally, based on the project results and wider consultations, PRIMUS will develop a scientific roadmap in the form of a peer-reviewed paper, posing scientific challenges and observations gaps that need to be addressed over the 2023 to 2027 timeframe. Project Description Primary productivity in upwelling systems (PRIMUS) will provide the best possible characterisation of net primary productivity (NPP) and its relationship to upwelling in Atlantic Eastern Boundary Upwelling Systems. We will produce a 25-year time series of 1-km NPP in all Atlantic EBUS, and experimentally, at higher-resolution (300m) using the unique capabilities of the MERIS and OLCI sensors. These data, together with upwelling indices from different data sources, existing in-situ data, and ocean circulation modelling, will address the objectives stated in the 4DAtlantic theme 1 requirements. PRIMUS will design and implement a novel research plan that aims to describe how we plan consolidate and advance the current understanding of Atlantic EBUS, specifically addressing net primary productivity, its relation to wind-induced upwelling, its impact on Earth system processes, and effects on socio-economically important activities. This plan will include a wide-ranging consultation with relevant stakeholders and early-adopters. PRIMUS will create or add to databases of relevant EO and in situ data that will be used in the project, notably as input for computation of NPP (as well as other elements of the carbon cycle impacted by EBUS). We will make use of a new 1-km version of the long-term climate quality ESA OC CCI dataset and leverage the unique resolution and spectral band capabilities of ESA MERIS and OLCI instruments. In-situ data will be mined from the scientific literature, existing databases, and be provided by our collaborators, notably in the regularly sampled Galician Sea component of the Iberian upwelling system, as well as other regions of interest (Portuguese coast, Canary current system and Benguela upwelling system. PRIMUS will investigate prototype products and perform a thorough validation of the products from two existing NPP models for Atlantic EBUS. These will be evaluated using a number of criteria including accuracy (with respect to in situ data) computational efficiency (and success in simplification though an AI/ML investigation to be conducted, and appropriateness for specific regions or science applications. Evolution of the models will be based on developments from the ESA BICEP project. We will focus attention on specific developments to input variables to the models: i.e. chl-a, considering optical water type classification and sunglint-impacted data PRIMUS will generate and validate a “4DAtlantic Experimental Dataset” of EO-based Atlantic EBUS data. These products will span over 25 years during the project, , and will make use of recently available data from Sentinel 3 for an experimental high resolution NPP product. PRIMUS will use these data to advance Earth System science analyses covering Atlantic EBUS temporal and spatial variability in NPP and its statistical relationship to upwelling and climate indices (such as the NAO). PRIMUS will also operate eight further science cases in specific science areas / regional settings, such as aquaculture in Galicia, or fisheries and eutrophication in the Portuguese upwelling region. In addition we will investigate: potential EBUS impacts on ocean carbon pools; Lagrangian estimates of NPP; and air-sea interaction and acidification impacts. Science cases will make use of EO data, in situ data as well as numerical model outputs (freely available through Copernicus and elsewhere) to investigate the 4D character of EBUS, for example linking Lagrangian NPP with sediment traps samples at depth. These will provide exemplars for science that can be conducted with 4D reconstructions In order to demonstrate wider socio-economic relevance and impact, PRIMUS will conduct demonstrations that transfers science into solutions for society, working together with scientific, agency, policy and commercial early-adopters, building on three of the science case studies (concerning EBUS and aquaculture, fisheries and eutrophication monitoring); affiliating with the Future Earth Coasts initiative; evaluating transition of data production to operational initiatives such as Copernicus and GMES and Africa; and the potential for exploitation by the European and international ecosystem modelling community. Based on the project results and wider consultations PRIMUS will develop a scientific roadmap in the form of a peer-reviewed paper, posing scientific challenges and observations gaps that need to be addressed over the 2023 to 2027 timeframe. The roadmap will focus on Atlantic EBUS, but also consider global applications of the PRIMUS results. A further aim is to collaborate on ways forward with other ESA activities (e.g. BICEP, Ocean-SODA and notably ESA Digital Twin Precursors), and other international efforts. Finally, PRIMUS will coordinate and promote international collaboration and communicate results to scientists and citizens to maximise impact of the project through cross-cutting promotion, communication, and education activities, and through peer-reviewed publications. In conclusion, PRIMUS aims to make a major contribution to the ESA 4DAtlantic research programme, 4D reconstructions and understanding of Atlantic EBUS net primary production in relation to upwelling and its socio-economic impacts. The ESA Regional Initiative 4DATLANTIC-EBUS-PRIMUS Project has been kicked-off in September 2021, for a duration of 2 years. New approach to satellite data analysis reveals unexpected patterns in biological production New PRIMUS paper using the MOving Standard deviation Saturation (MOSS) to study timescales of variability in global satellite Chl and SST Plymouth Marine Laboratory new approach to analyse the variability in satellite data (video) |
| 4DATLANTIC – OCEAN HEAT CONTENT – (OHC) | This project aims at developing, testing and implementing innovative methods able to use space geodetic data from altimetry and gravimetry to generate the regional ocean heat content (OHC) change over the Atlantic Ocean. The ESA MOHeaCAN project [...] | MAGELLIUM (FR) | Science | altimeter, Atlantic, climate, gravity and gravitational fields, oceans, regional initiatives, science | This project aims at developing, testing and implementing innovative methods able to use space geodetic data from altimetry and gravimetry to generate the regional ocean heat content (OHC) change over the Atlantic Ocean. The ESA MOHeaCAN project strategy has been pursued and refined at regional scales both for the data generation and the uncertainty estimate. In practice, we propose to develop a purely space-based product paying a careful attention to the error propagation along the processing scheme. This will enable to keep the product independent from in situ data which are the unique source of data for validation. By keeping the space-based product independent from in-situ data we ensure that we can validate properly and precisely both the space product and its uncertainty. In addition, the product will be only based on observations. With this approach there is no premature mixing with model solutions. The data and their uncertainty are driven by observations only. Thus, the space-based product fits the needs for any model validation. This is absolutely essential to ensure an efficient dissemination of the product among the climate modelling community. The official version of the 4DAtlantic-OHC product and its associated documentation is now available on the ODATIS/AVISO portal. The product has been validated against in-situ data and is now used and analysed to address the major science questions helping us to better understand the complexity of the climate system. The study is focused on the Meridional Heat Transport (MHT) in the North Atlantic with a regional heat budget. In parallel, our early adopters started to assess the strengths and limitations of the OHC product for potential new solutions for society. The ESA Regional Initiative 4DATLANTIC OHC Project has been kicked-off on 7 July 2021, for a duration of 2 years. The first phase of the project (development and validation of the product) has come to an end. The second phase relating to the scientific use case and the use of the product by early adopters is on-going. |
| 4DGreenland | In 4DGreenland the overall aim is to advance the current state of knowledge on the hydrology of the Greenland Ice Sheet, by capitalising on the latest advances in Earth Observation data. The high latitudes of the Northern Hemisphere have [...] | Technical University of Denmark (DK) | Science | Glaciers and Ice Sheets, polar science cluster, science | In 4DGreenland the overall aim is to advance the current state of knowledge on the hydrology of the Greenland Ice Sheet, by capitalising on the latest advances in Earth Observation data. The high latitudes of the Northern Hemisphere have experienced the largest warming over the last decades. The Greenland ice sheet is currently undergoing rapid changes in response to the increased temperatures. Understanding the Greenland ice sheet hydrologyis essential to understand these changes – and how the Greenland ice sheet will contribute to global sea level rise in a future warming climate. In 4DGreenland we will map and quantify both meltwater- , subglacial- and supra-glacial processes, as well as performing an integrated assessment of Greenland’s hydrology based on the results. We will focus our integrated assessment analysis on the time span 2010-present, and generate a Product Portfolio of novel datasets over the whole Greenland ice sheet to characterise the different components of the hydrological system. Thorough validation ofall derived products and scientific results will be carried out. Another outcome of the project will be a scientific roadmap providing recommendations to ESA to further advance the use of EO technology to address the main knowledge gaps and scientific challenges associated with the Greenland hydrology. |
| 4DHydro – Hyper-resolution Earth observations and land-surface modeling for a better understanding of the water cycle | The project brings together the EO water cycle community developing novel high-resolution EO data products, and the land surface and hydrological modelling community engaged in advancing hyper-resolution modelling of the hydrological cycle at [...] | HELMHOLTZ – ZENTRUM FUER UMWELTFORS (DE) | Science | hydrology science cluster, terrestrial hydrosphere, water cycle and hydrology | The project brings together the EO water cycle community developing novel high-resolution EO data products, and the land surface and hydrological modelling community engaged in advancing hyper-resolution modelling of the hydrological cycle at regional and continental scales to assess the uncertainty of existing EO and LSM/HM data sets related to key terrestrial ECVs and generate improved datasets at 1 km spatial resolution in the selected study areas. Targeted science cases will demonstrate the synchronization of EO products and LSM/HMs models for improved predictability of hydrology systems at higher spatial and temporal resolutions, while use cases will develop tools to enhance the ability of end-users and decision-makers to extract and manipulate existing and future reanalysis and climate data sets. |
| 4DIONOSPHERE | The project is also called Swarm Space Weather Variability of Ionospheric Plasma (Swarm-VIP). The Swarm-VIP project aims at advancing our understanding and characterisation of ionosphere processes in order to better model and potentially predict [...] | UNIVERSITY OF OSLO (NO) | Science | ionosphere and magnetosphere, science | The project is also called Swarm Space Weather Variability of Ionospheric Plasma (Swarm-VIP). The Swarm-VIP project aims at advancing our understanding and characterisation of ionosphere processes in order to better model and potentially predict the behaviour of the ionosphere. In particular, the project members work on the development of a semi-empiric model and improving the forecasting capabilities for extreme space weather events. Swarm-VIP project performs extensive and complex statistical analysis on Swarm electron density, electric and magnetic field data focusing on: 1) the ionospheric climate/weather during quiet geomagnetic conditions; 2) the extreme events such as geomagnetic storms / superstorms and 3) the physics of ionospheric perturbations and small-scale variability. |
| 4DMED-Hydrology | 4DMED-Hydrology aims at developing an advanced, high-resolution, and consistent reconstruction of the Mediterranean terrestrial water cycle by using the latest developments of Earth Observation (EO) data as those derived from the ESA-Copernicus [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | hydrology science cluster, Mediterranean, regional initiatives, science, terrestrial hydrosphere, water cycle and hydrology | 4DMED-Hydrology aims at developing an advanced, high-resolution, and consistent reconstruction of the Mediterranean terrestrial water cycle by using the latest developments of Earth Observation (EO) data as those derived from the ESA-Copernicus missions. In particular, by exploiting previous ESA initiatives, 4DMED-Hydrology intends: to demonstrate how this EO capacity can help to describe the interactions between complex hydrological processes and anthropogenic pressure (often difficult to model) in synergy with model-based approaches; to exploit synergies among EO data to maximize the retrieval of information of the different water cycle components (i.e., precipitation, soil moisture, evaporation, runoff, river discharge) to provide an accurate representation of our environment and advanced fit-for-purpose decision support systems in a changing climate for a more resilient society. 4DMED-Hydrology will focus on four test areas, namely the Po river basin in Italy, the Ebro River basin in Spain, the Hérault River basin in France and the Medjerda River basin in Tunisia, which are representatives of climates, topographic complexity, land use, human activities and hydrometeorological hazards of the Mediterranean Region (MR). The developed products will be then extended to the entire region. The resulting EO-based products (i.e., experimental datasets, EO products) will be made available in an Open Science catalogue hosted and operated by ESA. |
| 4DMED-SEA | The objective of the 4DMED-SEA project is to develop a data-driven, 4D reconstruction of the Mediterranean Sea physical and biogeochemical state, exploit this information to further improve our understanding of the complex interactions between [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | Marine Environment Monitoring, Mediterranean, ocean, Ocean Circulation, Ocean Temperature, Salinity and Density, sea surface topography | The objective of the 4DMED-SEA project is to develop a data-driven, 4D reconstruction of the Mediterranean Sea physical and biogeochemical state, exploit this information to further improve our understanding of the complex interactions between physical and biological processes at a broad range of temporal and spatial scales and explore options to transfer that knowledge into new solutions for society regarding the monitoring, restoration and preservation of the Mediterranean Sea Health. The project was kicked-off on June 22nd 2023. A meeting with FAO-GFCM (General Fisheries Commission for the Mediterranean Sea) took place on September 7th to present the 4DMED project and discuss possible collaboration during the Impact Assessment studies dedicated to Fisheries. |
| A MARKETPLACE FOR SATELLITE IMAGE TASKING | A key indication of the performance of earth observation is how easy, quick and affordable it is to collect fresh imagery of a location. This underpins the viability of value-added services and the credibility of the sector right across markets. [...] | GEOCENTO LIMITED (GB) | Enterprise | generic platform service, permanently open call | A key indication of the performance of earth observation is how easy, quick and affordable it is to collect fresh imagery of a location. This underpins the viability of value-added services and the credibility of the sector right across markets. It is our contention that fresh image collection rates poorly in this regard, particularly in relation to very high resolution optical imagery. If a customer wishes to obtain a fresh image of their area of interest, they have to select a supplier (typically based on reputation rather than informed knowledge), select a service (which can be complex and not necessarily a great fit to requirements), wait for a feasibility report, and then pay a supplier before knowing if the collection will be successful. To address this, we are developing EarthImages-on-Demand – a commercial service that drives standardised requests for very high resolution optical image collection to the network of imaging suppliers for cooperative fulfilment. This turns the current image collection protocol around 180 degrees in favour of customers by allowing them to specify what imagery they want, where and when and the price they are prepared to pay (via a simply interface), and then have the money released to the first supplier that delivers to specification within the requested time window. EarthImages-on-Demand will benefit the whole sector by creating a dynamic between demand and supply, encouraging competition for image collection (driving standards in delivery time and pricing) and supporting scalability through standardisation of imaging requests. We are looking to exploit these benefits by identifying and stimulating demand for the service in key markets, starting with some pilot projects, thus ultimately benefitting suppliers as well as customers through increased demand for image collection. |
| A Swarm, SuperDARN, and ICEBEAR Collaboration – Turbulent E-region Aurora Measurements (SSIC-TEAM) | Living Planet Fellowship research project carried out by Devin Huyghebaert. The Swarm SuperDARN ICEBEAR Collaboration – Turbulent E-region Aurora Measurements (SSIC-TEAM) project will focus on the Farley-Buneman Instability (FBI) and its [...] | UNIVERSITY OF SASKATCHEWAN (CA) | Science | ionosphere and magnetosphere, living planet fellowship, science | Living Planet Fellowship research project carried out by Devin Huyghebaert. The Swarm SuperDARN ICEBEAR Collaboration – Turbulent E-region Aurora Measurements (SSIC-TEAM) project will focus on the Farley-Buneman Instability (FBI) and its effects on plasma density irregularity and turbulence generation in the E-region ionosphere. A better understanding of the FBI is required due to its potential for turbulent heating of the ionospheric E-region plasma during active ionospheric events driven by magnetospheric and solar effects. Heating of the ionosphere affects plasma circulation patterns and neutral atmospheric dynamics. Understanding the sources of ionospheric heating is essential to better model and predict space weather impacts on the terrestrial atmosphere. The FBI is a plasma density instability that has a positive growth rate when electrons in a plasma have a velocity that is greater than the ion velocity by at least the ion-acoustic speed. This instability is able to occur in the E-region of the ionosphere, primarily at altitudes of 90-120 km. The instability generates plasma density irregularities at a multitude of characteristic wavelengths, where the growth rate and phase speed of the irregularities are related to the electron motion direction. Plasma density irregularities are a signature of plasma turbulence occurring in the ionosphere and can be measured using ground based ionospheric radars. Through the use of measurements from the Swarm satellite constellation and coherent scatter radars the physical phenomena associated with the FBI will be investigated. The magnetometer and Electric Field Instrument (EFI) will be used from the Swarm Alpha, Bravo, and Charlie satellites to provide essential context for the coherent scatter radar measurements. The Fast Auroral Imager (FAI) from the recently added Swarm Echo satellite will also be utilized to provide optical details of the region when available. For coherent scatter radars both the Ionospheric Continuous-wave E-region Bistatic Experimental Auroral Radar (ICEBEAR) and Saskatoon Super Dual Auroral Radar Network (SuperDARN) radars will be used in the studies. These radars are based out of the University of Saskatchewan in Canada and have a field of view located in the terrestrial auroral zone. Due to the recent advances in radio hardware and techniques it is now possible to obtain measurements from these different instruments on similar spatial and temporal resolution scales. |
| AALM4INFRAM: ARCTIC ACTIVE LAYER MONITORING FOR INFRASTRUCTURE MANAGEMENT | This project will use various InSAR based approaches to characterize changes in land subsidence rates due to permafrost melting in Greenland and assess the impact such changes are having on critical infrastructure in the region. | GAMMA REMOTE SENSING AG (CH) | Digital Platform Services | climate, land, permanently open call, SAR, snow and ice | This project will use various InSAR based approaches to characterize changes in land subsidence rates due to permafrost melting in Greenland and assess the impact such changes are having on critical infrastructure in the region. |
| ADVANCED AI BASED FEATURE DETECTION FOR SECURITY APPLICATIONS | Development and testing of novel Deep Learning based methods for detection and classification of priority features of interest (tents, vehicles, rotary wing aircraft etc). | SPACEKNOW, INC., odštěpný závod (CZ) | Enterprise | AI4EO, applications, security | Development and testing of novel Deep Learning based methods for detection and classification of priority features of interest (tents, vehicles, rotary wing aircraft etc). |
| ADVANCED AI4EO FOR WILDFIRE MONITORING | The Artificial Intelligence for Earth Observation (AI4EO) Wildfires project began in December 2020 and run for 8 months, focussing on developing and demonstrating a burned area (BA) mapping service that combines EO data, specifically [...] | CGI IT UK LIMITED (GB) | Enterprise | AI4EO, burned areas, mapping/cartography, Sentinel-2, wildfires | The Artificial Intelligence for Earth Observation (AI4EO) Wildfires project began in December 2020 and run for 8 months, focussing on developing and demonstrating a burned area (BA) mapping service that combines EO data, specifically Sentinel-2 optical data, with an AI-enabled algorithm. The project consortium is led by CGI UK, utilising their legacy of developing cloud-based EO-data processing portals, with project partner University of Leicester (UK) who has been involved in a number of projects focused on wildfire mapping including the European Space Agency (ESA) CCI Fire project. The AI4EO project and demonstration service has shown the potential of combining increasingly frequent and high-resolution satellite observations with AI/ML to provide improved BA mapping products to support wildfire management organisations. ML enables the service to be easily trained using real wildfire events over a range of differing biomes and scenarios to create a collection of mapping solutions. When executed, the demonstration service automatically selects the most relevant mapping solution to the scene, allowing the creation of a simple, easy to interpret, map of Burned Areas. The service is deployed on a cloud-based online processing platform, the EO4SD Lab. It provides useRs with a robust scalable service that creates Burned Area maps, which can be easily analysed and ingested into the user’s established systems. |
| Advanced Sentinel-1 analysis ready data for Africa | Historically for land application, synthetic aperture radar (SAR) satellite imagery has often been seen only as as complement to optical remote sensing in cloud covered areas. There are several reasons for this: 1) the threshold of [...] | NORTHERN RESEARCH INSTITUTE (NORUT) (NO) | Sustainable Development | permanently open call, SAR | Historically for land application, synthetic aperture radar (SAR) satellite imagery has often been seen only as as complement to optical remote sensing in cloud covered areas. There are several reasons for this: 1) the threshold of interpretation and understanding of SAR imagery is often perceived as very high to an untrained user, 2) the human capacity and technical capability in pre-processing SAR data has been out of reach without adequate, often expensive software, and technically-trained staff and 3) the availability of data has been too sparse and expensive for being used operationally for applications other than in (sub)-polar regions. This has especially been the case in developing countries. The Copernicus program, specifically the Sentinel-1A/B (S1) satellites, and recent international efforts opened for a new era of operational SAR application, data access and processing and overcome the challenges 2 and 3 above. Satellite open data cubes (ODC) are currently developed in several countries, including in Africa, with the aim to provide analysis ready data (ARD) from both optical and SAR sensors. The combination of both optical and SAR generally improves the application results. However, for SAR data these ARD efforts generally aim to provide only pre-processed, i.e. radiometric, terrain and slope corrected and georeferenced, single SAR scenes or, at the best, yearly mosaics with questionable consistency and reduce little the subjective reluctance of using SAR data operationally. The purely vast amount of single scenes therefore needs further processing in order to reduce the amount of data as well as to make the data more attractive and easier to interpret for untrained users. This project is intended to overcome user reluctance to integrate SAR data into their EO monitoring and assessment activities by making advanced SAR products available as Analysis Ready Data and demonstrate the possibilities of processing and integrating these data with conventional EO data in a cloud environment. The primary focus will be users in developing countries so the demonstration activities will explicitly take into account issues such as bandwidth constraints. |
| Advancing the Study of Extreme Weather Events with Data, Deep Learning Methods and Climate Analysis | EIDGENÖSSISCHE TECHNISCHE HOCHSCHULE ZURICH (ETH ZURICH) (CH) | AI4EO | atmospheric winds, climate | ||
| AEOLUS+ INNOVATION – IMPROVING DUST MONITORING AND FORECASTING THROUGH AEOLUS WIND DATA ASSIMILATION (NEWTON) | Windblown dust plays a key role in the Earth system, affecting climate, marine and terrestrial ecosystems, anthropogenic activities as well as humans’ health. Winds, acting as the main driving force of dust emission determine also the [...] | NATIONAL OBSERVATORY OF ATHENS (GR) | Science | Aeolus, Aeolus+ Innovation, Aerosols, atmosphere, atmosphere science cluster, science | Windblown dust plays a key role in the Earth system, affecting climate, marine and terrestrial ecosystems, anthropogenic activities as well as humans’ health. Winds, acting as the main driving force of dust emission determine also the spatiotemporal evolution of dust plumes during transport. The proposed study, entitled NEWTON, aims to demonstrate the potential improvement of short-term dust forecasts when the numerical simulations are initialized from meteorological fields in which Aeolus observations have been assimilated. To realize the overarching objective of NEWTON, regional dust simulations initialized with ECMWF numerical outputs, will be performed for specific regions of the planet, i.e. West Sahara-Tropical Atlantic Ocean and Eastern Mediterranean. The regional modelling approach will rely on the WRF model, in which critical developments have been implemented. These upgrades have been driven by recent studies, relying on advanced observations revealing that mineral particles are not appropriately treated in the current state-of-the-art atmospheric-dust models. In a nutshell, the NEWTON project aims to: Assess the potential improvements on short-term regional dust forecasts attributed to the assimilation of Aeolus wind profiles; Investigate the modifications of dust emission and transport mechanisms by contrasting numerical simulations initialized with and without Aeolus observations; Highlight the benefits and the necessity of Aeolus data on dust research, paving the way for future operational satellite missions.” |
| AEOLUS+ INNOVATION – OCEAN SUB-SURFACE PRODUCTS AND APPLICATIONS | The Aeolus Ocean Color (AOC) project aims at assessing the potential of the Aeolus mission to monitor ocean sub-surface optical and biogeochemical properties based on the measurements from the wind lidar ALADIN (Atmospheric Laser Doppler [...] | NOVELTIS SAS (FR) | Science | Aeolus, Aeolus+ Innovation, Aerosols, Altitude, atmosphere, atmosphere science cluster, Ocean Indicators, ocean optics, ocean science cluster, science | The Aeolus Ocean Color (AOC) project aims at assessing the potential of the Aeolus mission to monitor ocean sub-surface optical and biogeochemical properties based on the measurements from the wind lidar ALADIN (Atmospheric Laser Doppler Instrument) at 355 nm. AOC is funded by ESA within the framework of the Aeolus + Innovation project. The retrieval scheme for the AOC products relies upon parametric relationships between the lidar signal and the parameters of interest in a stepwise approach: “lidar-derived optical” parameters that can be inferred from the two lidar profiles in the Mie and Rayleigh channels: the particulate attenuated backscatter βP and the attenuation coefficient KL; “ocean optical” parameters related to ocean optical properties: the diffuse attenuation coefficient (Kd(355)) and the particulate back-scattering parameter (bbp(355)) that can be derived from the lidar-derived parameters; “biogeochemical”parameters: the particulate organic carbon (POC), the phytoplankton carbon (Cphyto) and the coloured dissolved organic matter (CDOM) that can be derived from the optical parameters. The prototype AOC product will be generated over a set of regions of interest (English Channel, tropical gyres, Polar Ocean), and evaluated against available ground truth as well as other comparable remotely sensed products and biogeochemical model simulations. |
| AEOLUS+ INNOVATION – STUDIES ON WIND AND AEROSOL INFORMATION FROM LIDAR SURFACE RETURNS (SWAILS+) | In the SWAILS+ project the Aeolus lidar surface returns are used in combination with collocated wind speed observations to retrieve the aerosol optical depth. The retrieval algorithm under development, LARISSA (Lidar Aerosol Retrieval based on [...] | KNMI (NL) | Science | Aeolus, Aeolus+ Innovation, Aerosols, Altitude, atmosphere, atmosphere science cluster, science | In the SWAILS+ project the Aeolus lidar surface returns are used in combination with collocated wind speed observations to retrieve the aerosol optical depth. The retrieval algorithm under development, LARISSA (Lidar Aerosol Retrieval based on Information from Surface Signal of Aeolus), will complement the standard Aeolus (L2) aerosol profile products. Not only as LARISSA provides an opportunity to evaluate the standard Aeolus aerosol products but also since the L2a profile approach lacks sensitivity in low aerosol loading regions where an integrated column approach may be more successful. In addition, for low aerosol optical depth conditions, it is investigated whether it is feasible to retrieve the: Near-surface winds Bidirectional reflectance distribution function over land, based on which aerosol optical depth over land can be also retrieved using LARISSA The LARISSA products are developed at the Royal Institute of Meteorological Sciences (KNMI) in the SWAILS (NSO) and SWAILS+ (ESA) projects. The resulting aerosol product from LARISSA will be beneficial for various scientific applications including Better understanding of the wind speed dependence in off-nadir ocean surface scattering in the ultraviolet. Evaluation of aerosol models, where the LARISSA-based (integrated) aerosol optical depth can be used as input for data assimilation. Studies of global aerosol optical properties as LARISSA will retrieve the average column lidar ratios. Support of future lidar missions with nadir and non-nadir viewing angles in the UV, i.e., the EarthCARE mission lidar ATLID. |
| AEOLUS+ INNOVATION – CDOM-PROXY RETRIEVAL FROM AEOLUS OBSERVATIONS (COLOR) | The objective of the COLOR (CDOM-proxy retrieval from aeOLus ObseRvations) project is to assess the feasibility of deriving an in-water AEOLUS product from the analysis of the ocean sub-surface backscattered component of the 355 nm signal [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | Aeolus, Aeolus+ Innovation, atmosphere, atmosphere science cluster, Ocean Indicators, ocean optics, ocean science cluster, science | The objective of the COLOR (CDOM-proxy retrieval from aeOLus ObseRvations) project is to assess the feasibility of deriving an in-water AEOLUS product from the analysis of the ocean sub-surface backscattered component of the 355 nm signal acquired by the ALADIN (Atmospheric LAser Doppler INstrument). The project will focus on the potential retrieval of the ocean particle optical properties at 355 nm: diffuse attenuation coefficient for downwelling irradiance, Kd [m-1], and sub-surface hemispheric particulate backscatter coefficient, bbp [m-1]. COLOR activities are organized in three different but interacting phases: 1) Consolidation of the scientific requirements; 2) Implementation and assessment of AEOLUS COLOR prototype product; 3) Scientific roadmap. Furthermore, data collection activity will feed phase 1 and 2, encompassing both AEOLUS dataset and the ancillary reference/validation datasets. The overall proposed approach is based on the transfer of the lidar consolidated know-how from atmospheric to oceanic applications through AEOLUS observation data analysis and ocean radiative transfer numerical modelling. |
| AEOLUS+ INNOVATION – LIDAR MEASUREMENTS TO IDENTIFY STREAMERS AND ANALYZE ATMOSPHERIC WAVES (LISA) | For a better comprehension of climate change it is fundamentally important how well we understand the general condition (dynamics and chemistry) in the atmosphere. Aeolus wind measurements enable for the first time the derivation of atmospheric [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | Aeolus, Aeolus+ Innovation, atmosphere, atmosphere science cluster, atmospheric winds, gravity and gravitational fields, science | For a better comprehension of climate change it is fundamentally important how well we understand the general condition (dynamics and chemistry) in the atmosphere. Aeolus wind measurements enable for the first time the derivation of atmospheric wave structures on different temporal and spatial scales and wind gradients in particular above the oceans, where wind measurements from ground-based instruments are sparse. These measurements will help us to better understand the atmospheric dynamics. Planetary waves (PWs) are global scale waves, which are well-known as main drivers of the large-scale weather patterns in mid-latitudes on time scales from several days up to weeks in the troposphere. When PWs break, they often cut pressure cells off the jet stream. A specific example are so-called streamer events, which occur predominantly in the mid- and high-latitudes of the lower stratosphere. During a streamer event the wind field changes rather strong over a comparatively small horizontal distance. It is found that streamer mainly occur at the transition zone from the Northern Atlantic to Europe. Strong wind gradients can excite gravity waves (GWs). GWs have typical vertical wavelengths from a few 100 m to some kilometers. GWs are the main drivers of the mean meridional circulation of the mesosphere and lower thermosphere. Their propagation is strongly dependent on the zonal wind in the stratosphere. The question of how much energy from the field of planetary waves is finally transferred into the generation of gravity waves is still an open question. Objectives Three data products will be derived by Aeolus measurements: global maps of horizontal wind shear, PW activity and GW activity. Supplementary measurements are used to further study acoustic GW activity at the ground and at large heights (Doppler sounding or microbarograph measurements). This allows a cross-check of the temporal evolution of the kinetic wave energy density and also provides additional information about the dynamic conditions in the stratosphere. The data products will be demonstrated within a case study of a selected streamer event. The Aeolus data will be compared with ERA-5 reanalysis data. The data products will be made available on a project web-site. The findings and recommendations of this project will be delivered through a scientific roadmap in order to further develop the methods and their application. |
| AEOLUS+ INNOVATION – OCEAN SURFACE WIND FROM AEOLUS SEA SURFACE RETURNS (SEA-FLECT) | Welcome to the SEA-FLECT project page. The winds from Aeolus lidar SEA surface reFLECTance (SEA-FLECT) aims to demonstrate the potential of the Aeolus observations for monitoring of sea surface winds. This project is funded [...] | Verisk Analytics GmbH (DE) | Science | Aeolus, Aeolus+ Innovation, atmosphere, atmosphere science cluster, Ocean Indicators, science | Welcome to the SEA-FLECT project page. The winds from Aeolus lidar SEA surface reFLECTance (SEA-FLECT) aims to demonstrate the potential of the Aeolus observations for monitoring of sea surface winds. This project is funded by ESA under the Aeolus + Innovation project. Objective The objectives of the Aeolus Ocean Surface Wind project are to Demonstrate if the Aeolus observations can be used to derive ocean surface winds, and Understand which meteorological and oceanic conditions are favourable to derive this product from the observations Method To meet the objectives, we will perform a detailed analysis of the Aeolus surface returns over selected regions, under different surface wind conditions. The surface wind information will be derived from scatterometer data, while the surface conditions will be determined from traditional imagery data as provided by e.g. Modis or Sentinel2. In addition detailed radiative transfer calculations will be performed to support the analysis. |
| AEOLUS+ PROCESSES | The "Aeolus+Processes" project addresses three major objectives of the Aeolus+Innovation program of ESA: use of Aeolus data for atmospheric process studies, use of Aeolus wind observations in the next generation of atmospheric reanalysis [...] | UNIVERSITY OF HAMBURG (DE) | Science | Aeolus, Aeolus+ Innovation, atmosphere, atmospheric winds, climate | The “Aeolus+Processes” project addresses three major objectives of the Aeolus+Innovation program of ESA: use of Aeolus data for atmospheric process studies, use of Aeolus wind observations in the next generation of atmospheric reanalysis (ERA6), and benefits of Aeolus wind observations for the modelling of the middle atmosphere. Furthermore, the project investigates multivariate effects of Aeolus wind profiles in the ECMWF data assimilation system. In particular, the effects of Aeolus are compared with the wind-field information derived from the assimilation of COSMIC2 GNSS-RO temperature data. |
| AI and EO as Innovative Methods for Monitoring West Nile Virus Spread (AIDEO) | AI and EO as Innovative Methods for Monitoring West Nile Virus Spread (AIDEO) is being developed by the Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”, a veterinary public health institution that has an established [...] | Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale” (IT) | Digital Platform Services | artificial intelligence, enterprise, health, permanently open call | AI and EO as Innovative Methods for Monitoring West Nile Virus Spread (AIDEO) is being developed by the Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”, a veterinary public health institution that has an established international track record in the surveillance, diagnosis, epidemiology, modelling, molecular epidemiology of Vector Borne Diseases (VBDs), AImageLab, that is a research laboratory of the Dipartimento di Ingegneria “Enzo Ferrari” at the University of Modena and Reggio Emilia with extensive experience in Computer Vision, Pattern Recognition, Machine Learning and Artificial Intelligence, Progressive Systems, that delivers solutions to simplify Earth Observation data exploitation and brings significant expertise and experience to the consortium based on years of collaboration with ESA and on-site presence at ESRIN, and REMEDIA Italia, that has relevant experience in designing and realising printed, web, multimedia and technology enhanced scientific communication projects, systems and tools developed inside the Earth Observation Department of ESA (ESRIN). Aim of the project is to develop an innovative, scalable and accurate process to produce West Nile Disease (WND) risk maps, using EO data and specific AI algorithms. Vector-borne diseases (VBDs) are an important threat with an increasing impact on public health due to wider geographic range of occurrence and higher incidences. West Nile virus (WNV) is one of the most spread zoonotic VBD in Italy and Europe. Identifying suitable environmental conditions across large areas containing multiple species of potential hosts and vectors can be difficult. The recent and massive availability of Earth Observation (EO) data and the continuous development of innovative Artificial Intelligence (AI) methods can be of great help to automatically identify patterns in big datasets and to make highly accurate predictions. Our project aims to develop an innovative, scalable and accurate process to produce West Nile Disease (WND) risk maps, using EO data and specific AI algorithms. Using historical ground truth data of WND cases and EO data derived from different sources (e.g. Sentinel-2, Sentinel-3, PROBA-V, etc.), a learning architecture, based on Convolutional Neural Network (CNN) and Graph Theory, will be applied on ground truth WND cases and satellite images and tested. This process will produce AI based risk maps that will be then compared with classical statistical methods to evaluate the degree of improvement in forecasting the disease occurrence and spread. Knowledge acquired with this project can be potentially used to define intervention priorities within national diseases surveillance plans. Moreover, the definition and development of algorithms working on available and frequent satellite images could be applied in early warning systems not developed so far, and could be integrated into the Information Systems of the Italian Ministry of Health and made available to other interested stakeholders. This work will therefore lay the basis for a future early warning system that could alert public authorities when climatic and environmental conditions become favourable to the onset and spread of the disease. This will be achieved in three key phases: Phase 1: Definition of requirements Information regarding EO data to be used, criteria to select ground truth data, temporal interval to be analysed and different Deep Neural Network models will be evaluated and defined. Selection criteria and preparation of remotely sensed products will then be investigated, considering data from multiple sources, various sensors, spectral bands, spatial resolutions and revisit times. WND and EO data will be selected to guarantee a correct spatial and temporal representation of the last ten-years epidemics. Phase 2: Data retrieval and processing WND cases will be extracted from the official repository of the Italian Ministry of Health (National Information System of Animal Disease Notification – SIMAN), integrated with laboratory data coming from the national veterinary laboratories, validated and selected, in space and time, according to the requirements defined in phase 1. WND ground truth outbreaks will be split in different datasets that will be used to train and test the DNN model, then fine-tune the model and hence make predictions and evaluate the overall accuracy. Selected EO data will be collected from different sources and stored in a centralised system where they will be organised and pre-processed according to the requirements defined in phase 1. Classical statistical models for WND spread (suitability analysis, logistic regression, etc.) will be developed to be compared with AI model performance. Phase 3: Train, fine-tuning and validation of the AI model AI models/algorithms for the analysis and prediction of WND “behaviour” will be developed and parameters estimated. Graph-based DNN models will be explored for merging geo-referenced local sites information with satellite images, the latter being processed through Convolutional Neural Networks (pre-trained or trained from scratch). Temporal deep models (e.g. RNN – Recurrent Neural Networks, LSTM – Long-short term memory) will then be employed for an effective forecasting of the behaviour based on EO data. The accuracy of the chosen model will then be evaluated together with the need to include additional data or to change the train model hyper-parameters. We will hence produce the final model that will be compared with the classical statistical models developed in phase 2. Dissemination of information and project results will last for the entire duration of the project and will be made available to stakeholders, relevant institutions, organisations and individuals through workshop and congress presentations, publications in peer reviewed journals, websites. |
| AI FOR ANIMAL CENSUS AND HABITAT MONITORING | Development of AI based methods to classify herds of different animals based on the spatial distribution patterns adopted within different herd species. AI based pattern recognition methods based on distribution patterns of animals within a herd [...] | EOLAS Insight Ltd (GB) | Enterprise | AI4EO, generic platform service, permanently open call | Development of AI based methods to classify herds of different animals based on the spatial distribution patterns adopted within different herd species. AI based pattern recognition methods based on distribution patterns of animals within a herd detected in EO imagery. |
| AI-based tillage detection for improved agricultural and climate policies | Our planet's population is growing rapidly, while climate change is causing more extreme weather events and changes in land-use. This creates a demand for better information services in policy-making, nature conservation, and food security. The [...] | KAPPAZETA LTD (EE) | AI4EO | agriculture, applications, climate, open call | Our planet’s population is growing rapidly, while climate change is causing more extreme weather events and changes in land-use. This creates a demand for better information services in policy-making, nature conservation, and food security. The European Commission’s Common Agricultural Policy (CAP) urges member states to embrace Earth Observation (EO) data as an integral part of the area monitoring system (AMS). At the same time, the carbon emission trading sector is growing, making it essential to monitor different agricultural practices. This project aims to address these pressing needs by enhancing existing artificial intelligence (AI) models and developing new ones. Primarily, we seek to support agricultural paying agencies in their transition to the AMS, where they have to rely mainly on satellite-based monitoring in agricultural checks. Furthermore, our AI-based tillage detection will play an important role in promoting sustainable agriculture as anticipated in the European Green Deal, distinguishing and rewarding low-impact practices that contribute to carbon sequestration. By combining AI and satellite data, this project represents a transformative step towards a greener and more informed agricultural landscape. |
| AI4ARCTIC | The AI for the Arctic (AI4ARCTIC) project applies deep learning, in particular deep convolutional neural networks, for Earth observation applications within the cryosphere, focusing on sea ice and snow. The project trains deep-learning systems [...] | NORWEGIAN COMPUTING CENTER NORSK REGNESENTRAL (NO) | Science | AI4Science, Arctic, polar science cluster, snow and ice | The AI for the Arctic (AI4ARCTIC) project applies deep learning, in particular deep convolutional neural networks, for Earth observation applications within the cryosphere, focusing on sea ice and snow. The project trains deep-learning systems from relevant training data, and tests and demonstrates the capability of deep learning by applying it to large-scale inference of cryosphere-related variables.The project focuses on two use cases, one on snow mapping in Scandinavia and the other on sea ice charting in the waters around Greenland. |
| AI4CH4: An End-to-End AI Framework for Methane Plume Detection and Quantification using Satellite Imagery | Methane (CH4) is a significant anthropogenic greenhouse gas, second only to carbon dioxide (CO2) in contributing to global warming. It constitutes approximately 25% of the warming effect since pre-industrial times. Traditional methods for [...] | C-CORE (CA) | Science | AI4Science, air quality, atmosphere, atmosphere science cluster, atmospheric chemistry, environmental impacts, health, Sentinel-5P | Methane (CH4) is a significant anthropogenic greenhouse gas, second only to carbon dioxide (CO2) in contributing to global warming. It constitutes approximately 25% of the warming effect since pre-industrial times. Traditional methods for monitoring methane emissions rely on bottom-up approaches, calculating emissions by multiplying activity levels with emission factors. Satellites offer a more efficient alternative, providing near-real-time information on national emissions by sector. This data serves as a baseline for establishing methane reduction goals and allows ongoing monitoring to assess progress. Unlike bottom-up inventories, which may have latencies of a few years, satellites enable the documentation of rapid changes in emissions. The “AI4CH4” project aims to revolutionize methane atmospheric monitoring using advanced state-of-the-art earth observation data and technology. With a clear focus on innovation, the project aims to address a critical gap in the current methane emission monitoring landscape. As such, the project’s key objective is to develop an advanced end-to-end AI model for automatic plume detection and quantification, surpassing the limitations of conventional physics-based techniques (e.g., high uncertainty, slow processing speed, and dependency to ancillary data, such as wind information). By leveraging the vast datasets from the harmonious synergy of Sentinel data and creating a comprehensive benchmark dataset of plumes, the AI4CH4 project promises automated and accurate identification and quantification of methane emissions based on the integration of advanced deep learning models. This cutting-edge project will advance our collaborations with GHGSat and Harvard University and holds the potential to significantly advance our understanding of methane emissions at various temporal and spatial scales, contributing to global transparency and support for more effective climate change mitigation efforts for a greener, more sustainable future. |
| AI4DROUGHT | AI4DROUGHT is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, and contributes to the ESA Extremes and Natural Disasters Science Cluster. The [...] | Lobelia Earth, S.L. (ES) | AI4EO | AI4EO, AI4Science, Ecosystems, science | AI4DROUGHT is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, and contributes to the ESA Extremes and Natural Disasters Science Cluster. The AI4SCIENCE ITT had 2 main objectives: Advancing Earth System Science: advancing our capacity to combine EO and AI to address a major scientific challenge: The observation, understanding and characterisation of multi-hazards, compound and cascade events and its impacts on society and ecosystems. Advancing Artificial Intelligence for EO: unlocking the full potential of Artificial Intelligence for Earth System Science with focus on two main AI challenges: physics-driven Artificial Intelligence and explainable AI. The AI4DROUGHT project will develop a methodology for the prediction of drought climatic events over the Iberian peninsula. The main objectives of the project are: to design the appropriate deep learning architectures that allow to maximize the extraction of information from both the EO-based datasets and the Seasonal Prediction Systems (SPS); to enhance the knowledge on the cause and effects of drought events by the combination of the complementary climate system descriptions provided by EO-based observations and Seasonal Prediction Systems (SPS) through the implementation of AI-based algorithms. The proposed methodology combining numerical climate models with AI driven approaches at different temporal and spatial scales to identify multi-hazards and cascading effects will be highly scalable, replicable and transferable to other regions and applications, thanks to data driven approaches and pipelines that permit to automate and continuously store climatic experiences. Additional information and resources can be found at the project website https://www.ai4drought.com/ |
| AI4DTE | The project analyses the potential of artificial intelligence technologies for a digital twin of the earth and determine a roadmap for further developments. digital twin of the earth will allow science and policy users alike to gain insights of [...] | DFKI GMBH (DE) | AI4EO | AI4EO | The project analyses the potential of artificial intelligence technologies for a digital twin of the earth and determine a roadmap for further developments. digital twin of the earth will allow science and policy users alike to gain insights of our earth system and will help with decision support. There are two key user groups of a digital twin of the earth: Scientific users will benefit from the data access and modelling capabilities that a digital twin of the earth provides Policy users will benefit from explanations and post-processed data that is accessible also to non-expert users. A digital twin of the earth shall allow access to a diverse set of data sources of our planet and the results of different kinds of models. These outputs shall be available on different detail levels, such that they can be used by both scientific users as well as policy users. The team focuses on identifying AI technologies that a digital twin of the earth can benefit from. We will both identify existing capabilities that are already available and will point out potential for further developments. |
| AI4DTE Software stack | Digital Twins of the Earth address decision support under uncertainty, providing a prognostic, evidence-based decision support capability representing the dynamic relationships between the physical and natural environments (the Earth System) and [...] | TELESPAZIO VEGA UK LIMITED (GB) | AI4EO | AI4EO | Digital Twins of the Earth address decision support under uncertainty, providing a prognostic, evidence-based decision support capability representing the dynamic relationships between the physical and natural environments (the Earth System) and society (such as socioeconomic pathways, adaptation and mitigation actions or governance). In accordance with this vision, the uses cases that may be envisioned for the digital twins must provide, inter alia: Quantifiable and comparable impact predictions in the Earth System and/or downstream impact sectors; Actionable information and evidence-based decision support based on comparison of predicted impacts resulting from varying initial conditions; Support to ex-ante Impact Assessment in the form of “what-if“ scenario analysis; and in addition, Must be explainable in major steps of modelling and simulations, enabling model inspection and user interpretation, and Estimate and propagate uncertainty relevant to users (e.g. for policy makers uncertainty could refer to the confidence levels of a predictive capability of a simulation) in all steps of the use case. AI will provide many fundamental building blocks at the data, modelling, and reasoning levels of the digital twins. Accordingly, the objectives of the AI4DTE SW stack project are to: Refine the understanding of constraints and requirements guiding the use of AI in DTE, and identify opportunities, risks, limitations and needs for further research and development; Develop, demonstrate and evaluate AI tools and techniques implementing the requirements and constraints for the use of AI in DTE; Set the stage for future operationalization of AI/ML capabilities and community tools required in DTE in the medium- (2-3 years) and longer-term (3-6 years); Enable a DTE user community to develop new AI-based applications and use cases for a variety of Earth System Models and DTs; Explore future operations concepts, such as iterative AI active learning pipelines (MLOps), to be used as community tools, including continuous feedback and update of input data and software, for future integration in more “operational” and constrained DestinE environments, Build and foster a community of AI4DTE solution providers and establish partnerships with ESM and DestinE user communities. In this context, the AI4DTE SW stack project will: Design, develop and deliver an AI4DTE SW Stack containing a representative subset of AI capabilities relevant to DTE across the data layer, the model layer and the decision support layer; Deliver an AI4DTE Integrated Development Environment (IDE) for demonstration purposes providing access to the AI4DTE SW Stack, allowing for the development and execution of AI-based DTE applications and use cases; Develop and deliver at least 2 DTE use cases based on the capabilities provided in the AI4DTE SW stack and IDE; Define and conduct a Pilot Demonstration Campaign, bringing together a small group of pilot users for a brief period of time, execute a demo aimed at showing full use of the system capability in a real-world albeit simulated context and capture results; Evaluate principles, opportunities, requirements, constraints and limitations of the use of AI in DTE, refine the concept and deliver a roadmap for further development advancing the state of the art and operationalization of AI4DTE; Engage and build partnerships with the AI4DTE provider and impact sector user communities. |
| AI4EO Accelerator | The AI4EO Accelerator bridges the gap between Artificial Intelligence and Earth Observation by connecting partners in industry, national and international organisations and the third sector with students on short innovative projects. Project [...] | BRITISH ANTARCTIC SURVEY (GB) | AI4EO | AI4EO | The AI4EO Accelerator bridges the gap between Artificial Intelligence and Earth Observation by connecting partners in industry, national and international organisations and the third sector with students on short innovative projects. Project themes are selected for their value, impact, feasibility, and relevance to earth observation research. The AI4EO Accelerator is a collaboration between ESA Φ-Lab and the UKRI Centre for Doctoral Training (CDT) in the Application of Artificial Intelligence to the study of Environmental Risks, hosted jointly by University of Cambridge and British Antarctic Survey. Over the last decade, rapid developments in digital technologies and in our capability to monitor our home planet from space with Earth Observation (EO) satellites resulted in large amounts of data. The rate at which data is generated is ever increasing for example by the new generation of satellites coming online, including the Copernicus system and New Space. The AI4EO Accelerator facilitates high impact innovative research sprints. To select end-user relevant topics, AI4ER partners who come from industry, the third sector as well as national and international institutions, help setting several environmental themes. Themes are focused into specific challenge questions which are tackled by the teams of AI4ER master students from December to March. The AI4EO Accelerator project aims to address questions raised by the current partners of the UKRI Centre for Doctoral Training (CDT) in the Application of Artificial Intelligence to the study of Environmental Risks. In addition to benefiting from the direct involvement of the partners in CDT activities, the students also benefit from exposure to a broad range of future career options nationally and internationally, within and beyond academia. |
| AI4EO Innovation pipeline for WFP partners – WFP Accelerator | The United Nations (UN) World Food Programme (WFP) is saving lives in emergencies and changing lives for millions through sustainable development. The “WFP Innovation Accelerator” based in Germany explores the disruptive innovations, [...] | WFP Innovation Accelerator (DE) | AI4EO | AI4EO | The United Nations (UN) World Food Programme (WFP) is saving lives in emergencies and changing lives for millions through sustainable development. The “WFP Innovation Accelerator” based in Germany explores the disruptive innovations, technologies and business models for the mother organisation WFP. This project seeks out cutting-edge innovations that use EO and AI technologies to address the challenges that WFP faces in its operations, while striving for business viability and industry leadership. The idea is to create an innovation pipeline to move from ideas to commercial applications, feeding into the ESA business programme. In particular, the project will source startups and SMEs, support the testing of prototypes, and then prepare them to apply for other incubation funding such as ESA and/or WFP Innovation Accelerator to further develop the prototype into a complete solution. |
| AI4EO Rapid Prototyping Environment (AiTLAS) | The amount of available satellite imagery data has been substantially growing since the start of the Sentinel missions. Nevertheless, applications of AI to EO data are still scarce. The main goal of the AiTLAS project is to facilitate the uptake [...] | Bias Variance Labs, svetovanje in r (SI) | AI4EO | AI4EO | The amount of available satellite imagery data has been substantially growing since the start of the Sentinel missions. Nevertheless, applications of AI to EO data are still scarce. The main goal of the AiTLAS project is to facilitate the uptake of EO data by AI experts and vice versa – the uptake of (advanced) AI methods by EO experts. This is achieved through the development of a comprehensive toolbox with resources such as: benchmarking tools, ready-to-exploit models, tools for learning models de novo, and semantically annotated datasets prepared in a format that is easy to use by AI methods. The AiTLAS (Artificial Intelligence Toolbox for Earth Observation)t oolbox potential and usefulness is showcased by the execution of three pilots: a development of an EO Data benchmarking repository; a Maya archeological sites challenge; and crop type prediction for Slovenia, the Netherlands and Denmark. AiTLAS targets two user groups: EO practitioners and AI practitioners. Considering the existing gap between the available EO imagery data and the developments in AI, AiTLAS is tailored for easy use by both user groups as follows. For EO practitioners, it provides easy-to-use interfaces to a variety of deep learning methods (through JSON file configurations and/or Jupyter notebooks). For AI practitioners, it provides easy-to-exploit EO data already implemented in AI-ready format. The AiTLAS toolbox includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as a repository of AI-ready Earth Observation (EO) datasets. It can be easily applied for a variety of Earth Observation tasks, such as land use and land cover classification, crop type prediction, localization of specific objects (semantic segmentation), etc. AiTLAS has several distinguishing properties: Maya archeological sites location;and crop type prediction for Slovenia, the Netherlands and Denmark. It is modular and flexible – allowing for easy configuration, implementation and extension of new data and models, It is general and applicable to a variety of tasks and workflows, It allows for fast and easy implementation of prototype solutions as well as implementation of complex analysis workflows. It is user-friendly. In sum, AiTLAS, aides the AI community to engage in EO related tasks, by providing access to structured EO data, but more importantly, it facilitates and accelerates the uptake of (advanced) machine learning (AI) methods by the EO experts, thus bringing these two communities closer together. |
| AI4FOOD | An unprecedented richness of data is captured by satellites every day, resulting in an ever-growing time series of EO data. Despite the extensive availability of data, there are still many challenges when defining procedures for extracting [...] | VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK VITO (BE) | AI4EO | agriculture, AI4EO, Food Security, land cover, Sentinel-1, Sentinel-2 | An unprecedented richness of data is captured by satellites every day, resulting in an ever-growing time series of EO data. Despite the extensive availability of data, there are still many challenges when defining procedures for extracting relevant information from long time series. The goal of the AI4FOOD project is to tackle the challenges that arise when requiring data fusion or advanced time series analytics. The AI4FOOD project investigates advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to develop new algorithms for the creation of fused (with a focus on Sentinel-1 SAR and Sentinel-2 optical) continuous data streams, and evaluate aspects such as time series predictability over different land environments. This is done by a consortium of industry experts on data fusion and time series techniques (University of Valencia and VITO, e.g., CROPSAR, SPIRITS, FAO-ASIS, ESA WorldCover and WorldCereal, ERC-SENTIFLEX, Cost-SENSECO network), and open-source implementation and operational service provision to users (Sinergise and VITO; i.e., Sentinel Hub, Terrascope, Euro Data Cube, openEO Platform, S2 Global Mosaic, eo-learn, s2cloudless, EO Browser, WatchItGrow platform, ESA-MEP and other initiatives by the partners). Within AI4FOOD, the consortium strives to create an open-source, modular, extensible, and reusable toolbox, called fuseTS. To support the fusion of complementary EO data streams and time series analytics, relevant algorithms will be integrated into the toolbox as a service. One of the objectives of the project is to develop a data fusion framework for Sentinel-1 SAR and Sentinel-2 multi-spectral data, taking advantage of state-of-the-art ML approaches and allowing the creation of fused data streams for various target variables. Data fusion can become particularly interesting in the context of land monitoring, where a temporal dense time series is crucial to detect various. For example, in areas affected by frequent cloud cover, optical satellite imagery is often insufficient to reconstruct detailed time series. By integrating algorithms such as Multi Output Gaussian Process Regression (MOGPR), the Whittaker smoother or Deep Learning based methods (e.g., GANs), the framework will provide several options for users to fuse and enhance different EO data streams. Figure 1 Data fusion example reconstructing a cloud affected image. Time Series Analytics While data fusion can lead to temporally continuous data streams, actual information extraction from these fused data streams requires a time series modelling and analytics framework. The project aims at integrating several algorithms for time series fitting and characterization from which information about land surface dynamics can be extracted. This includes change detection for gradual trends, abrupt changes, and periodical behavior e.g. related to growing seasons. Figure 2 Automatic identification of some seasonal patterns by using the reconstructed LAI curve(GPR: Gaussian Process Regression, STD: Standard Deviation, SOS/EOS: Start/End of Season, LOS: Length of Season) On-Demand Service Next to the FuseTS Python library, which can be installed locally, the AI4FOOD toolbox will also be made available as a cloud-based on-demand service. For the actual deployment, existing operational services such OpenEO platform (VITO, Sinergise) and Euro Data Cube (Sinergise) will be used. This cloud-based implementation will lead to a scalable software-as-a-service (SAAS) approach ensuring that a wider group of users will be able to implement data fusion and time series analytics techniques to develop EO-based services. Use case driven The algorithms that are included in the toolbox are demonstrated through 3 real-life use cases: Subtle Land Cover Change Monitoring (FAO) Cropland Phenology Indicators (ITACyL) Agriculture and Land Management Activities Identification (Agency for Agricultural Markets and Rural Development, Slovenia) Code repositories: https://github.com/Open-EO/FuseTS https://open-eo.github.io/FuseTS/ Notebooks: https://github.com/Open-EO/FuseTS/tree/main/notebooks |
| AI4IS: AI FORECASTING FOR ICE SHELF CALVING | The instability of Antarctic ice shelves is one of the most critical open questions in polar science, due to its capacity to drive rapid sea level change at - and beyond - current high-end climate projections. Yet forecasting future instability [...] | Science [&] Technology Norway (NO) | Science | AI4EO, AI4Science, Antarctica, polar science cluster, snow and ice | The instability of Antarctic ice shelves is one of the most critical open questions in polar science, due to its capacity to drive rapid sea level change at – and beyond – current high-end climate projections. Yet forecasting future instability is notoriously difficult because of the complex, non-linear forcing mechanisms controlling an ice shelf’s response, including calving at the ice margin. As a result, the timescales for ice shelf collapse forms one of the largest uncertainties in modelling future sea level scenarios. In AI4IS we aim to develop the first AI-based forecasting system for iceberg calving of Antarctic ice shelves. Our AI model, which will fundamentally be built to include Explainable AI (XAI) techniques, will consume a bespoke 4-D multivariate data cube of EO products, complemented with process-model simulations of key climate parameters. Our 4-D data cube will be assembled using a novel Gaussian random field representation approach that our team have recently developed, which is computationally efficient and preserves sub-grid scale information. |
| AI4Platform: INFER – artIficial iNtelligence for Food sEcuRity – | The artIficial iNtelligence for Food sEcuRity - INFER - Project aims to foster adoption of AI models for Earth Observation (EO) applications. Many initiatives have been recently launched by ESA to augment the availability of training data, to [...] | CGI ITALIA S.R.L. (IT) | Digital Platform Services | AI4EO, Food Security, platforms, thematic exploitation platform | The artIficial iNtelligence for Food sEcuRity – INFER – Project aims to foster adoption of AI models for Earth Observation (EO) applications. Many initiatives have been recently launched by ESA to augment the availability of training data, to support new ideas through creation and management of challenges, and to incrementally adopt standards that facilitate interchange and reuse of resources. This project has to goal to focus on a more operational aspect, e.g. to enhance existing cloud-based processing oriented platforms (e.g. TEPs, DIAS and other initiatives) by adding AI specific capabilities. These capabilities include the possibility of performing the following: Facilitate creation or improvement of existing models, by running on an already established platform providing seamless access to data and scalable processing resources. Facilitate access to existing training datasets and exchange of training datasets within a community. Provisioning of AI-oriented tools in a unique environment which serves as an experimental lab for Data Scientists. Supporting the possibility for third parties to deploy and make available AI models and training datasets with a predefined remuneration model. We are proposing a simple and robust implementation approach, which is based on the FS-TEP. This platform is already listed in the services offered by the NOR. The platform will be enhanced with additional AI-related features and with an enhanced module supporting fine grained accounting to enable the required business models. The consortium will be led by CGI, who has extensive expertise in developing and operating distributed EO-processing platforms and will integrate a set of tools developed during previous activities, including an ESA activity sponsored by the Open Call mechanism, during which a suite of AI-oriented tools were developed and demonstrated. The consortium will be complemented by 2 partners with solid expertise in EO and with a focus on the AI adoption, namely: KP Labs, very active in the field of AI activity in ESA will implement a showcase based on super-resolution for hyperspectral data, by leveraging the finding of other related projects. KP Labs will be the independent entity validating the service Vista, the prime contractor of the FS-TEP will bring another showcase focusing on crop mapping and will also complement the consortium with the relevant business-oriented expertise derived from selling commercial EO services to third parties and from the direct management of the NOR offering |
| AI4SNOW-ARTIFICIAL INTELLIGENCE FOR SNOW COVER IN MOUNTAIN REGIONS | The component of the Earth System addressed in this project is snow cover in mountain regions. The main scientific and technical objectives of AI4Snow are the development and training of AI methods to greatly improve remote sensing-based snow [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | AI4Science, hydrology science cluster, snow and ice | The component of the Earth System addressed in this project is snow cover in mountain regions. The main scientific and technical objectives of AI4Snow are the development and training of AI methods to greatly improve remote sensing-based snow cover products for mountain regions as well as the implementation of data cubes containing all necessary datasets to apply these AI methods to the desired study regions. The aim is to produce a consistent, gapless, high resolution set of snow products suitable for highly detailed analyses even within complex terrain. The data cubes constituting the basis for these products shall be designed in a way that makes the application of the AI methods easily scalable and transferrable to any desired region of interest. The training of the AI models will be performed relying on an innovative approach which combines a physical-based snow process model with the remote sensing-based and meteorological datasets. This approach provides a very high density of available training data covering three large test domains within Switzerland, ensuring that a huge variety of topographic, climatic, and land cover characteristics will be represented. The project will include a scientific application/a scientific case, where the results produced by the developed AI-models will be used in a hydrological model. The results from this model will be compared with the outputs based on traditional input data, which shall demonstrate the value of the AI4snow-developments. |
| AIOPEN | The AIOPEN project will combine and extend the existing platform ASB (Automated Service Builder), EOPEN (Open Interoperable Platform for Unified Access & Analysis of EO Data) and EOEPCA (EO Exploitation Platform Common Architecture) with new [...] | SPACE APPLICATIONS SERVICES S.A./N.V. (BE) | Digital Platform Services | AI4EO, generic platform service, platforms | The AIOPEN project will combine and extend the existing platform ASB (Automated Service Builder), EOPEN (Open Interoperable Platform for Unified Access & Analysis of EO Data) and EOEPCA (EO Exploitation Platform Common Architecture) with new and innovative services based on operationally mature AI/ML software capabilities to provide a platform that supports the end-to-end AI model development lifecycle. The platform, hosted in the ONDA DIAS, owned by Serco, will be capable to distribute processing tasks in remote environments. The result will be a public commercial service offering a dynamic pricing structure with a remuneration policy for contributors to the platform content (with models or data) or for performing activities such as labelling data and training AI models. AIOPEN will bring together: the processing and data access capabilities of a powerful and flexible platform, the users interested in offering training datasets and AI/ML models, and the EO science and application development community looking at how to exploit these technologies with EO data. The service will allow versioning, sharing and customising the various AI/ML resources and provide the tools to integrate/exploit the AI/ML models in new applications, for example exposing these ones via programming interfaces for running predictions. Based on the Automated Service Builder (ASB) and EOPEN, developed by Space Applications Services, AIOPEN will allow importing custom processes, creating workflows and executing them in a distributed environment to deliver services on user customisable dashboards. Components from ESA/ESRIN EO Exploitation Platform Common Architecture (EOEPCA) project, led by Telespazio, will be included to bring interactive development, cataloguing and sharing capabilities. Popular open-source software will be integrated to include AI capabilities required by the AI model development lifecycle such as the ability to version and store model training projects, publish available models and datasets, annotate raw data, further train models and use models to do predictions. Key operations such as model training and predictions generation will also be available through programming interfaces. Validation Showcases In the course of the project, two showcases related to the Space for a Green Future theme will be implemented using the platform in order to demonstrate and validate its AI capabilities: Forest cover monitoring, proposed by KP Labs, and Urban Change Detection with Transformer Architecture, proposed by IT4Innovations (VSB —Technical University of Ostrava). Forest cover monitoring, including deforestation tracking, can be achieved via segmentation and comparison of segmentation masks. This approach enables the usage of standard, well-known, favourably supervised, architectures like U-Nets for image segmentation. Moreover, images taken at any time interval can be subjected to this type of deforestation analysis. The deforestation tracking will use segmentation as an intermediate step. The resulting model will offer services like generating forest coverage masks, deforestation masks (via subtraction of forest masks), and quantification of deforestation (% of forests that were lost in the given time interval). In the second showcase proposed by IT4Innovations we use EO data and Deep Neural Networks (DNNs) to detect (urban) related changes on the Earth’s surface to construct a digital twin of Earth’s (urban) changes. Detection of how urban areas, cities, infrastructure, and urban sprawl change over time helps to understand the dynamics of how the environment is impacted, to identify new (illegal) settlements, and to extrapolate trends for future planning. The showcase uses modern transformer based architectures to demonstrate the versatility and performance of DNNs for urban change detection. |
| AIREO – AI ready EO training datasets | Artificial Intelligence (AI) and Machine Learning (ML) algorithms have great potential to advance processing & analysis of Earth Observation (EO) data. Training datasets (TDS) are crucial for ML and AI applications but they are becoming a [...] | NATIONAL UNIVERSITY OF IRELAND (NIU GALWAY) (IE) | AI4EO | applications, artificial intelligence, enterprise | Artificial Intelligence (AI) and Machine Learning (ML) algorithms have great potential to advance processing & analysis of Earth Observation (EO) data. Training datasets (TDS) are crucial for ML and AI applications but they are becoming a major bottleneck in more widespread and systematic application of AI/ML in EO. The issues include: General lack and inaccessibility of high-quality TDS Absence of standards resulting in inconsistent and heterogeneous TDS (data structures, file formats, quality control, meta data, repositories, licenses, etc.) Limited discoverability and interoperability of TDS Lack of best-practices & guidelines for generating, structuring, describing and curating TDS Another obstacle to the use of AI/ML in EO applications for non-EO experts is a lack of domain specific knowledge such as map projections, file formats, calibration and quality assurance. As such, AI-Ready EO Training Datasets (AIREO) should be self-explanatory, follow FAIR principles and be directly ingestible for AI/ML applications. AIREO approach: Review current initiatives, activities, techniques,tools, practices and requirements for preparing, using and sharing AI-Ready EO Training Datasets Setup AIREO network of stakeholders and practitioners in the AI/ML, EO, data science in communities and from other relevant science disciplines. Capture community requirements and develop: Specifications for AIREO datasets by leveraging existing formats and standards; Best-practices guidelines for preparing, using and sharing AIREO TDS; Pilot and benchmark AIREO datasets for selected use-case applications ; A Python library, compatible with OGC web; interface standards and RESTful APIs, for ingesting AIREO TDS into workflows; Jupyter notebooks showing the use of AIREO pilot datasets & Python library. AIREO specifications, best practices and datasets will: Meet FAIR (Findable, Accessible, Interoperable, Reusable) data principles; Involve and build on top of relevant community initiatives All the project resources are available at: https://www.aireo.net/aireo-training-dataset-pilot-datasets/ |
| AIRSENSE | Project overview AIRSENSE's main objective is to enhance the understanding of aerosol and aerosol-cloud interactions. This activity is part of Atmosphere Science Cluster of ESA’s EO Science for Society programme, an element of the ESA FutureEO [...] | GRASP-SAS (FR) | Science | Aerosols, atmosphere, atmosphere science cluster, Sentinel-2, Sentinel-3, Sentinel-5P | Project overview AIRSENSE’s main objective is to enhance the understanding of aerosol and aerosol-cloud interactions. This activity is part of Atmosphere Science Cluster of ESA’s EO Science for Society programme, an element of the ESA FutureEO programme, which aims at boosting Europe’s excellence in EO science and its applications. One of the goals of this programme is to establish a strong coordinated scientific effort in Europe on Aerosol and Aerosol/Cloud interaction research by promoting a cooperation between activities launched by ESA and the European Commission (EC), in particular with CLEANCLOUD and CERTAINTY projects that were selected under the EC Horizon Europe Call “Improved knowledge in cloud-aerosol interaction” (HORIZON-CL5-2023-D1-01-04). AIRSENSE objectives Support algorithms development for multi-mission approach promoting synergies between different space-borne instruments to compensate for individual weaknesses allowing the creation of long Aerosol Optical properties (e.g., AOD, AE) time series (i.e., Aerosol_CCI) combining mid resolution satellite such as Sentinel5-p and CO2M with high resolution sensors such as PRISMA and Sentinel-3. Explore the capability of new aerosol and cloud products from existing (e.g. POLDER) or upcoming (CO2M, PACE, MAIA) Multi Angle Polarimeters (MAP) to infer aerosol characterization and absorption properties developing products such as Angstrom Exponent (AE), Single Scattering Albedo (SSA), Absorbing Aerosol Optical Depth (AAOD) and Fine mode Aerosol Optical Depth (AODF) but also Cloud Condensation Nuclei (CCN) and their role in climate and radiative forcing of the Earth system. Maximize the scientific impact of EarthCARE (in combination with additional EO missions and ground observations) in terms of novel observations and enhance scientific understanding of cloud, aerosol properties and their interactions: e.g., Long-term assessments in combination with Aeolus and CALIPSO data; aerosol-cloud interactions from the synergy between space- and ground-based instruments, study of precipitation initiation processes, characterisation of convection with synergistic GEO and LEO satellite observations, light precipitation and low-level oceanic clouds, global estimates of hydrometeors sedimentation rates, etc. Study the effects of cloud screening and aerosol retrievals in partly cloudy scenes, develop and improve the capabilities to detect aerosol above clouds and over challenging scenarios such as snow, ice shelves and in low illumination conditions such as the Arctic. Study cloud height, aerosol-cloud interactions and chemistry to understand the processes that can lead to cloud formation and to infer radiative properties of different cloud and aerosol types. Improve the quantification of the impact of 3D cloud shape and cloud shadow on cloud retrievals and for the impact of 3D cloud effects and apply this to aerosol retrievals close to clouds edges. Investigate the aerosol influence on the hydrological cycle fostering the use of aerosols products in combination with water vapour and water vapour isotopologues satellite observations. Investigate aerosol and cloud observations from Aeolus and extend this into the use of ATLID on EarthCARE with respect to humidity-growth effects in different areas of the world and for different aerosol types by comparing them with ground-based measurements during nearby overpasses; Make use of multiwavelength polarization Raman lidars that comprise also water-vapour channels are best suited for the detection of changes in scattering properties at high relative humidity. Improve the capabilities to detect stratospheric aerosol with a classification scheme allowing their separation by sources. Build on existing work and enhance the generation of stratospheric aerosol CDRs Advance the retrieval of aerosol vertical profiles fostering the simultaneous use of active and passive satellite instruments considering lessons learnt from Aeolus, but mainly novel EarthCARE products and validation activities Support (coordinated) activities on the radiative forcing due to aerosol-cloud interactions and the anthropogenic contribution on it considering lessons learnt from Aeolus and the future availability of EarthCARE mission products that will provide vertical information about aerosol particles and clouds (e.g., shape, size, type, amount). Support (coordinated) activities on the effect of climate and air quality on cloud properties, relevance for extreme events such as heavy rainfall, hailstorm, etc. Support (coordinated) activities to quantify the improvement of the numerical weather predictions (NWP), Earth System Models (ESM), and for the understanding of atmospheric dynamics and its interaction with the water cycle related to the development of novel aerosol products. Capitalise on novel EO-based capabilities, in particular EarthCARE observations, to advance our understanding and characterisation, including uncertainty reduction, of radiative forcing due to aerosol-cloud interactions and the anthropogenic contribution on it considering lessons learnt from Aeolus and the future availability of EarthCARE mission products that will provide vertical information about aerosol particles and clouds. Capitalise on novel EO-based capabilities, in particular EarthCARE observations, to advance understanding of atmospheric dynamics and its interaction with the water cycle related to the development of novel aerosol products and potentially numerical weather predictions (NWP). |
| AKROSS: Altimetric Ku-Band Radar Observations Simulated with SMRT | Accurate estimates of sea ice thickness are essential for numerical weather prediction, ice extent forecasts for navigability and to demonstrate the impacts of climate change on sea ice. The main source of uncertainty in sea ice thickness [...] | CORES SCIENCE AND ENGINEERING LIMIT (GB) | Science | altimeter, CryoSat, permanently open call, polar science cluster, science, snow and ice | Accurate estimates of sea ice thickness are essential for numerical weather prediction, ice extent forecasts for navigability and to demonstrate the impacts of climate change on sea ice. The main source of uncertainty in sea ice thickness measurements from radar altimetry is due to snow. Scattering of the radar signal as it travels through snow changes the return received by the altimeter. AKROSS will determine how snow properties affect the radar return and therefore the accuracy of sea ice thickness estimates. AKROSS has three main objectives: Collection of a suite of field observations of the properties of snow on sea ice suitable for evaluation of electromagnetic models across a range of different satellites, with a focus on radar altimetry. Evaluation and consolidation of the Snow Microwave Radiative Transfer Model in altimeter mode. Investigate origin of signal returns through analysis of the dependence of the altimeter waveform to snowpack structure. The field campaign will take place in Eureka, Canada, timed to coincide with CryoSat2 and ICESat2 satellite overpasses. Snow measurements will include specific surface area, density, layer boundary roughness and casted samples for x-ray tomography imaging. AKROSS will complement and co-ordinate with other activities including studies for the Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) candidate mission. |
| ALBATROSS – ALtimetry for BAthymetry and TideRetrievals for the Southern Ocean, Sea ice and ice Shelves | The ALBATROSS Project (ALtimetry for BAthymetry and Tide Retrievals for the Southern Ocean, Sea ice and ice Shelves) , led by NOVELTIS in collaboration with DTU, NPI and UCL, is one of the activities funded by ESA in the frame of the Polar [...] | NOVELTIS SAS (FR) | Science | altimeter, Antarctica, bathymetry and seafloor topography, CryoSat, cryosphere, Glaciers and Ice Sheets, oceans, polar science cluster, science, tides | The ALBATROSS Project (ALtimetry for BAthymetry and Tide Retrievals for the Southern Ocean, Sea ice and ice Shelves) , led by NOVELTIS in collaboration with DTU, NPI and UCL, is one of the activities funded by ESA in the frame of the Polar Science Cluster, with the objective to foster collaborative research and interdisciplinary networking actions. In this framework, the ALBATROSS ESA Project aims to improve knowledge about bathymetry and ocean tides in the Southern Ocean.The knowledge about ocean tides is at the crossroads of many scientific fields, especially in the Polar regions, as it has significant impact on ocean circulation modelling and the understanding of the coupled dynamical response of the ocean, sea ice and ice shelves system, the quality and accuracy of sea surface height and sea ice parameter estimates from satellite altimetry, or the understanding of ice-shelf dynamics, for example.Today, this knowledge is still limited by several aspects, such as the quality of bathymetry information, hydrodynamic model resolution and in situ and satellite observations availability for data assimilation and model validation. The objectives of the project are the following: Improve the knowledge on bathymetry around Antarctica, considering decade-long most recently reprocessed CryoSat datasets, innovative information on bathymetry gradient location through the analysis of sea ice surface roughness characteristics, and the compilation of the best available datasets in ice-shelf regions. Improve the knowledge on ocean tides in the Southern Ocean through the implementation of a high-resolution hydrodynamic model based on the most advanced developments in terms of ocean tide modelling, and data assimilation of observations, including satellite-altimetry derived tidal retrievals from the most recent and relevant satellite altimetry products. Improve satellite altimetry retrievals of sea surface heights and sea ice information thanks to the new tidal model solution. Improve the retrievals of ice shelves parameters thanks to the new tidal model solution. Share information and knowledge with other Polar science initiatives and projects. The ALBATROSS Project was launched in May 2021 and will span over two years. ——————————————————————————————————————- Presentation at the Living Planet Symposium (LPS22): ALBATROSS: Improving the bathymetry and ocean tide knowledge in theSouthern Ocean with satellite observations, M. Cancet, O. Andersen,M. Tsamados, G. Moholdt, F. Lyard, M. Restano, J. Benveniste ——————————————————————————————————————- PROJECT DOCUMENTS ALBATROSS ‐ Progress Report for First Quarterly Review PUBLICATIONS & COMMUNICATIONS Cancet M., Lyard F., Andersen O., Tsamados M., Moholdt G., Benveniste J., ALBATROSS, ALtimetry for BAthymetry and Tide Retrievals for the Southern Ocean, Sea ice and ice Shelves, presentation at the ESA Polar Science Cluster Collocation virtual Meeting, 15-17 September 2021 Cancet M., Fouchet E., Sahuc E., Lyard F., Andersen O., Dibarboure G., Picot N., Benveniste J., Improvement of the Bathymetry and Regional Tidal Modelling in the Arctic Ocean, presentation at the CryoSat 10th Anniversary Conference virtual event, 14-17 June 2021 (Announcement of the launch of the ALBATROSS project) ——————————————————————————————————————- The ALBATROSS Mid-Term Review meeting was held on the 23rd of June2022. The work on the bathymetry, coastline and grounding linedatasets that will feed the hydrodynamic tidal model is almostcompleted. Hydrodynamic tidal simulations have been performed inorder to assess the accuracy of the new bathymetry datasets andprovide feedback about improved areas and regions where furtherimprovements may be needed. The exploratory work on the linkagesbetween sea ice surface roughness computed from MISR data,bathymetry features and vertical tidal excursions shows promisingresults and could be used as a complementary tool to assess therealism of some features in the bathymetry models. Finally, thetidal harmonic constituents retrieved from 10 years of CryoSat-2observations in the Southern Ocean provide an invaluable validationdatabase for the tidal model, bridging the gap between the scarcecoastal in-situ observations and the Topex/Jason conventionalaltimetry observations that are limited to 66°S and stronglyaffected by the presence of sea ice. The implementation of the newhigh-resolution tidal atlas will continue in the coming months andwill be followed by an assessment phase |
| ALBIOM (ALtimetry for BIOMass) | The ALBIOM project (ALtimetry for BIOMass) proposes to derive forest biomass using SAR Altimetry Data from the Copernicus Sentinel-3 (S3) Mission. Biomass is at present monitored globally using optical satellites, SAR and LiDAR technology, [...] | DEIMOS SPACE UK LTD (GB) | Science | altimeter, Biomass, biosphere, carbon cycle, carbon science cluster, forestry, land, Sentinel-3 | The ALBIOM project (ALtimetry for BIOMass) proposes to derive forest biomass using SAR Altimetry Data from the Copernicus Sentinel-3 (S3) Mission. Biomass is at present monitored globally using optical satellites, SAR and LiDAR technology, but it is still poorly quantified in most parts of the world, and the satellite data currently exploited for this purpose are not enough to achieve the goal of global biomass mapping and monitoring with sufficient accuracy. In this context, data from existing satellites but unexploited so far, capable of providing additional independent biomass information, have the potential for a very important role in global observation of biomass, advancing our understanding of the carbon cycle and management of forests, biodiversity and ecosystems. The ALBIOM project combines: A modelling component, through the development of a Sentinel-3 altimeter backscattering simulator over vegetated areas, based on the existing state of the art modelling of the backscattering of Ku and C-band signals from vegetation, to establish the physical relationships between the backscattered signal from S3 altimeter and the different levels of biomass; An algorithm component, through the development of a suitable inversion algorithm for biomass estimation from S3 altimeter data, investigating both a simple method based on error minimization (i.e. derivation of analytical or empirical model function) and a more empirical Artificial Neural-Network (ANN) approach trained on the model outputs, or on a combination of model outputs and data; A prototype biomass product is generated as final project output over specific sites of boreal and tropical forests and shared with a number of users to assess its validity. ALBIOM is an innovative project, since both the use of Sentinel-3 SAR altimeter data to retrieve biomass and the generation of a Sentinel-3 SAR altimeter backscatter simulator over vegetated areas have not been accomplished before. The outcome of such project will have an important scientific impact, as it can provide a new global biomass dataset derived from S3 altimetry, which could be integrated into existing high-resolution biomass products derived from data fusion methods. The project would also open up new perspectives on the use of all the historical data from the past altimetry missions for biomass mapping. Users potentially interested in the results of ALBIOM include environmental agencies, space agencies, private companies, and all the entities interested in bioenergy, deforestation and forest degradation, biodiversity conservation, and sustainable management of biomass resources. This 12 month activity is led by Deimos Space UK with the participation of University of La Sapienza (IT) and Tor Vergata University (IT). ============================================================================ Methods and Results The developed Sentinel-3 SRAL altimeter waveforms simulator, obtained through the modification & merging of the Tor Vergata Vegetation Scattering Model (TOVSM) and the Soil And Vegetation Reflection Simulator (SAVERS), can simulate both bare soil and forest backscattered waveforms. Simulated signals have been compared to both innovative Sentinel-3 waveforms, provided by the G-POD SARvatore for Sentinel-3 service (now moved to the ESA Altimetry Virtual Lab on EarthConsole®), and official Sentinel-3 L2 products. The analysis of results over different types of surfaces has shown that waveforms related to forested surfaces present at least two peaks, due to the top of canopy and the ground. The presence of topography may introduce other peaks in the waveforms making the identification of vegetation and topographic effects very challenging. Despite these composite patterns, the developed simulator proved its capability to reproduce the main characteristics of Sentinel-3 waveforms. Citations De Felice Proia G.,Restano M., Comite D.,Clarizia M.P., Benveniste J., Pierdicca N. and Guerriero L., “AnElectromagnetic Simulator for Sentinel-3 SAR Altimeter WaveformsOver Land—PartI: Bare Soil,” in IEEE Transactions on Geoscience and RemoteSensing, vol. 60, pp. 1-11, 2022, Art no. 2007211, doi:10.1109/TGRS.2022.3210720. De Felice Proia G.,Restano M., Comite D.,Clarizia M.P., Benveniste J., Pierdicca N. and Guerriero L., “AnElectromagnetic Simulator for Sentinel-3 SAR Altimeter WaveformsOver Land—PartII: Forests,” in IEEE Transactions on Geoscience and RemoteSensing, vol. 60, pp. 1-10, 2022, Art no. 2007310, doi:10.1109/TGRS.2022.3210722. ESA Altimetry Virtual Lab: https://earthconsole.eu/wp-content/uploads/2022/03/SARvatore_br_singlepages_220315.pdf ============================================================================ |
| AlpGlacier | The Glacier Science in the Alps project is part of the Alps Regional Initiative and is aimed at maximising the scientific return of European investments in EO specifically from Sentinel-1 and Sentinel-2 specifically to provide first enhanced [...] | UNIVERSITY OF ZURICH (CH) | Regional Initiatives | Alps, cryosphere, Glaciers and Ice Sheets, hydrology science cluster, polar science cluster, science, Sentinel-1, Sentinel-2, snow and ice, water resources | The Glacier Science in the Alps project is part of the Alps Regional Initiative and is aimed at maximising the scientific return of European investments in EO specifically from Sentinel-1 and Sentinel-2 specifically to provide first enhanced observation capacity for glaciers in the Alps beyond area to glacier velocity and end of season snow cover on a weekly-annual basis and second to provide a scientifically sound assessment of hazard state as a direct function of glacier change, specifically, lake size and slope movement around glaciers. This project attempts to provide a wall-to-wall coverage of glaciers in the Alps for the full Sentinel era and will analyse changes taking place in this time period and in contrast with earlier data from the EO archives. Discover more projects, activities and resources on the Alps regional initiative (EO4ALPS) page. |
| AlpLakes | The AlpLakes project aims at providing operational products based on a combination of remote sensing and hydrodynamic models. ALPLAKES is a continuation of the CORESIM (ESA SEOM S2-4Sci Land and Water) project based on the recommendations [...] | EAWAG (CH) | Applications | Alps, hydrology science cluster, lakes, Sentinel-2, water resources | The AlpLakes project aims at providing operational products based on a combination of remote sensing and hydrodynamic models. ALPLAKES is a continuation of the CORESIM (ESA SEOM S2-4Sci Land and Water) project based on the recommendations provided during the CORESIM roadmap. While many studies have focused on ecosystem variability over a latitudinal gradient (Woolway and Merchant, 2019), the response of the freshwater systems to climate changes over an altitudinal gradient is comparatively less understood. For this purpose, the project upscaled the web-based platform (see Meteolakes, http://meteolakes.ch/ as baseline) by integrating 11 lakes from ~60 m.a.s.l to 1800 m.a.s.l around the Alps with a 3D modelling approach. Sentinel-2 products are used to improve the quality of the hydrodynamic model by providing, in near real-time, information about light penetration. This parameter is essential for the distribution of the incoming solar radiation as it controls, together with the atmospheric forcing, the evolution of the lake’s thermal structure. Then, there will be an evaluation of the short time evolution of identified patterns from Sentinel-2 products by applying a particle-tracking technique. The final application will be openly available for in-depth analyses of specific events in a new web-based platform. |
| ALPS APPLICATIONS PRIORITIES | This project will implement a demonstrator of a Digital Twin for the Alps looking at Disaster Risk Management and Water Resources Management. It has mandated user organizations in France, Italy and Switzerland. | SENTINEL HUB VAS GMBH (AT) | Enterprise | Alps, regional initiatives, water resources | This project will implement a demonstrator of a Digital Twin for the Alps looking at Disaster Risk Management and Water Resources Management. It has mandated user organizations in France, Italy and Switzerland. |
| Alpsnow | The AlpSnow project will develop improved products for a number of snow parameters (area extent, albedo, grain size, depth, snow water equivalent, snow melt area and wetness). A dataset covering the entire Alps for 4 years will be produced, and [...] | ENVEO – ENVIRONMENTAL EARTH OBSERVATION GMBH (AT) | Regional Initiatives | Alps, hydrology science cluster, polar science cluster, science, snow and ice, water cycle and hydrology | The AlpSnow project will develop improved products for a number of snow parameters (area extent, albedo, grain size, depth, snow water equivalent, snow melt area and wetness). A dataset covering the entire Alps for 4 years will be produced, and its usefulness will be demonstrated through three science cases and three demonstration cases related to land surface modelling, hydrology, numerical weather forecasting and water management. Discover more projects, activities and resources on the Alps regional initiative (EO4ALPS) page. |
| AnREO: Retrieval of Total Ozone using OLCI-S-3 over Antarctica | The main part of the project is to develop a total ozone product for Ocean and Land Colour Instrument (OLCI) on board Sentinel 3 A,B. The product will be derived using the Sentinel-3A, B OLCI Level 1 Full Resolution data. The cloud mask, snow [...] | VITROCISET BELGIUM SPRL (BE) | Science | atmosphere science cluster, atmospheric chemistry, OLCI, permanently open call, science, Sentinel-3 | The main part of the project is to develop a total ozone product for Ocean and Land Colour Instrument (OLCI) on board Sentinel 3 A,B. The product will be derived using the Sentinel-3A, B OLCI Level 1 Full Resolution data. The cloud mask, snow mask, and atmospheric correction procedures will be also developed. OLCI measurements make it possible to understand the intra-pixel variability of the total ozone and observe rapid changes on the total ozone with a high spatial detail. The accuracy of the retrievals will be assessed using ground and collocated satellite (e.g., OMI) measurements of total ozone. |
| APPLICABILITY OF SATELLITE AND DRONES EO DATA FOR LANDFILLS DETECTION AND MONITORING | SAT+Dron4Landfills is a project which aims to use EO data for effective and timely detection and monitoring of landfills. As a major innovation, two main types of EO data are considered under the project: from existing satellite systems, and [...] | FUNDACIÓN ANDALUZA PARA EL DESARROL (ES) | Enterprise | land, platforms | SAT+Dron4Landfills is a project which aims to use EO data for effective and timely detection and monitoring of landfills. As a major innovation, two main types of EO data are considered under the project: from existing satellite systems, and from in-situ drone campaigns. EO satellite data will be used to provide relevant information to detect illegal landfills, and also to allow macro-scale monitoring capacities. Data from ad-hoc drone campaigns willprovide closer-to-the-ground, more frequent and cloud coverage independency inputs. The development of a data processing platform is proposed to analyze both sources of data, using advanced AI techniques. Moreover, a User Committee has ben created to raise awareness in the community of waste management users of the capacities that EO could bring for the efficient management of landfills.The project is envisaged as a proof of concept for the demonstration of the proposed solution, with field tests in Torija landfill in Guadalajara, Spain. The project started in October 2022 with the characterization of landfills in order to select the key parameters that can be extracted for their efficient detection and monitoring, and the initial activities for identifying available EO satellite resources and the definition of the drone campaigns to carry out. |
| Arctic + Salinity | Sea Surface Salinity (SSS) is a key indicator of the freshwater fluxes and an important variable to understand the changes the Arctic is facing. However, salinity in-situ measurements are very sparse in the Arctic region. For this reason, remote [...] | ARGANS LIMITED (GB) | Science | ocean science cluster, oceans, polar science cluster, science | Sea Surface Salinity (SSS) is a key indicator of the freshwater fluxes and an important variable to understand the changes the Arctic is facing. However, salinity in-situ measurements are very sparse in the Arctic region. For this reason, remote sensing salinity measurements (currently provided by L-band radiometry satellites, SMOS and SMAP) are of special relevance for this region. The retrieval of SSS in the Arctic represents a challenge, because brightness temperatures measured by L-band satellites are less sensitive to salinity in cold waters. An additional drawback consists in the presence of sea ice, that contaminates the brightness temperature and must be adequately processed. The ESA Arctic+ Salinity project (Dec 2018 – June 2020) will contribute to reduce the knowledge gap in the characterization of the freshwater flux changes in the Arctic region. The objectives of this project are the following: 1. Develop a new algorithm and novel approaches with the aim of producing the best quality validated SMOS SSS product in the Arctic region with its corresponding accuracy. Additionally, SMOS and SMAP data will be combined with the aim to improve the radiometric accuracy and the characterization of the product biases and stability. 2. Generate a long-term salinity dataset from 2011 up to date to be publicly offered to the scientific community. The products will be daily distributed with a temporal resolution of 9 days and a spatial resolution of 25Km (EASE Grid 2.0). 3. Assess the relation between the dynamics of SMOS salinity with respect to land freshwater fluxes (Greenland and glacier flows) and ocean freshwater fluxes (rivers and E-P balance) using model outputs. This has the objective to quantify the freshwater fluxes through SSS products. 4. Assess the impact of the new SSS satellite data in a data assimilation system (the TOPAZ4 system, both in forecast and reanalysis mode) with the idea that, if an improvement is demonstrated, the assimilation of SMOS & SMAP products in TOPAZ will be part of the new Arctic reanalysis and forecast products on the CMEMS portal. 5. Define a roadmap describing the future work to better characterize the freshwater fluxes for the Arctic regions. The output of this project will be of great benefit for the on-going ESA Sea Surface Salinity Climate Change Initiative (CCI) project, which started in February 2018. The outputs of the project will be: 1. The distribution to the scientific community of the best-up-to-date sea surface salinity maps from SMOS and from the combination of SMOS and SMAP with their corresponding uncertainties. 2. Explore the feasibility and utility of assimilating the surface salinity maps product in the TOPAZ4 model. The potential problem the project face is the sparse in-situ data availability in the area which is needed for a complete validation assessment. Other potential problems are the sea ice edge that has a direct effect in the brightness temperature and the RFI contamination. But several solutions have already been identified. |
| Arctic Crowdsourcing | The Arctic Crowdsourcing project has been successfully completed. The objective was to create an enhanced Earth Observations (EO) services for Arctic applications planned for C-CORE’s Coresight Platform to include community/crowd sourced very [...] | C-CORE (CA) | Digital Platform Services | permanently open call, platforms | The Arctic Crowdsourcing project has been successfully completed. The objective was to create an enhanced Earth Observations (EO) services for Arctic applications planned for C-CORE’s Coresight Platform to include community/crowd sourced very high-resolution drone data, ESA Sentinel mission data and other forms of field data that support Arctic stakeholder needs. The Arctic Crowdsourcing project included: 1) Engagement of Arctic communities to develop skills around drone operations, as well as GIS, and EO satellite knowledge. The community engagement also investigated remote sensing based services for that could directly benefit communities. 2) The development Arctic Crowdsourcing Service for collecting community-sourced knowledge, targeting community sourced Drone Data, and geotagged video and image data. 3) The prototype development of enhanced EO based services and incorporate other community sourced data or new products created via the Polar TEP. The developed products were on display and ready for live demos at ESA’s Living Planet Symposium May 2019 in the C-CORE booth, and available publically to all, after the symposium. The project involved direct engagement with community members via several face-to-face meetings with communities, supporting the establishment of training programs and the hiring of local commercial drone operators to collect test scenario data. Initial community engagement highlighted two obstacles to support crowdsourcing of drone imagery which were the lack of in region drone operation skills, and lack of high bandwidth connectivity to transfer the high number of large bandwidth files created by drones and their higher resolution sensors. While this project has completed, the opportunity of developing Arctic crowdsourced drone data will continue to be developed as numbers of drone operators in the Arctic increase, and further engagement and feedback are received from Arctic communities. |
| ARCTIC+ SEA ICE MASS | The Arctic is a complex region encompassing different physical and biogeochemical processes and interactions among several components of the Earth system (e.g., sea ice, ocean, glaciers, ice caps, the Greenland Ice Sheet, snow, lakes and river [...] | ISARDSAT SP. Z O.O. (PL) | Science | science, snow and ice | The Arctic is a complex region encompassing different physical and biogeochemical processes and interactions among several components of the Earth system (e.g., sea ice, ocean, glaciers, ice caps, the Greenland Ice Sheet, snow, lakes and river ice, permafrost, vegetation, complex interactions with the atmosphere, people, etc.). Changes in the Arctic have a strong impact on the Earth’s climatesystem , the global energy budget, the ocean circulation, the water cycle, gas exchanges, sea level, and biodiversity. Considering that all of Earth’s inter-connected components respond to changes in temperature, the Arctic is a sensitive indicator of climate variability and change.Despite considerable research progress in understanding the Arctic region over the last decade, many gaps remainin observational capabilities and scientific knowledge. These gaps limit present ability to understand and interpret on-going processes, prediction capabilities and forecasting in the Arctic region, thereby hampering evidence-based decision making. Addressing these gaps represents a key priority in order to establish a solid scientific basis for the development of future information servicesfor the Arctic.In this context, the 20th January 2015, ESA and the Cryosphere project of the World Climate Research programme (CliC-WCRP) organised a scientific consultation meeting in Tromso with the main objective of gathering recommendations from the scientificcommunity on the most pressing priorities for Arctic research, where EO may contribute in the coming decade. The workshop resulted ina report listing a number of different priority areas that will contribute to establish an strong focus on Arctic research in thenext components of ESA EO programmes for the period 2017-2021.In order to put words in actions, this ITT aims at addressing someofthepriorities identified in Tromso as an starting point for future activities. In particular, with this ITT, a number of priority areas will be addressed at feasibility and demonstration level with the ultimate target of establishing a solid scientific basis to initiate larger research actions from 2017.To this end, with this ITT ESA plans to place 4 parallel contracts adressing different priority areas as identified by the scientific community.In this context, Arctic+ aims at advancing towards the achievement ofsome of the most pressing priorities in Arctic science, where EO may contribute. In particular, the main overarching project objectiveis threefold: 1) Supporting the development of novel products and enhanced data sets responding to the needs of the Arctic science community;2) Fostering new scientific results addressing the main priority areas of Arctic research;3) Preparing a solid scientific basis for larger activities addressing the priorities of the Arctic science community; This shall involve the collaborationamong the different scientific communities involved in Arctic process studies, modellers and EO experts;In the medium and long-term the objectives of the project include:• To foster the scientific exploitation of EO-based geo-information products (maximising the use of ESA data) to respond directly to the needs of the Arctic scientific community in the context of selected thematic areas;• To support existing international efforts to improve the observation, understanding and prediction of ocean-sea-ice-atmosphere processes at different spatial and time scales demonstrating the capability of EO and ESA data to respond to the needs of the Arctic research community;• To foster the integration of EO data, in-situ observations and models in support of Arctic science;• To develop aScientific Roadmap as a basis for further ESA activities in support of the Arctic research. |
| ARCTIC+ SNOW ON SEA ICE | The Arctic is a complex region encompassing different physical and biogeochemical processes and interactions among several components of the Earth system (e.g., sea ice, ocean, glaciers, ice caps, the Greenland Ice Sheet, snow, lakes and river [...] | ISARDSAT SP. Z O.O. (PL) | Science | science, snow and ice | The Arctic is a complex region encompassing different physical and biogeochemical processes and interactions among several components of the Earth system (e.g., sea ice, ocean, glaciers, ice caps, the Greenland Ice Sheet, snow, lakes and river ice, permafrost, vegetation, complex interactions with the atmosphere, people, etc.). Changes in the Arctic have a strong impact on the Earth’s climatesystem , the global energy budget, the ocean circulation, the water cycle, gas exchanges, sea level, and biodiversity. Considering that all of Earth’s inter-connected components respond to changes in temperature, the Arctic is a sensitive indicator of climate variability and change.Despite considerable research progress in understanding the Arctic region over the last decade, many gaps remainin observational capabilities and scientific knowledge. These gaps limit present ability to understand and interpret on-going processes, prediction capabilities and forecasting in the Arctic region, thereby hampering evidence-based decision making. Addressing these gaps represents a key priority in order to establish a solid scientific basis for the development of future information servicesfor the Arctic.In this context, the 20th January 2015, ESA and the Cryosphere project of the World Climate Research programme (CliC-WCRP) organised a scientific consultation meeting in Tromso with the main objective of gathering recommendations from the scientificcommunity on the most pressing priorities for Arctic research, where EO may contribute in the coming decade. The workshop resulted ina report listing a number of different priority areas that will contribute to establish an strong focus on Arctic research in thenext components of ESA EO programmes for the period 2017-2021.In order to put words in actions, this ITT aims at addressing someofthepriorities identified in Tromso as an starting point for future activities. In particular, with this ITT, a number of priority areas will be addressed at feasibility and demonstration level with the ultimate target of establishing a solid scientific basis to initiate larger research actions from 2017.To this end, with this ITT ESA plans to place 4 parallel contracts adressing different priority areas as identified by the scientific community.In this context, Arctic+ aims at advancing towards the achievement ofsome of the most pressing priorities in Arctic science, where EO may contribute. In particular, the main overarching project objectiveis threefold: 1) Supporting the development of novel products and enhanced data sets responding to the needs of the Arctic science community;2) Fostering new scientific results addressing the main priority areas of Arctic research;3) Preparing a solid scientific basis for larger activities addressing the priorities of the Arctic science community; This shall involve the collaborationamong the different scientific communities involved in Arctic process studies, modellers and EO experts;In the medium and long-term the objectives of the project include:• To foster the scientific exploitation of EO-based geo-information products (maximising the use of ESA data) to respond directly to the needs of the Arctic scientific community in the context of selected thematic areas;• To support existing international efforts to improve the observation, understanding and prediction of ocean-sea-ice-atmosphere processes at different spatial and time scales demonstrating the capability of EO and ESA data to respond to the needs of the Arctic research community;• To foster the integration of EO data, in-situ observations and models in support of Arctic science;• To develop aScientific Roadmap as a basis for further ESA activities in support of the Arctic research. |
| ARCTIC+ THEME 3 – FRESH WATER FLUXES (ArcFlux) | The Arctic is a complex region encompassing different physical and biogeochemical processes and interactions among several components of the Earth system (e.g., sea ice, ocean, glaciers, ice caps, the Greenland Ice Sheet, snow, lakes and river [...] | Technical University of Denmark (DK) | Science | science, water cycle and hydrology, water resources | The Arctic is a complex region encompassing different physical and biogeochemical processes and interactions among several components of the Earth system (e.g., sea ice, ocean, glaciers, ice caps, the Greenland Ice Sheet, snow, lakes and river ice, permafrost, vegetation, complex interactions with the atmosphere, people, etc.). Changes in the Arctic have a strong impact on the Earth’s climatesystem , the global energy budget, the ocean circulation, the water cycle, gas exchanges, sea level, and biodiversity. Considering that all of Earth’s inter-connected components respond to changes in temperature, the Arctic is a sensitive indicator of climate variability and change.Despite considerable research progress in understanding the Arctic region over the last decade, many gaps remainin observational capabilities and scientific knowledge. These gaps limit present ability to understand and interpret on-going processes, prediction capabilities and forecasting in the Arctic region, thereby hampering evidence-based decision making. Addressing these gaps represents a key priority in order to establish a solid scientific basis for the development of future information servicesfor the Arctic.In this context, the 20th January 2015, ESA and the Cryosphere project of the World Climate Research programme (CliC-WCRP) organised a scientific consultation meeting in Tromso with the main objective of gathering recommendations from the scientificcommunity on the most pressing priorities for Arctic research, where EO may contribute in the coming decade. The workshop resulted ina report listing a number of different priority areas that will contribute to establish an strong focus on Arctic research in thenext components of ESA EO programmes for the period 2017-2021.In order to put words in actions, this ITT aims at addressing someofthepriorities identified in Tromso as an starting point for future activities. In particular, with this ITT, a number of priority areas will be addressed at feasibility and demonstration level with the ultimate target of establishing a solid scientific basis to initiate larger research actions from 2017.To this end, with this ITT ESA plans to place 4 parallel contracts adressing different priority areas as identified by the scientific community.In this context, Arctic+ aims at advancing towards the achievement ofsome of the most pressing priorities in Arctic science, where EO may contribute. In particular, the main overarching project objectiveis threefold: 1) Supporting the development of novel products and enhanced data sets responding to the needs of the Arctic science community;2) Fostering new scientific results addressing the main priority areas of Arctic research;3) Preparing a solid scientific basis for larger activities addressing the priorities of the Arctic science community; This shall involve the collaborationamong the different scientific communities involved in Arctic process studies, modellers and EO experts;In the medium and long-term the objectives of the project include:• To foster the scientific exploitation of EO-based geo-information products (maximising the use of ESA data) to respond directly to the needs of the Arctic scientific community in the context of selected thematic areas;• To support existing international efforts to improve the observation, understanding and prediction of ocean-sea-ice-atmosphere processes at different spatial and time scales demonstrating the capability of EO and ESA data to respond to the needs of the Arctic research community;• To foster the integration of EO data, in-situ observations and models in support of Arctic science;• To develop aScientific Roadmap as a basis for further ESA activities in support of the Arctic research. |
| ArcticSummIT: Arctic Summer Ice Thickness | Living Planet Fellowship research project carried out by Jack Landy. Arctic-SummIT will deliver, for the first time, a sea ice thickness product during summer months from the ESA Cryosat-2 satellite. As the extent of Arctic sea ice has [...] | UNIVERSITY OF BRISTOL (GB) | Science | CryoSat, cryosphere, living planet fellowship, polar science cluster, science | Living Planet Fellowship research project carried out by Jack Landy. Arctic-SummIT will deliver, for the first time, a sea ice thickness product during summer months from the ESA Cryosat-2 satellite. As the extent of Arctic sea ice has declined at unprecedented speed over the past few decades, we have been able to view only limited snapshots of the ice cover’s thickness. Pan-Arctic observations of sea ice thickness have been obtained in recent years by satellite altimeters such as ICESat and Cryosat-2, but conventionally these data are only available during winter months. Our current understanding of basin-scale sea ice melting patterns during summer are limited to poorly-constrained ice-ocean model simulations, at a time when the ice cover is most dynamic, not to mention biological productivity and ice-ocean geochemical fluxes are most active. Moreover, advanced knowledge of ice conditions – thickness in particular – are critical for managing sustainable commercial enterprises, such as shipping and oil & gas extraction, in the northern polar seas. This project will develop a novel algorithm for obtaining sea ice thickness from satellite altimetry, even as the ice is melting. The conventional technique for separating sea ice from water (i.e. leads within the ice pack) relies on classifying altimeter waveforms through the shape of echoes, but breaks down when meltwater ponds forming at the ice surface appear the same as leads. However, pilot research alongside partners from the Canadian Ice Service (CIS) has demonstrated that other characteristics of the Cryosat-2 echoes, particularly the calibrated backscatter coefficient of the radar, can separate ice from ocean regardless of the surface melting state. Arctic-SummIT will develop this exciting discovery into a rigorous method for measuring sea ice thickness during summer months. By the end of the project, a unique, pan-Arctic sea ice thickness product will be produced for July-September over the full Cryosat-2 data record: 2011-2018+, filling the summer ‘gap’ we have presently. Exchange of sea ice between the central Arctic Ocean and, for instance, the Canadian Arctic Archipelago (CAA) or Fram Strait will then be determined from the product of ice volume from Cryosat-2, and high-resolution ice drift speed obtained from Synthetic Aperture Radar (SAR) imagery including the ESA Sentinel-1 constellation and the Canadian Space Agency’s (CSA) RADARSAT-2. Seasonal ice volume fluxes will be made available to the academic community, alongside the new summer sea ice thickness product, through an online portal hosted via ESA at the University of Bristol. |
| ARKTALAS HOAVVA PROJECT | The multi-disciplinary, long-term, satellite-based Earth Observations (EO) form a tremendous synergy of data and information products that should to be more systematically and consistently explored, from the short synoptic time scales to the [...] | NANSEN ENVIRONMENTAL AND REMOTE SENSING CENTER (NO) | Science | cryosphere, ocean science cluster, oceans, polar science cluster, science | The multi-disciplinary, long-term, satellite-based Earth Observations (EO) form a tremendous synergy of data and information products that should to be more systematically and consistently explored, from the short synoptic time scales to the longer decadal time scales. This lays the rationale for the ESA funded Arktalas Hoavva study project. A stepwise multi-modal analyses framework approach benefitting from native resolution satellite observations together with complementary in-situ data, model fields, analyses and visualization system and data assimilation tools will be applied. Following this approach, the overall goal is to remove knowledge gaps and advance the insight and quantitative understanding of sea ice, ocean and atmosphere interactive processes and their mutual feedback across a broad range of temporal and spatial scales. In turn, four major existing interlinked Arctic Scientific research Challenges (ASC) will be investigated, including: ASC-1: Characterize Arctic Amplification and its impact (ASC-1) Central elements (not exclusive) are: – reduction in sea ice extent and concentration; – changes in albedo; – changes in the radiation balance; – increased air temperature; – delayed onset of sea ice freezing; – early onset of sea ice melting; – increasing area of melt ponds and polynias; – increased lead fraction; – changes in snow cover and SWE; – changes in ocean-atmosphere momentum, heat exchange and gas exchanges; – reduction in fast ice area; – thinning of sea ice thickness; – changes in optical conditions in the upper ocean with influence on the biology and marine ecosystem; – more favourable conditions for sea ice drift; – more meltwater; – larger fetch; – enhanced wave-sea ice interaction; – more wave induced sea ice break-up; – modifications to atmospheric boundary layer and changes in weather pattern; – influence on Arctic vortex and hence teleconnection to mid-latitudes. ASC-2: Characterize the impact of more persistent and larger area open water on sea ice dynamics Building on ASC-1, this is associated with: – increasing momentum transfer to the upper ocean leading to more turbulent mixing and possibly entrainment of warm Atlantic Water below the halocline; – increasing Ekman effects; – changes in sea ice growth, salt rejection and halocline formation; – larger fetch and lower frequency waves penetrating further into the ice covered regions leading to more floe-break-up; – increasing lead fraction and more sea ice melting; – reduction in sea ice flow size, age, thicknesses and extent and subsequent change in sea ice mechanical behaviour; – possibly more abundance of internal waves and mesoscale and sub-mesoscale eddies generated in the open ocean with subsequent abilities to propagate into the ice covered regions leading to changes in sea ice deformation and dynamics. ASC-3: Understand, characterize and predict the impact of extreme event storms in sea-ice formation Growing areas of open water within the Arctic Ocean and the neighbouring seas will be more effectively exposed to extreme events. Cold air outbreak and polar lows, for instance, are known to have strong impact in the Marginal Ice Zone (MIZ), including; – enhanced momentum transfer and vertical mixing; – enhanced sea ice formation; – enhanced formation of unstable stratification in the atmospheric boundary layer; – more low cloud formations changing the radiation balance; – set up abnormal wave field to strengthen wave induced sea ice break-up; – abnormal impact on the pycnocline and subsequent entrainment of heat into the upper mixed. A central question is eventually whether the Arctic amplification will trigger increasing frequency of occurrences and strength of extremes. ASC-4: Understand, characterize and predict the Arctic ocean spin-up The ongoing Arctic amplification and subsequent changes, mutual interactions and feedback mechanisms are also expected to influence the basin scale atmospheric and ocean circulation within the Arctic Ocean. In particular, this will address: – freshwater distribution and transport; – importance of Ekman pumping; – changes in water mass properties; – changes in upper ocean stratification and mixing; – changes in sub-surface heat exchange; – possibly more abundance of mesoscale and sub-mesoscale eddies and internal waves generated in the open ocean with subsequent abilities to propagate into the sea ice covered regions. The Arktalas Hoavva project kicked-off 9 July 2019 and will be executed over a 24 months period through the following seven interconnected tasks with mutual input-output feeds as schematically illustrated in the figure below. One of the major outcomes of the project is six dedicated research papers emerging from Task 3 that are specifically addressing the Arctic Scientific Challenges. These papers will be published in peer review journals. Moreover, the project will develop a visualization portal in polar-stereographic configuration that will be connected to the Arktalas data archive and allow users to access and make use of the Arktalas satellite-based, in-situ and model-based dataset during the project. |
| Artificial Intelligence for SAR at High Resolution (AI4SAR HighRes) | AI4SAR is an attempt to harness AI techniques for high-resolution, high-fidelity SAR data, both in time and spatially. It aims to process rapid-revisit SAR data and develop modular applications for high-frequency monitoring of [...] | ICEYE OY (FI) | AI4EO | AI4EO, AI4Science, ecosystems/vegetation, forestry, SAR, terrestrial hydrosphere | AI4SAR is an attempt to harness AI techniques for high-resolution, high-fidelity SAR data, both in time and spatially. It aims to process rapid-revisit SAR data and develop modular applications for high-frequency monitoring of Earth. The inherent complexity of the backscattered SAR signal presents a daunting challenge to data scientists and machine learning (ML) engineers, thereby increasing the entry barrier and precluding the exploration of an incredibly rich data source. AI4SAR is a great opportunity to lower this entry barrier to SAR-based ML applications and unlock the full potential of persistent monitoring of our dynamic planet. AI4SAR addresses three critical needs of the data science and machine learning community: Ease of data handling: The inherent complexity of the SAR data is quick to overwhelm novice and experts. AI4SAR abstracts away the preprocessing burden of calibration, map projection, coregistration, and label transformation to enable the community users to handle the data in a way that makes sense to them. Persistent analysis of change: SAR is the only EO technology that can consistently and with high precision enable the quantification of change over time. High-temporal resolution is critical to the community users who need to enable informed decisions about the changing baseline and not be left stranded with time gaps. Unsanctioned deforestation can no longer be hidden in the rainy season. Assurance of clean, reliable data: SAR data has its share of peculiarities in the form of along-flight-direction (azimuth) and across-flight-direction (range) ambiguities. These artifacts question its efficacy in ML models that need massive volumes of reliable data for monitoring global changes, such as deforestation. AI4SAR leverages ML for automated identification and removal of these ambiguities so that the community users can trust the data that feeds their ML models. AI4SAR aims at building tools that simplify SAR for data scientists and ML engineers so that they can accelerate AI development for EO applications. To this end, the AI4SAR project team built the icecube toolkit that helps organize ICEYE SAR images and annotations for supervised ML applications. The Python library generates multidimensional SAR image and labels datacubes. The datacubes stack SAR time-series images in range and azimuth and can preserve the geospatial content, intensity, and complex SAR signal from the SAR images. You can use the datacubes with ICEYE Ground Range Detected (GRD) geotifs and Single Look Complex (SLC) .hdf5 product formats. With the icecube toolkit, the community can: Analyze time-series ICEYE SAR data Configure ICEYE’s time-series data for critical analysis and A/B testing Leverage the power of datacubes for accessing, sharing, and managing ICEYE data Additional resources: The icecube toolkit is available on https://github.com/iceye-ltd/icecube/ |
| Asian Development Bank Resident Support | Through this activity ESA is deploying an EO information expert (Technical Secondment) to the headquarters of the Asian Development Bank (ADB) in Manila, Philippines, during 2017–2021. This activity is implemented in conjunction with ESA's EO4SD [...] | Collaborative Space (IE) | Sustainable Development | sustainable development | Through this activity ESA is deploying an EO information expert (Technical Secondment) to the headquarters of the Asian Development Bank (ADB) in Manila, Philippines, during 2017–2021. This activity is implemented in conjunction with ESA’s EO4SD initiative, and to further strengthen the collaboration with ADB (in particular, as an integral part of the ESA–ADB Memorandum of Intent). The primary objective of the secondment is to promote increased awareness use of EO information products and services within ADB operational activities. Europe has a world-leading EO capability, therefore priority is given to promoting European EO assets and skills. The longer-term objective is to achieve widespread acceptance and sustainability of EO-based products and services within international development operations. |
| Assesscarbon | The Assesscarbon project (Feb 2020 – Feb 2021) developed and demonstrated at a pre-operational level an approach for large area forest biomass and carbon modelling, combining ground reference data, Sentinel-2 imagery and primary production [...] | VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD (FI) | Applications | applications, Biomass, carbon cycle, forestry, permanently open call, Sentinel-2 | The Assesscarbon project (Feb 2020 – Feb 2021) developed and demonstrated at a pre-operational level an approach for large area forest biomass and carbon modelling, combining ground reference data, Sentinel-2 imagery and primary production modelling. The overall goal of the project was to develop a foundation for a novel approach to derive large area biomass and carbon pool and flux estimates and forecasting in a scalable fashion on an online platform. The project was coordinated by VTT Technical Research Centre of Finland and funded by ESA under the EO Science for Society Permanently Open Call funding mechanism. The main input data for the project were Copernicus Sentinel-2 satellite data, forest plot measurements and climatic datasets. The Sentinel-2 mosaics was created by Terramonitor (Satellio Oy) using their novel image mosaicking approach. This image composite was used together with field sample plots provided by the Finnish Forest Centre to create forest variable estimation models. Finally, dynamic forest primary production variables were modelled using the forest structure variables and climatic data. The forest structural variable models were based on the Probability software package developed by VTT. It contains three different parts, which together form a comprehensive package of classification/estimation tools combining field data with satellite imagery. The primary production modelling is based on the PREBAS models developed by the University of Helsinki. The models were further developed utilizing multi-temporal observations. The practical processing of the primary production estimates for the area of interest was carried out by Simosol Oy. The demonstration was conducted on the Forestry TEP. Forest structural variable and primary production information were produced for a test area covering the entire Finland and the Russian boreal forests until the Ural mountains. All components of the project were implemented in a manner that enables scalable execution of the models in Forestry TEP environment. The chosen approach utilized the Sentinel-2 tiling structure as the building blocks. All software components were redeveloped to enable processing of a given number of Sentinel-2 tiles in a coordinated manner, in order to produce consistent results over large interest areas. |
| ASSESSING CRYOSPHERE-BIOSPHERE LINKAGES WITH EARTH OBSERVATIONS IN NORTHERN HIGH LATITUDES (CRYOBIOLINKS) | Climate warming in the northern high latitudes is twice as strong as the global average. Increasing surface temperatures drive significant changes in the cryosphere, reducing the snow mass and extent, seasonal frost and permafrost. Changes in [...] | FINNISH ENVIRONMENT INSTITUTE (SYKE) (FI) | Science | biosphere, climate, cryosphere, living planet fellowship, Sentinel-3, SMOS, snow and ice, sustainable development | Climate warming in the northern high latitudes is twice as strong as the global average. Increasing surface temperatures drive significant changes in the cryosphere, reducing the snow mass and extent, seasonal frost and permafrost. Changes in the cryosphere are interconnected with changes in the biosphere, e.g. carbon uptake and release by vegetation and soil. These cryosphere-biosphere linkages and feedbacks may have important implications for the warming processes in the northern high latitudes and failure to account for them in Earth system models may cause significant uncertainties in climate projections. CryoBioLinks will investigate linkages between cryosphere variables and the carbon uptake of vegetation and their changes by using satellite observations on snow cover, soil freeze, land surface temperature, vegetation indices and solar-induced chlorophyll fluorescence (SIF), together with in situ CO2 flux measurements. For that, the ESA Climate Change Initiative (CCI) snow cover fraction, SMOS soil freeze and thaw time series and Sentinel-3 land surface temperature will be exploited and combined. SMOS soil freeze and thaw state will be fused with a novel Sentinel-1 soil freeze and thaw product to improve spatial resolution and reduce scaling errors when compared to CO2 flux sites. The correspondence of advanced vegetation indices from Sentinel-3 (chlorophyll/ carotenoid index and the plant phenological index) and GOSAT SIF and their relationship to gross primary production will be analysed. Satellite proxies describing seasonal dynamics of vegetation photosynthesis and gross primary production will be developed and their spatial distribution will be mapped in the northern high latitudes. The processing of vegetation indices and derived metrics from Sentinel-3 will be implemented to a cloud processing platform. The project will produce and publish multi-annual maps of proxy indicators covering the northern high latitudes (>60°N). Interconnections between the cryosphere variables and carbon fluxes will be studied for different ecosystem types in Finland and underlying mechanisms will be explored with the new terrestrial ecosystem model QUINCY. CryoBioLinks will advance the knowledge and produce new data sets on cryosphere-biosphere interactions, thus contributing to a grand challenge in climate science. The expected indicators can be utilized for the evaluation of cryosphere and biosphere processes in Earth system models. Developed methods are expected to provide means for the monitoring of changes in the cryosphere and vegetation carbon uptake, thus raising awareness and providing information for the preparation of climate adaptation and mitigation plans and herewith contributing to the Sustainable Development Goal 13: Climate action. |
| Assessing unpaved road condition from optical satellite imagery using machine learning in th e Global South | Rural roads in Africa provide mobility to the poorest in society, enabling them to access economic opportunities and essential services such as health and education. A study on rural access estimated that over a billion people living in rural [...] | TRL LIMITED (GB) | Applications | africa, climate, permanently open call, sustainable development | Rural roads in Africa provide mobility to the poorest in society, enabling them to access economic opportunities and essential services such as health and education. A study on rural access estimated that over a billion people living in rural areas do not have reasonable access to an all-season road (World Bank, 2016). Latest data (World Bank Data Catalogue, 2019) indicates that 59% of Africans live in rural areas, with the difference in livelihoods between rural and urban being most pronounced (OECD, 2019). At least 80% of goods and 90% of passengers are transported by road in Africa, and 53% of these roads are unpaved (African Development Bank, 2014). Rural roads can be a great enabler of economic and social transformation and are key to a number of Sustainable Development Goals (SDGs), especially SDG 9.1. (TRL, 2019). Climate change is affecting the resilience of rural roads to resist more frequent and extreme weather events. Low- and Middle-Income Countries (LMICs) are struggling to keep pace with the revised requirements for resilience and in many cases do not have the basic information on their road networks to allow them to make essential decisions. The aim of this research is to develop an Earth Observation (EO) based system to rapidly assess the condition of unpaved road networks in LMICs and provide an overview of accessibility for improving road asset management. This minimises the time-consuming and logistically difficult process of gathering road condition information locally, whilst enabling efficient interventions where and when needed, hence optimising the use of resources through more efficient maintenance planning and prioritisation. To be attractive to LMIC road authorities the system must be cost-effective. Previous research focused on using very high-resolution satellite imagery to identify road condition on a Good/Fair/Poor/Bad basis by using Machine Learning classifiers and Convolutional Neural Networks. To minimise imagery costs this research is exploring the possibility of using lower resolution imagery to replicate the results, which would save up to 70% of the imagery costs. The project foresees a ground truthing process with local road managers partners, and will be first developed in two trial countries, Malawi and Madagascar, which are two of the countries with the least developed roads. A cost-benefit analysis will be also carried out, ensuring to determine the most appropriate level of accuracy against cost, to the level of accuracy required by road asset managers in LMICs. The project will produce an open GIS plug-in compatible with Road Asset Management Systems (RAMS). Two local key partners support the activity, specifically the Roads Authority in Malawi, and the NGO Lalana in Madagascar whose mission is to promote sustainable development process focusing on road infrastructure and transportation. |
| Atlantic cities: smart, sustainable and secure ports and protecting the ocean | The project aims at developing and delivering to the end user communities a number of customized EO-based information services to support decision making processes in the Atlantic Region: Climate Resilience Atlantic Cities and Ports [...] | DEIMOS SPACE UK LTD (GB) | Regional Initiatives | Atlantic, oceans, ports, regional initiatives, sustainable development, urban | The project aims at developing and delivering to the end user communities a number of customized EO-based information services to support decision making processes in the Atlantic Region: Climate Resilience Atlantic Cities and Ports Protecting the Ocean The Climate Resilience Service will be focused on providing information and know-how for assessing the risks and potential socio-economic impacts of coastal processes such as erosion and flooding, to: Critical infrastructures Business activities Coastal protection elements The main service users are: environmental agencies municipalities coastal business activities The Cities and Ports Service will focus on addressing the needs identified by coastal cities with ports, supporting the social cohesion and inclusiveness while ensuring the harmonious co-existence of many economic activities and the well-being of its inhabitants and tourists. This service therefore aims to support ports, cities and related entities in: Assessing the activities in and around ports Monitoring of maritime transport Detecting port-related pollution Identifying security/safety issues for assets. The Protecting the Ocean Service will focus on: detecting emerging pollutants such as marine litter monitoring the environmental status of ocean areas, including MPAs and other marine ecosystem relevant areas. This service addresses users from national and international authorities and other entities responsible for reporting marine status and indicators. |
| Atlantic Meridional Transect Ocean Flux from satellite campaign (AMT4OceanSatFlux) | This project estimates of the air-sea flux of CO2 calculated from a suite of satellite products over a range of Atlantic Ocean provinces. It deploys state-of-the-art eddy co-variance methods to provide independent verification of satellite [...] | Plymouth Marine Laboratory (GB) | Science | ocean science cluster, oceans, science | This project estimates of the air-sea flux of CO2 calculated from a suite of satellite products over a range of Atlantic Ocean provinces. It deploys state-of-the-art eddy co-variance methods to provide independent verification of satellite estimates of CO2 gas exchange over the Atlantic Ocean. The project provides Fiducial Reference Measurements from the AMT28 (from 23rd September to 29th October 2018) and AMT 29 (from 13th October to 25th November 2019) field campaigns to enable independent verification and validation of the satellite CO2 air-sea flux estimates both at point scales and on scales that relate to satellite data over a range of oceanographic conditions. Global algorithms that are being used to study ocean acidification from using satellite data are also being evaluated and refined within the project, using high spatio-temporal resolution underway measurements made on AMT28 and AMT29 field campaigns. |
| Atlantic Regional Initiative – Applications: Offshore Wind Energy | Services based on Earth Observation (EO) can provide valuable information during the design stage by providing a long time series of wind data that allows a better assessment and characterization of the wind resource energy production potential [...] | Deimos Engenharia (PT) | Regional Initiatives | Atlantic, energy and natural resources, oceans, regional initiatives, renewable energy | Services based on Earth Observation (EO) can provide valuable information during the design stage by providing a long time series of wind data that allows a better assessment and characterization of the wind resource energy production potential of different possible wind farm (WF) sites, helping to select the most advantageous ones. These typical site wind characteristics can also assist in the determination of the optimal location of each individual wind turbine (WT) inside the specified site boundaries, minimizing combined WT wake influence and therefore minimizing energy production losses. Once the WF is operational, the EO based services can help establish optimal site maintenance weather windows and help foresee or determine/monitor possible rain erosion effects on the WT blades. Long time series of wind and wave data will help determine possible overall weather windows for those operations, while short term weather forecast can provide valuable information to guide the planned maintenance activities (e.g. adjust time window for the activity based on weather forecast inputs). This 2-year project focuses on the development of an integrated application covering: A planning dashboard for wind farm design and operations, including weather windows for offshore operations planning. The dashboard aims to provide a single access point to the different EO services to be developed with advanced data visualisation and download capabilities so that the user is able to trigger service runs, access easily all service outputs, compare different site locations, configurations and maintenance scenarios, and get support from a team of specialised personnel for each one of the services. The EO-based services will cover different activity areas of wind farm design and operations from wind resource and wake effect assessment to the definition of maintenance operations weather windows, provided by dedicated expert teams coming from different partners. The users will interact with those EO experts to better understand the capabilities, optimal conditions of use and possible limitations of the different presented services, therefore easing their learning curve on the usage and uptake on these products. Hopefully this process, that will be upscaled to other users in the final workshop of the project, will improve significantly the uptake of these types of products by the wind energy sector. The dashboard should integrate these new EO based services with wind industry sector standard metrics for energy production, operational costs and total cost of energy to provide more recognisable and actionable information to the end users and therefore ease the uptake of these types of services by these non-EO expert user communities. Winds for resource assessment. The main focus will be on making EO data and derived products easily accessible for end users and on the development of new applications, which can integrate the EO data seamlessly into the applications already in use by the wind energy community and in particular the wind energy industry. The aim is to fully integrate satellite wind based products with well established industry standard wind farm planning and operations software solutions (SOWFA) and indicators (AEP and LCOE), addressing the full information value chain to provide meaningful and familiar information to infrastructure managers and other interested stakeholders. Assessment of wind turbine wake effects. The work will provide access to the higher resolution SAR based EO datasets, produced by DTU, to downstream industry standard applications developed by Wavec. Those applications will use those wind satellite products as ground truth to run the required simulations to assess and minimise wake effects. As in the previous service, standard energy production and cost indicators such as AEP and LCOE will be estimated in these simulations to provide actionable and familiar information to the different stakeholders. Assessment of rain erosion of wind turbine blades. The work will use rain data from the GPM mission to characterise rain events, which, combined with wind data from satellite EO, will produce novel rain-wind data series for selected sites with operating wind farms. The work will be the first of its kind, thus in a prototype level data for initial evaluation by end users, namely, wind farm owners, wind farm operators and wind farm planners. The main partner to demonstrate the services will be EDP, through the Windfloat Atlantic wind farm project installed 20 km off the Portuguese coast at Viana do Castelo. During the user engagement the consortium team will be in contact with a series of stakeholders working in the Atlantic Region to help consolidate the technical requirements. As a result, additional service exercises for different users might be prepared. This activity corresponds to Theme 2 of the original Invitation to Tender. |
| ATMOSPHERE VIRTUAL LAB | The Atmosphere Virtual Lab is based on three main pillars. It adopts the concept of Exploitation Platforms and Cloud Based services. There is a strong focus on making sure that users can work with the vast amounts of satellite data without [...] | Science [&] Technology Netherlands (NL) | Science | atmosphere, atmosphere science cluster, science | The Atmosphere Virtual Lab is based on three main pillars. It adopts the concept of Exploitation Platforms and Cloud Based services. There is a strong focus on making sure that users can work with the vast amounts of satellite data without having to download all data locally. Providing analysis environments inside cloud-based environments close to the data is an essential part in making this work. The project will further develop tools that have been historically developed for users to handle and process atmospheric data (cf. https://atmospherictoolbox.org/). Use cases of a wide selection of atmospheric science scenarios will demonstrate the capability of the Atmosphere Virtual Lab and allow users to explore datasets in an interactive manner. |
| Automatic Looting Classification From Earth Observation Activity – ALCEO | Illegal excavation of archaeological sites aimed at collecting historical material culture (‘looting’) to introduce it in the illicit market of antiquities is a pressing problem on a global scale. Under favourable circumstances, looting can be [...] | ISTITUTO ITALIANO DI TECNOLOGIA (IT) | Enterprise | AI4EO, artificial intelligence, permanently open call | Illegal excavation of archaeological sites aimed at collecting historical material culture (‘looting’) to introduce it in the illicit market of antiquities is a pressing problem on a global scale. Under favourable circumstances, looting can be exposed on Earth Observation (EO) data by detecting changes that have occurred between two or more consecutive EO images of a time-series (fig 1.). The main goal of ALCEO (Automatic Looting Classification from Earth Observation) project is to develop Artificial Intelligence (AI) methods for the automatic identification and classification of Cultural Heritage looted sites on EO multi-temporal series. ALCEO aims to set a benchmark in the use of remote sensing for the identification of looting activities as: i) it will develop a novel and efficient semi-supervised change detection technique for identifying looting activities relying only on small number of labelled data ii) it will produce the first large EO training dataset of looted sites incorporating information provided by cultural heritage and Law Enforcement Agencies’ (LEA) experts; iii) it will develop new image restoration techniques to enhance the quality of EO images and make them more appropriate for looting detection tasks. The proposed methodology for detection and tracking of looting activities will have a major impact on the protection of endangered cultural heritage sites by strengthening the ability of Law Enforcement Agencies to promptly react to ongoing illicit activities or acquire criminal conduct patterns to be used for behavioural profiling and further investigations. |
| BALTIC+ Geodetic SAR for Baltic Height System Unification (SAR-HSU) | Height systems and related sea level observations are based on a number of measurement systems, which all have their own characteristics and deliver different type of observations. Traditionally, sea level is observed at tide gauge stations, [...] | TECHNICAL UNIVERSITY OF MUNICH (DE) | Science | Baltic, GOCE, SAR, science | Height systems and related sea level observations are based on a number of measurement systems, which all have their own characteristics and deliver different type of observations. Traditionally, sea level is observed at tide gauge stations, which usually also serve as height reference stations for national levelling networks and therefore define a height system of a country. Thus sea level research across countries is closely linked to height system unification and needs to be regarded jointly. In order to analyse all observations they need to be available in a common reference frame. Within this project three major objectives are addressed. Connection of tide gauge markers with the GNSS network geometrically by the geodetic SAR technique in order to determine the relative vertical motion and to correct the tide gauge readings. Determine a GOCE based high resolution geoid at tide gauge stations in order to deliver absolute heights of tide gauges with respect to a global equipotential surface as reference. Joint analysis of geometrical and physical reference frames to make them compatible, and to determine corrections to be applied for combined analysis of geometric and physical heights. These objectives are addressed by the project team with complementary expertise. The Baltic Sea serves as test area with very good geodetic infrastructure in order to identify the capabilities of the geodetic SAR technique for height system unification and determination of the absolute sea level at tide gauges. |
| BALTIC+ Salinity Dynamics | This project aims to study the potential benefit of incorporating satellite-derived Sea Surface Salinity (SSS) measurements into oceanographic and environmental applications within the Baltic Sea. For such purpose, a team led by ARGANS Ltd (UK) [...] | ARGANS FRANCE (FR) | Science | Baltic, ocean science cluster, science | This project aims to study the potential benefit of incorporating satellite-derived Sea Surface Salinity (SSS) measurements into oceanographic and environmental applications within the Baltic Sea. For such purpose, a team led by ARGANS Ltd (UK) with participation of Barcelona Expert Centre (BEC / ICM-CSIC, Spain) and the Finnish Meteorological Institute (FMI, Finland) will develop an innovative SSS product from the measurements obtained by the Earth Explorer SMOS. It incorporates advanced techniques for noise and bias correction to deal with the specific difficulties that the retrieval of salinity has in the region: land/sea contamination, sea/ice contamination, manmade radio-frequency interferences, and limitations in the current dielectric constant. The project will generate data by modifying substantially the existing production chain from L0 data to L4 maps, aiming to obtain meaningful information for applications. The characteristics of the final products will be enhanced both spatially and temporally thanks to data fusion, in order to meet the end-user requirements. SSS accuracy will be also improved to meet the needs of the scientific community operating in this basin. In the first half of the project, the focus will be in improving the brightness temperatures and adequate the image reconstruction process specifically for the Baltic Sea. In the second half of the project, the emphasis will be in the removal of remaining biases and generation of the fused L4 products, as well as assessing the performance and impact it has in the various case studies. Specific attention will be drawn to investigate the added-value of this new product to address the scientific challenges associated to salinity, as identified by Baltic Earth community: salinity annual trends and budgets; insights of the coupling mechanisms involved in the interfaces atmosphere-ice-sea; climatological projections. In addition, it is expected to estimate how other types of studies would benefit of incorporating SSS, like regional biochemical models, or any other in which frontal areas identification could be of relevance. For instance, river run-offs, sea ice formation/melting and, marginally, North Sea water intrusions. The project benefits of the existence of a long time series of observations provided by SMOS, which allows the team to explore longer time scales. The expected higher time and spatial coverage will be key factors in the outcome of this project, in a region in which in situ observations of salinity are scarce or concentrated in the coastal areas. It is expected that the results of this activity will lead towards an increase in the presence of SSS data. |
| BALTIC+ Sea-Land biogeochemical linkages (SeaLaBio) | The overall goal of the ESA funded project Baltic+ SeaLaBio (Sea-Land Biogeochemical linkages) running from Dec 2018 to May 2020 is to develop methods for assessing carbon dynamics and eutrophication in the Baltic Sea through integrated use of [...] | FINNISH ENVIRONMENT INSTITUTE (SYKE) (FI) | Science | Baltic, carbon cycle, carbon science cluster, land, ocean science cluster, oceans, Sentinel-2, Sentinel-3 | The overall goal of the ESA funded project Baltic+ SeaLaBio (Sea-Land Biogeochemical linkages) running from Dec 2018 to May 2020 is to develop methods for assessing carbon dynamics and eutrophication in the Baltic Sea through integrated use of EO, models, and ground-based data The poor state of the Baltic Sea again became apparent during summer 2018 in form of massive and long-lasting cyanobacteria blooms. Warm and sunny weather, combined with good availability of nutrients led to the worst algae situation in a decade. Climate change is expected to cause further warming in this region making these events more and more common in the future. The decades of dumping untreated waste water into the Baltic Sea and the use of fertilizers in agriculture have resulted in strong internal loading. While the water treatment situation has improved and fertilizers are being used more responsibly, the flux of carbon and nutrients from land to sea is still great and in many areas largely unknown. The Sentinel satellites of the Copernicus programme offer an excellent opportunity for characterizing and monitoring the fluxes and processes occurring in coastal zones. This in turn will lead to improved process understanding. With this in mind, the Baltic+ SeaLaBio research project aims to find an answer to the question: • Can we quantify the carbon flux from land to sea with Sentinel-3 (S3) OLCI and Sentinel-2 (S2) MSI data in the Baltic Sea region? And if not, what are the main obstacles and potential solutions to be addressed in the future? In addition to frequent cyanobacteria blooms, the high absorption by colored dissolved organic matter (CDOM) causes problems to the utilization of EO for monitoring the state of the Baltic Sea. The available processors for S3 and S2 often provide overestimated values for Chlorophyll a and underestimate CDOM. The main source of these problems is the failure of the atmospheric correction to provide reasonable marine reflectances. Thus, the project focuses especially on improving the atmospheric correction and in-water inversion algorithms for S3 and S2 images. The developed methods will be validated with in situ data collected from different parts of the Baltic Sea. We will also improve the spatial resolution of a biogeochemical (BGC) model (Ecological ReGional Ocean Model, ERGOM) and compare its output against the EO results. S3 OLCI has a better band combination for water quality estimation than S2 but its spatial resolution limits its use in river estuaries and archipelagos common in the coastal areas of the Baltic Sea. Hence, the synergistic use of these two data sources can lead to improved coverage in coastal regions without compromising the thematic quality of the data. The project will actively disseminate its progress and results in various Baltic Sea and EO events. |
| BALTIC+ SEAL – Sea Level | The current knowledge of the water circulation in the Baltic Sea comes essentially from in situ observations and models. The Baltic+ SEAL (Sea Level) Project aims at providing a consistent description of the sea level variability in the Baltic [...] | TECHNICAL UNIVERSITY OF MUNICH (DE) | Science | altimeter, applications, Baltic, marine environment, ocean science cluster, science | The current knowledge of the water circulation in the Baltic Sea comes essentially from in situ observations and models. The Baltic+ SEAL (Sea Level) Project aims at providing a consistent description of the sea level variability in the Baltic Sea area in terms of seasonal and inter-annual variation and put the results in relationship with the forcing associated with this variability, using a developed dedicated coastal altimetry product. The objective is to create and validate a novel multi-mission sea level product in order to improve the performances of the current state-of-the-art of the ESA efforts in this topic: the Sea Level Climate Change Initiative (SL_cci). In this sense, this project can actually be considered as a laboratory in which advanced solutions in the pre-processing and post-processing of satellite altimetry can be tested before being transferred to global initiatives, such as the future phases of SL_cci. The Baltic Sea includes the two main areas in which the use of satellite altimetry has been severely limited since the start of the “altimetry era”: the presence of sea ice and the proximity of the coast. During the winter season and the sea ice maximum in end of February, 40% of the Baltic Sea is covered by sea ice. The Team aims to apply an unsupervised classification approach to all possible altimetry satellite missions treated in this project (TOPEX-Poseidon, ERS-1/2, Envisat, Jason-1/2/3, SARAL/AltiKa, CryoSat-2, Sentinel-3A/B) to get reliable open water observations and adapt the classification approach to the sea-ice/open-water conditions and different satellite altimetry mission characteristics (e.g. pulse-limited, SAR). The Baltic Sea area is also strongly impacted by Vertical Land Motion and in particular by the glacial isostatic adjustment. As it has the advantage of being an area very well sampled by tide gauges, which measure relative sea level, the Project aims at constituting a more reliable source to compare the absolute sea level from altimetry with the absolute sea level obtained by subtracting the Vertical Land Motion from the trends at the tide gauge and could even be the data source for experiments of differentiation between TG and altimetry trends in the absence of GPS measurements. |
| BAMS-MAZOVIA: Built-up Areas Monitoring Service for Mazovia | The project created a service platform providing reliable information on changes in built-up areas, derived from Sentinel-2 data in a fully automatic manner using image classification algorithms. These algorithms, selected for the tool, are [...] | Geosystems Polska (PL) | Enterprise | generic platform service, land cover, Sentinel-2, water resources | The project created a service platform providing reliable information on changes in built-up areas, derived from Sentinel-2 data in a fully automatic manner using image classification algorithms. These algorithms, selected for the tool, are successfully operated and validated in other Land Cover mapping activities conducted by the consortium partners. Results of the image classification contributed to a systematically updated database, which in turn supports the updating of specific public registries of topographic objects, the detection of illegal buildings, and the monitoring of the impact of new buildings on protected areas. Topographic mapping workflows were updated thereby reducing cost and saving time. The scope of the project was the entire Mazovian Voivodeship, the largest and most populous Polish province. The end users of the service were, among others, the Department of Digitisation, Geodesy and Cartography of the Mazovian Marshal’s Office, the Department of Properties and Infrastructure (Department of Infrastructure and Agriculture) of the Voivodeship Office, the Regional Directorate of Environmental Protection and the Regional Water Management Authority. |
| BathySent – An Innovative Method to Retrieve Global Coastal Bathymetry from Sentinel-2 | The BathySent project aims at the development of an automated method for mapping coastal bathymetry (water depths) on the basis of Copernicus Sentinel-2 mission. The interest of using Sentinel-2 data lies on the capacity to cover large areas [...] | BUREAU DE RECHERCHES GEOLOGIQUES ET MINIERES (BRGM) (FR) | Science | coastal zone, ocean science cluster, permanently open call, science | The BathySent project aims at the development of an automated method for mapping coastal bathymetry (water depths) on the basis of Copernicus Sentinel-2 mission. The interest of using Sentinel-2 data lies on the capacity to cover large areas (National and European scale targeted), while benefiting from the high repeat cycle (5 days) of the mission. The systematic acquisition plan of Sentinel-2 is of major interest for studying and monitoring coastal morphodynamics. The proposed methodology avoids limitation of exiting techniques in terms of dependency on water turbidity and requirement for calibration. The main objective of the project is to propose a method for deriving coastal bathymetry on wide areas (National/European scale) based on Sentinel-2 data and assess its performances. Today knowledge of near-shore bathymetry is essential for multiple applications such as for the study of submarine morphodynamics. These data are vital for planning sustainable coastal development, coastal risks assessments (including tsunamis) and conservation of submarines ecosystems. Moreover, they represent a crucial input for near-shore navigation and submarine resources exploration. The reasons why space-borne remote-sensing techniques must play an essential role in retrieving near-shore bathymetry are threefold. First, space-borne imagery makes it possible to access remote areas with wide spatial coverage at high spatial resolution. Second, because space-borne imagery is acquired on a regular basis, a historical data archive is accessible for most sensors, which enables scientists to access information from the past. Third, the cost of the data is relatively affordable compared to airborne or ground missions. In the BathySent project, we propose to extract bathymetry from a single Sentinel-2 dataset, exploiting the time lag that exists between two bands on the focal plane of the Sentinel 2 sensor. To tackle the issue of estimating bathymetry using two Sentinel 2 images acquired quasi simultaneously, we plan to develop a method based on cross-correlation and wavelet analysis that exploits the spatial and temporal characteristics of the Sentinel 2 dataset to jointly extract both ocean swell celerity (c) and wavelengths (λ). Our team has already started to develop this method based on the French Space Agency’s (CNES) SPOT 5 dataset (Système Probatoire pour l’Observation de La Terre) with promising results (Pourpardin et al., 2015). We called it the CWB method, which stands for Correlation, Wavelets and Bathymetry. Our method combines the direct measurement of c presented in (de Michele et al., 2012) with an original wavelet-based adaptive λ estimate (that we published in Poupardin et al., 2014) to retrieve a spatially dense cloud of (λ, c) couples that are then used to estimate water depth (h) via the dispersion relation presented in equation (1). The method preferably applies to the zone between the coast and an area of depth less than or equal to half the wavelength of the waves (typically up to a hundred meters deep), with the exception of the wave breaking zone. Bibliography Poupardin, A., D. Idier M. de Michele D. Raucoules “Water depth inversion from a single SPOT-5 dataset” IEEE Trans. Geosci. Remote Sens. vol. 54 no. 4 pp. 2329-2342 Apr. 2016. de Michele M., Leprince S., Thiébot J., Raucoules D., Binet R., 2012, “Direct Measurement of Ocean Waves Velocity Field from a Single SPOT-5 Dataset”, Remote Sensing of Environment, vol 119, pp 266–271. |
| BICEP – Biological Pump and Carbon Exchange Processes | The ocean carbon cycle is a vital part of the global carbon cycle. It has been estimated that around a quarter of anthropogenically-produced emissions of CO2, caused from the burning of fossil fuels and land use change, have been absorbed by the [...] | Plymouth Marine Laboratory (GB) | Science | carbon cycle, carbon science cluster, ocean science cluster, oceans, permanently open call, science | The ocean carbon cycle is a vital part of the global carbon cycle. It has been estimated that around a quarter of anthropogenically-produced emissions of CO2, caused from the burning of fossil fuels and land use change, have been absorbed by the ocean. On the other hand, significant advances have been made recently to expand and enhance the quality of a wide range of Remote Sensing based products capturing different aspects of the ocean carbon cycle. Building on recommendations made in a series of recent meetings and reports, on ESA lead initiatives and projects and on other relevant international programmes, the objective of the BICEP project is to bring these developments together into an holistic exercise to further advance our capacity to better characterise from a synergetic use of space data, in-situ measurements and model outputs, the different components of the ocean biological carbon pump, its pools and fluxes, its variability in space and time and the understanding of its processes and interactions with the earth system. To achieve this goal, the BICEP project will first synthesise the current state of knowledge in the field and produce a consolidated set of scientific requirements that define the products to be generated, as well as how these products will be evaluated and used to produce an enhanced BICEP dataset. Major emphasis will be placed on developing unified products to ensure that the carbon budgets made are in balance. Uncertainties in the derived products will also be quantified. A large in situ dataset of ocean carbon pools and fluxes will be created, to be used to evaluate and select the algorithms, with a focus on five key test sites, representative of the range of conditions in the global ocean. Using these selected algorithms, a 20-year time series of data will be generated, built through application of the selected algorithms to the ESA OC-CCI time series, a merged, bias-corrected ocean-colour data record explicitly designed for long-term analysis. The dataset will be used as input to a novel, satellite-based characterisation of the ocean biological carbon pump, quantifying the pools and fluxes, how they vary in time and space, and how they compare with ocean model estimates. The satellite-based Ocean Biological Cabon Pump analysis will then be placed in the context of carbon cycling in other domains of the Earth System, through engagement with Earth System modellers and climate scientists. Finally, a workshop will be organized, to be used as a vehicle to engage the international community in a discussion on how the BICEP work could be pushed forward, and integrated with results from other components of the ocean carbon cycle (e.g. CO2 air-flux and ocean acidification) not covered in the project, and how the representation of satellite-based ocean carbon work could be further improved in the context of large international Earth System analysis, such as the Global Carbon Project and assessments made within the International Panel of Climate Change (IPCC). The proposed work will be delivered by a consortium of twelve international Institutes, led by the Plymouth Marine Laboratory (PML, Plymouth, UK) and composed of top-level scientists, with collective expertise on Remote Sensing, statistical modelling, ocean carbon cycling, theoretical ecology and Earth System science. |
| Big EO Data Analytics | EO data allows us to gather massive global information about our planet Earth’s physical, chemical and biological systems via satellites carrying remote sensing devices. When large amounts of data are concerned, such as those captured by [...] | SPACETEC PARTNERS SPRL (BE) | AI4EO | agriculture, AI4EO, analytics, crops and yields, platforms | EO data allows us to gather massive global information about our planet Earth’s physical, chemical and biological systems via satellites carrying remote sensing devices. When large amounts of data are concerned, such as those captured by remote sensing devices on satellites used in EO, our computers and AI algorithms can be used to help us solve problems. They can learn to recognise patterns and find correlations that humans would otherwise miss. The goal of Big EO data analytics is to bring the worlds of AI and EO closer together through a series of challenges based on societal problems that can be solved by combining AI and EO, stimulating and fostering interaction and collaboration. The initiative targets customers worldwide, with a specific focus on the data science and AI communities. Our customers can be potential challenge participants as well as companies, startups and other entities aiming to launch their challenges in the AI4EO platform. Potential participants can be researchers, students, coders or any other parts interested in combining AI tools and EO data to solve the proposed problems. We are organizing several artificial intelligence-based challenges with world-class partners and sponsors, and our team manages the platform where the challenges are hosted, the overall organization of the challenges and related events, the interaction with contestants and the marketing campaigns. |
| Biodiversity in the Open Ocean: Mapping, Monitoring and Modelling (BOOMS) | Increasing pressure due to anthropogenic drivers is leading to a reduction of global biodiversity and its associated benefits at the planetary scale. In open ocean (seafloor depth greater than 200 m) the most important direct drivers of [...] | Plymouth Marine Laboratory (GB) | Science | biodiversity flagship, biodiversity science cluster, coastal processes, coastal zone, Ecosystems, marine environment, ocean health flagship, ocean science cluster, oceans, science, sea surface topography | Increasing pressure due to anthropogenic drivers is leading to a reduction of global biodiversity and its associated benefits at the planetary scale. In open ocean (seafloor depth greater than 200 m) the most important direct drivers of biodiversity loss is fishing and extraction of seafood, with a lesser but rapidly increasing importance of climate change, pollution and invasive species. These drivers have accelerated in the last 50 years and they are predicted to continue, despite international efforts in the last decades. To guide further action, it is, therefore, urgent and important to develop “fit-for-purpose” observation tools. These observations should be capable of assessing and monitoring how the community structure and function of coastal ecosystems respond to the anthropogenic and natural drivers in a changing climate. The BOOMS project aims to provide the best possible characterisation of oceanic seascapes (habitats defined by physical, chemical or biological characteristics), and its relationship to Essential Biodiversity Variables (EBV) globally. It will produce a >10-year time series of seascapes based on 4-km resolution remote sensing data over the global ocean, combining independent datasets from advanced algorithms of ocean colour and sea surface temperature. BOOMS will focus on three Science Case Studies, for different trophic levels: phytoplankton, zooplankton and fish. In particular, this project main objectives are: Identify and characterise critical applications (Science Case Studies) of remote sensing to study open ocean biodiversity, with a focus on dynamic seascapes. Develop a global dataset and evaluate its application for each Science Case Study. Engage with the community of biodiversity stakeholders (scientific and Early Adopters) and the remote sensing community throughout the project. Define the activities necessary to utilise current and planned sensors to detect measures of marine biodiversity; or define new approaches, if the existing ones are not considered capable to fulfil the targeted science objectives. |
| Biodiversity of the Coastal Ocean: Monitoring with Earth observation (BiCOME) | Increasing pressure on nature due to anthropogenic drivers is leading to a reduction of global biodiversity and its associated benefits at the planetary scale. In coastal environments, the most important direct drivers of biodiversity loss are [...] | Plymouth Marine Laboratory (GB) | Applications | biodiversity flagship, biodiversity science cluster, coastal processes, coastal zone, Ecosystems, marine environment, ocean health flagship, ocean science cluster, oceans, science | Increasing pressure on nature due to anthropogenic drivers is leading to a reduction of global biodiversity and its associated benefits at the planetary scale. In coastal environments, the most important direct drivers of biodiversity loss are fishing, land and sea use, climate change and pollution. These drivers have accelerated in the last 50 years, and they are predicted to continue, despite international efforts in the last decades. To guide further action, it is therefore urgent and important to develop “fit-for-purpose” observation tools. These observations should be capable of assessing and monitoring how the community structure and function of coastal ecosystems will respond to the anthropogenic and natural drivers in a changing climate. BiCOME aims to develop and provide the necessary evidence and promote a set of global Earth Observation products for biodiversity science and policy for the coastal zone. In particular this project will: Identify and characterise critical applications (Pilot Studies) of remote sensing to study coastal biodiversity. Evaluate existing and planned sensor capabilities for each Pilot Study. Engage with the community of biodiversity stakeholders (scientific and policy makers) and the remote sensing community throughout the project. Define the activities necessary to utilise current and planned sensors to detect measures of marine biodiversity; or define new approaches, if the existing ones are not considered capable to fulfil the targeted science objectives. |
| BIODIVERSITY+ PRECURSORS EXPRO+ THEME 1 – TERRESTRIAL: Earth Observation for Biodiversity Modelling (EO4Diversity) | The main EO4Diversity objective and key innovation is to predict and monitor biodiversity in terrestrial ecosystems through the integration of state-of-the-art multi-sensor Earth Observation (EO) imagery and products with next-generation [...] | UNIVERSITY OF TWENTE (NL) | Science | biodiversity flagship, biodiversity science cluster | The main EO4Diversity objective and key innovation is to predict and monitor biodiversity in terrestrial ecosystems through the integration of state-of-the-art multi-sensor Earth Observation (EO) imagery and products with next-generation ecological models. The project addresses important biodiversity science gaps, including (i) filling data gaps in the geographic, temporal, habitat and taxonomic composition coverage from in situ biodiversity observations; (ii) filling knowledge gaps, thereby assessing global species diversity; (iii) forecasting ecological degradation in order to define effective actions to reduce terrestrial biodiversity loss; as well as (iv) filling gaps in the data-policy link which may lead to a disconnection of biodiversity data that EO can generate and policy strategies including the EU Biodiversity Strategy for 2030, the UN SDGs and the Convention on Biodiversity (CBD) post-2020 targets. The scientific and policy analyses, pilot demonstrations and agenda-setting that will be done during EO4Diversity will serve as a basis for the implementation of the EC-ESA Biodiversity Flagship Action in 2023. |
| BIODIVERSITY+ PRECURSORS EXPRO+ THEME 2 – FRESHWATER (BIOMONDO) | The European Space Agency (ESA) activity called Biodiversity+ Precursors is acontribution to the joint EC-ESA Earth System Science Initiative launched in February 2020 to jointly advance Earth System Science and its response to the global [...] | BROCKMANN GEOMATICS SWEDEN AB (HEAD (SE) | Science | biodiversity flagship, biodiversity science cluster, rivers | The European Space Agency (ESA) activity called Biodiversity+ Precursors is acontribution to the joint EC-ESA Earth System Science Initiative launched in February 2020 to jointly advance Earth System Science and its response to the global challenges that society is facing in the onset of this century. The ESABiodiversity+ Precursors include three projects on different themes; land (EO4Diversity), coast (BiCOME) and freshwaters (BIOMONDO). BIOMONDO is the freshwater project, and has a focus on biodiversity in lakes, wetlands, river and streams. Based on an in-depth-analysis of the relevant sources for scientific and policy priorities, the main knowledge gaps and challenges in biodiversity monitoring, including capabilities of current and future Earth Observation (EO) systems, are identified. Requirements related to EBVs, to drivers for change and to ecosystem functions are compared to (todays and future) possibilities and available data from EO. These findings are then the basis for development of innovative integrated earth science solutions that integrate EO based products, state-of-the-art biodiversity modelling and in situ data using advanced data science andinformation and communications technology. The BIOMONDO team has selected three solutions, or pilots, which focus on eutrophication, water temperature and heat waves, and river connectivity, and their impact on biodiversity. |
| BiomAP | The BiomAP project aims to Integrate active and passive microwave data towards a novel global record of aboveground biomass maps. This comprises an end-to-end assessment of active and passive microwave observations at coarse spatial resolution [...] | GAMMA REMOTE SENSING AG (CH) | Science | Biomass, carbon cycle, forestry, permanently open call, SMOS | The BiomAP project aims to Integrate active and passive microwave data towards a novel global record of aboveground biomass maps. This comprises an end-to-end assessment of active and passive microwave observations at coarse spatial resolution at the longest wavelengths available in space to generate global AGB estimates. This work will eventually provide a 5-years baseline, from 2015 to 2020, relevant to carbon-related studies. Global and repeated microwave observations will come from ESA (SMOS), Eumetsat (ASCAT), JAXA (AMSR2) and NASA (SMAP) missions and will be used in combination with NASA LiDAR observations (ICESat GLAS, GEDI and ICESat-2). The overarching objective of this study is to enhance the accuracy of global AGB estimates compared to existing data products and reported statistics by integrating the satellite observations currently most sensitive to the biomass stored in aboveground vegetation |
| BIOMASCAT: Assessing vegetation carbon dynamics from multi-decadal spaceborne observations | Characterization of forest biogeochemical cycles is of paramount importance in Earth system science to understand contemporaneous dynamics and for expanding global land models in order to predict future trends of vegetation and climate. Thanks [...] | GAMMA REMOTE SENSING AG (CH) | Science | biosphere, carbon cycle, carbon science cluster, forestry, land, permanently open call, SAR, science | Characterization of forest biogeochemical cycles is of paramount importance in Earth system science to understand contemporaneous dynamics and for expanding global land models in order to predict future trends of vegetation and climate. Thanks to the increasing amount of spaceborne observations of land and ocean surfaces, data-driven models are revealing intriguing trends and mechanisms and model evaluation exercises are reaching global insights into temporal dynamics, which would not be achievable otherwise. The global characterization and the accurate knowledge of terrestrial carbon pools have been acknowledged as a fundamental variable for driving research in the terrestrial component of Earth system models. Traditionally, carbon pools are best estimated from measurements of forest inventories. However, these estimates are sparse in time and sometimes only locally relevant. There is therefore a strong requirement for data collection approaches that expand these spatial-temporal representativeness limits. However to date, despite the long term records of observations from space, only one dataset of biomass extended over multiple years so far – a 10 year passive microwave data. This project is developing a more comprenensive approach to the inforamtion gap by combining SAR and scatterometer data collected since the early 1990s to estiamte biomass properties. As the spatial resolution of both sensors is consistent with the range of length scales typcially used within ecosystem models it is expected that this development will provide a unique contribution to improving ecosystem modelling and assessment. |
| Black Sea and Danube Regional Initiative – Applications: Environmental Risk Management in the Danube Catchment | The Environmental Risk Management in the Danube Catchment (The Danube Environmental Risk Assessment Platform, DEAP) project aims to create a platform of applications based on Earth Observation (EO) to support Environmental Risk Management within [...] | The Icon Group (IE) | Applications | Black Sea and Danube, regional initiatives | The Environmental Risk Management in the Danube Catchment (The Danube Environmental Risk Assessment Platform, DEAP) project aims to create a platform of applications based on Earth Observation (EO) to support Environmental Risk Management within the Danube catchment. The purpose of the project is to provide regional stakeholders, who currently do not regularly use EO data, with access to dynamic environmental assessments using such datasets. The service will comprise a suite of cloud-based applications which will detect, monitor, analyse and characterise the sources of environmental problems using available EO data in conjunction with in-situ inputs and other reference data. Service applications will be developed for deployment in the cloud and shall employ advanced dispersion modelling techniques in conjunction with EO Data to deliver meaningful (actionable) maps, statistics and other data across 20 countries. The project includes engagement with regional stakeholders, the definition of the service portfolio and data processing chains, and the provision of the operational service to stakeholders. The service will benefit from existing ESA/EC DIAS infrastructures to support the delivery of environmental risk assessments in a fully automated way. At an operational level, the service will identify industrial waste discharge, transport waste discharge, agricultural run-off, and ecosystem degradation in near real time, and shall represent a unique tool to regional agencies. Stakeholders include environmental protection agencies, port authorities, fisheries management agencies, the International Commission for the Protection of the Danube, various development agencies, etc. This activity corresponds to Priority Application Domain C of the original Invitation to Tender. |
| Black Sea and Danube Regional Initiative – Black Sea Environmental Protection | The Black sea is located in the north-eastern part of the Mediterranean Sea. It is a semi-closed basin that communicates with the Planetary Ocean through the Bosporus and Dardanelles Straits. The water balance is highly imposed by the freshwater [...] | NATIONAL INSTITUTE FOR MARINE RES.R (RO) | Enterprise | applications, Black Sea and Danube, carbon cycle, enterprise, regional initiatives | The Black sea is located in the north-eastern part of the Mediterranean Sea. It is a semi-closed basin that communicates with the Planetary Ocean through the Bosporus and Dardanelles Straits. The water balance is highly imposed by the freshwater inputs from some of the biggest rivers in Europe in terms of solid and liquid discharge: (e.g. Danube). As an endorheic system, the main characteristics that make Black Sea a special study place are the input of significant freshwater, the lack of strong vertical currents, and the limited water exchange with the Mediterranean Sea. Earth observation services for Black Sea Protection (EO4BSP) overlap the entire area of the Black Sea and propose a holistic approach that covers different elements with potential environmental impact.The project will implement six services that are going to be delivered to a number of 13 stakeholders from the Black Sea riparian countries and one International organization – The Black Sea Commission. S1 – Land Use – Land Cover coastal changes. Economic development is associated with land-use changes, transforming the natural green zones into exclusive anthropogenic areas. Analysis and modeling of land-use change trends and urbanization allow us to evaluate the spatial development patterns providing a key for effective planning practices in the context of Marine Strategy Framework Directive (MSFD) and MaritimeSpatial Planning (MSP) implementation. S2 – Eutrophication. Eutrophication represents one of the most severe and widespread environmental problems for coastal zone managers (IOCCG Report Number 3, 2000). In the “Black Sea region briefing – The European environment — state and outlook 2015” published by European Environmental Agency, eutrophication is considered one of the main four key transboundary challenges of the Black Sea. S3 – Marin Front Identification and mesoscale circulation. This service will include data fusion, satellite observations, numerical modeling, and data assimilation, as well as skill assessment and metrics with a focus on sea state, temperature, turbidity, and SPM, identification of ocean fronts. EO4BSP will provide services, based on numerical simulation and data assimilation, of currents, salinity and temperature, and distribution, height and period of wind waves, ocean colour, sediment transport dynamics, and biogeochemical component as well as the forecast of these parameters. S4 – Oil Tankers path identification.This service will make use of historical AIS data. Provided by EMODnet, the present data can be used in many ways, not only for oil tankers’ path identification but also for illegal trafficking in the Black Sea. S.4 will be used as decision tool for stakeholders. This application will be intimately linked with the Oil spill monitoring service. S5 – Oil spills identification and monitoring.Maritime surveillance activities are traditionally carried out by patrol ships or aircraft. However, in recent years the use of synthetic aperture radar (SAR) and optical satellite imagery has proved highly effective in ship traffic and oil spill monitoring. The capability of observing wide areas in almost all-weather and light conditions makes SAR sensors the most suitable tool formaritime surveillance purposes. S6 – High-resolution water quality monitoring in anchorage areas. Monitoring water quality parameters through remote sensing techniques may offer a comprehensive overview of water bodies due to the spatial and spectral capabilities of the sensors. The spatial and temporal distribution of these indicators will reveal the improvement or alteration of the surface water health status. This may be a consequence of nutrients or organic pollution or contamination of waters with hazardous substances. The service will focus on: chlorophyll a (chl_a), turbidity, and total suspended matter (TSM). Monitoringthe evolution of this parameter at several moments would reveal the anchorage areas aquatic ecosystem’s health status. |
| Black Sea and Danube RI – Applications | This activity is part of the EO (Earth Observation) Exploitation Platforms element of ESA’s Earth Observation Envelope Programme (EOEP-5) aiming to establish regional information services for Black Sea Region in the agriculture and forestry [...] | GISAT S.R.O. (CZ) | Enterprise | applications, Black Sea and Danube, enterprise, regional initiatives | This activity is part of the EO (Earth Observation) Exploitation Platforms element of ESA’s Earth Observation Envelope Programme (EOEP-5) aiming to establish regional information services for Black Sea Region in the agriculture and forestry domains. It is intended to develop a suite of service cases demonstrating the monitoring services to CAP paying agencies, precision agriculture, monitoring of agriculture production and forest resource management (forest area, type and deforestation mapping) with users in Czech Republic, Georgia, Romania and Hungary. |
| Blue economy: innovation clusters, Atlantic natural resources management and maritime spatial planning | The 2-years Blue Economy project aims at developing and demonstrating EO driven data solutions, which deliver actionable information to key coastal stakeholders. Applications will focus on the areas of coastal monitoring, ocean renewable energy, [...] | GMVIS SKYSOFT S.A. (PT) | Regional Initiatives | Atlantic, blue economy, coastal zone, marine environment, maritime spatial planning, oceans, regional initiatives, renewable energy | The 2-years Blue Economy project aims at developing and demonstrating EO driven data solutions, which deliver actionable information to key coastal stakeholders. Applications will focus on the areas of coastal monitoring, ocean renewable energy, and marine litter. It is being implemented through the European Space Agency’s Atlantic Regional Initiative. In parallel, a range of Atlantic-focused recommendations will be developed from engaged stakeholder inputs, and community development activities. These perspectives will (i) inform and enhance the roadmap being developed by the European Space Agency for the Atlantic Region, and (ii) find a seed Community of Practice of maritime-EO technology innovators for the Atlantic, focused on developing EO solutions to address Marine Strategy Framework, and Marine Spatial Planning ambitions. Rationale: As the Maritime Spatial Planning (MSPD) and Marine Strategy Framework (MSFD) directives are implemented across Europe, EU member states and aligning nations need innovative information gathering tools to monitor progress towards the goals of these two directives. Information from satellites can satisfy a number of these monitoring needs. The EO sector needs to demonstrate technological viability, and while doing so engage with policy makers and legislators to ensure information products are acceptable for monitoring and legal purposes. The Blue Economy project is a demonstration of this potential for Atlantic coastal states. A synthesis of products/services being developed is available in these slides. |
| Bringing the power of AI to Sentinel Hub | Sentinel Hub is one of the most commonly used services for satellite imagery processing, powering hundreds of data scientists worldwide, who jointly process more than 12 billion km2 of Sentinel, Landsat, MODIS and commercial satellite images [...] | SINERGISE LTD. (SI) | Digital Platform Services | artificial intelligence, platforms | Sentinel Hub is one of the most commonly used services for satellite imagery processing, powering hundreds of data scientists worldwide, who jointly process more than 12 billion km2 of Sentinel, Landsat, MODIS and commercial satellite images every single month – an equivalent of 80-times the total surface area of the Earth. During the project, we will upgrade Sentinel Hub to provide even more value in AI procedures by allowing users to deploy more powerful custom scripts and scale up the level of processing. This should speed up the development of the new ML model and make it much easier to integrate in the 3rd party systems – ML developers will not need to set-up all the elements of the operational system (resource management and scheduling, monitoring, error handling, billing, etc.) – they will simply upload their model in the Sentinel Hub and expose it via existing services and standard interfaces. |
| Building trust in digital economy | While IPR protection will have to rely mainly on contractual mechanisms, technology is increasingly offering means to enforce IPR protection via technical solutions. The study was to identify the approaches that are ready for operational use and [...] | ARGANS LIMITED (GB) | Digital Platform Services | blockchain, platforms | While IPR protection will have to rely mainly on contractual mechanisms, technology is increasingly offering means to enforce IPR protection via technical solutions. The study was to identify the approaches that are ready for operational use and can be implemented as part of the common architecture. The implementation strategy defined aftr user consultation entailed development of the IPR traceability services using the Merkel tree hash-functions which are the underlying the cryptographic element of the blockchain data structures. This approach has been independently validated by the Nov. 2020 announcement of the European Commission Action Plan for Intellectual Property Right Protection which is addressing the impact of new technologies (such as AI and blockchain) on the IP system. The underlying ambition of the European Commission is to create a ground breaking unitary system for Patent and IP recognition and dramatically increase the IP registration by SMEs using blockchcain-driven services to be offered by the EU Intellectual Property Office (EU IPO). A liaison with the EU Intellectual Property Office (IPO) has been established and EU IPO demonstrated own blockchain-based IP infrastructure being developed for all European IPOs. There are multiple other initatives at the EU IPO that will drive the digitisation and innovation agenda and it was agreed that multiple checkpoints will continue to enhance the cooperation opportunity and for ESA to represent the EO sector IP perspectives to the EU IPO stakeholders. The project has demonstrated blockchain-based IP protection/registration/traceability services deployed on the ESA Coastal TEP. The video demonstration of the Proof-of-Concept is available at https://www.youtube.com/playlist?list=PLNePkHV3wXsrgHMrChF-Ws1FLGMoub-d9 |
| BURNING QUESTIONS ON CARBON EMISSIONS FROM FIRES (BURNQUEST) | Landscape fires, whether natural or human-induced, have a key impact on the Earth system via the release of pollutants, greenhouse gases and aerosols, affecting human health and climate. Over the next decades their role may increase related to [...] | Netherlands Institute for Space Research (NWO-I) (NL) | Science | Aerosols, carbon cycle, living planet fellowship, Sentinel-2, Sentinel-5P, TROPOMI, wildfires | Landscape fires, whether natural or human-induced, have a key impact on the Earth system via the release of pollutants, greenhouse gases and aerosols, affecting human health and climate. Over the next decades their role may increase related to drier and warmer conditions, exacerbating biome shifts and lowering biodiversity. In addition, this may provide one of the most detrimental climate-carbon feedbacks raising CO2-levels. The past two decades have seen gradual improvements in quantifying fire emissions, including those from CO2, with global emission estimates converging to around 2 Pg C per year, equivalent to 20% of global fossil fuel emissions. New emerging information on burned area and emissions modeling indicates this estimate may be a gross underestimation with recent insights indicating global fire emission estimates may be closer to 4 Pg C per year. Parallel to these new developments,thespace-based TROPOMI instrument, onboard ESA Sentinel-5p mission,is now providing unprecedented top-down constraints on fire emissions, in particular those of carbon monoxide (CO). We propose to build a modeling framework to address fire emission underestimation by solving for an inverse problem: calculating improved fire emissions using observations of CO from space. We will apply this framework with specific focus on the African sub-Saharan savanna and Indonesian peatland fires. These regions are of interest because they are responsible for a staggering 60% of the global fire CO2 output, but the emissions may even be much larger in reality. Alongside TROPOMI, we include in our study other important datasets, such as NO2 from TROPOMI to learn more about the combustion efficiency, and new high resolution burned area information derived from ESA’s Sentinel-2 images that provide alternative fire emissions that should better reflect the contributions of smaller sized fires. The novelty of our work is not only reflected in our attempt to improve and better understand the uncertainties of fire emissions of CO-and indirectly CO2-but also to provide a much-needed independent benchmark to which we can compare current and new emerging fire emission estimates against. |
| Business Model Validation for Exploitation Platforms | This activity validated the specific business model of the EODC initiative - hyprid use of public infrastructure for public R&D and commercial use - for its possible reuse in the context of the Exploitation Platform programmatic activities. | EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT) | Digital Platform Services | platforms | This activity validated the specific business model of the EODC initiative – hyprid use of public infrastructure for public R&D and commercial use – for its possible reuse in the context of the Exploitation Platform programmatic activities. |
| CadasterENV Austria, Multi-Scale and Multi-Purpose Land Cover Monitoring System in Austria | In order to meet the reporting obligations from international conventions, European directives and national legislations, countries are required to produce up to date, detailed and harmonised information on their land cover and its use, at [...] | GeoVille (AT) | Applications | applications, land cover | In order to meet the reporting obligations from international conventions, European directives and national legislations, countries are required to produce up to date, detailed and harmonised information on their land cover and its use, at different scales, and for different domains of applications. Austria initiated its Land Information System Austria (LISA) in 2010 with the objective to achieve a national consensus on how to perform a continuous mapping of the national land cover and monitor its use. The CadasteENV Austria project aimed at developing a national multi-scale and multi-purpose Land Cover mapping and monitoring system in Austria according to the national specifications defined by the LISA project. The principal objectives of CadasterENV Austria was – the Integration of Pléiades satellite data in the LISA production chain – the production of VHR land cover in Austrian urban agglomerations (10,000 km2) – the development of methods to detect areas with frequent changes (hot spots) based on high resolution satellite images (SPOT 4/5 in preparation to the Sentinel 2 exploitation) – the production of a hot spot change maps (Land Cover Change Alerts) for the whole of Austria. The project was extended with the GSE CadasterENV project to integrate Sentinel-2 into the existing Land Information System Austria (LISA), and to operationalize a national Land Monitoring System, which is multi-temporal (bringing the annual seasonality/variability of land cover / land use to LISA), multi-scale (integrating Sentinel 2 observations with VHR imagery from Pleiades and national airborne campaigns) and multi-purpose (responding to user needs from different land sectorial communities). Five S2-based innovative products were developed (HR Land Cover Mapping, Enriched VHR Land Cover Mapping, Land Cover Change Alert, Land Use Monitoring and Ecosystem Monitoring) and validated over a number of representative pilot areas. |
| CadasterENV Sweden, Multi-Scale and Multi-Purpose Land Cover Monitoring System in Sweden | In order to meet the reporting obligations from international conventions, European directives and national legislations , countries are required to produce up to date, detailed and harmonised information on their land cover and its use, at [...] | METRIA MILJOEANALYS (SE) | Applications | applications, land cover | In order to meet the reporting obligations from international conventions, European directives and national legislations , countries are required to produce up to date, detailed and harmonised information on their land cover and its use, at different scales, and for different domains of applications. All Swedish stakeholders involved in land cover monitoring have emphasized the need for a homogenous and nationwide Land Cover database, which can be updated, on a regular basis and in a cost-effective manner. The objective of the CadasteENV Sweden project was to develop a national multi-scale and multi-purpose Land Cover mapping and monitoring system in Sweden, according to national user specifications. The system is comprised of two components: – a Land Cover mapping component based on a stratified approach which makes use of HR (SPOT-5 in prepararation of Sentinel 2) and VHR (Pleiades) data, combined with airborne data (orthophotos and LIDAR data) and existing land information databases in Sweden. – a Land Cover Change Alert component to detect areas with fast land cover changes (hot spots). The project was extended to support methodological adaptations to Sentinel 2, and facilitate a national roll-out by the Swedish Environmental and Protection Agency (SEPA). The Swedish National Land Cover Mapping (called NMD) which will be released in January 2019 is based on the Land Cover data model and methods developed by CadasterEnv Sweden. |
| CARBON-RO: Near-Real-Time CARBON EXTREMES | There is a need for comprehensive, accurate, and low-latency information on land carbon fluxes to be underpinned by high resolution remote-sensing datastreams. A key policy-relevant challenge for the scientific community is the lack of a rapid [...] | UNIVERSITY OF EXETER (GB) | Science | biosphere, carbon science cluster, ecosystems/vegetation | There is a need for comprehensive, accurate, and low-latency information on land carbon fluxes to be underpinned by high resolution remote-sensing datastreams. A key policy-relevant challenge for the scientific community is the lack of a rapid quantification of carbon losses from recent mega droughts or fires despite numerous observations being available. The Near-Real-Time (NRT) Carbon Extremes project will address this major challenge, with the following objectives: to develop robust observation-based estimates of changes in the land carbon sinks and their driving processes in near-real-time. to realize a first NRT process-based system for land biogeochemistry. to utilise output from the NRT system in combination with Earth Observation (EO)-data to diagnose and attribute the impact of climate extremes on the regional and global carbon cycle (Europe heatwave 2022, Brazil fires 2022, and a further region, to be defined depending on weather extreme occurrence, in 2023). A key policy-relevant challenge for the scientific community is the lack of a rapid quantification of carbon losses from recent mega droughts or fires despite numerous observations being available. The NRT Carbon Extremes project will address this major challenge, with the following objectives: To address these objectives, we will implement a near-real-time (NRT) carbon monitoring system for the terrestrial biosphere. For the first time the community will exploit ECVs and Dynamic Global Vegetation Models (DGVMs) in NRT instead of with a lag of 2-3 years. We will apply 3 global DGVMs with NRT climate forcing data (ERA5), and combine their results with EO-derived products to attribute the net carbon flux to underlying processes (i.e. changes fluxes: primary production, respiration and fire; and carbon stocks). |
| CASSIS (Climate Altimetric Studies with Sea Ice and Snow) | Since the 1970s, spatial imagery has allowed to witness dramatic changes in sea ice extension and distribution. However, the sea ice thickness (SIT), which is a fundamental variable to understand and predict sea ice dynamics, is still [...] | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) (FR) | Science | altimeter, Antarctica, climate, CryoSat, living planet fellowship, Sentinel-3, snow and ice | Since the 1970s, spatial imagery has allowed to witness dramatic changes in sea ice extension and distribution. However, the sea ice thickness (SIT), which is a fundamental variable to understand and predict sea ice dynamics, is still insufficiently observed. So far, the only possibility to observe the sea ice freeboard (the sea ice emerged part which is measured by altimetry) at a global scale is to use spatial altimetry. However, despite recent advances mainly coming from the development of SAR altimeters on-board the CryoSat-2 and Sentinel-3A&B satellites, sea ice freeboard measurements can not provide reliable climate time series. As a consequence, sea ice thickness satellite data can hardly be integrated into sea ice models for climate studies. In order to improve sea ice freeboard and thickness measurements from altimetry, this project will address the following points: The use of radar echo processing methods (also called ‘retrackers’) based on physical models instead of current heuristic models. The use of new snow depth observation products (dual-frequency altimetry, Advanced Microwave Scanning Radiometer, AMSR), A better quantification of uncertainties in sea ice products. As a first step, we will compute sea ice freeboard and thickness in Antarctica using a classical processing chain previously validated in Arctic (e.g., Guerreiro et al 2017, Paul et al 2018).This will provide a first sea ice data reference based on the state of the art covering the Envisat and CryoSat-2 time period (2002-2019). Note that the bi-frequency Ka/Ku snow depth data, developed at the LEGOS within the ESA CryoSat-2 +Antarctica, will be used. These results will then support the launch of the future Copernicus CRISTAL satellite mission The second step is to substitute the heuristic TFMRA retracker (Helm et al, 2014) by the SAMOSA+ physical retracker outputs provided through the ESA GPOD cluster in the processing chain. The relevancy of the methodology used at the LEGOS to derive freeboard estimates has already been demonstrated in Arctic within the Cryo-seaNice ESA project (Laforge et al 2019). We will apply the same procedure in the southern ocean. In addition, a SLA product aiming to ocean circulation studies will be provided. On a third step these new sea ice altimetric products will be compared with the LIM-3 CMEMS sea ice model. This work will be carried out in cooperation with MERCATOR-Ocean. The analyses will allow to identify the possible biases of the model and to re-adjust the level of uncertainty of sea ice observation products. The objective is to perform a preliminary work in the perspective of data assimilation and OSE’s experiments. Finally, we plan to use this synergy to provide a new estimation of global sea ice volume variability and changes. Our scientific objective is to re-evaluate the ocean global freshwater budget to provide, for the first time, a new constraint to the land ice contribution to sea level rise. Note that this exciting challenge was considered impossible in Monk, 2003. |
| CERES mining products – Phase I | With this program, CybELE aimed to apply its services also within the mining industry. The mining industry is facing major challenges related to waste management and pollution mitigation. Environmental compliance has become a top-priority [...] | CybELE LAWGICAL LDA (PT) | Enterprise | enterprise, mining | With this program, CybELE aimed to apply its services also within the mining industry. The mining industry is facing major challenges related to waste management and pollution mitigation. Environmental compliance has become a top-priority concern for the sector. Mining stakeholders devote an important and growing part of operational expenses to develop best practices and to achieve the highest environmental/ethical standards in order to obtain and maintain a Social License to Operate (SLA). Moreover, regulatory frameworks are becoming increasingly stringent both concerning environmental legal requirements and the liability burden associated with potential remediation of damages. Governmental entities also have a strong interest in using wide-scale monitoring capacities to improve the control of mining areas. On the basis of consultation with mining stakeholders (industries and governmental entities), CybELE has demonstrated opportunities for innovative solutions to support this sector with the monitoring of environmental status and compliance. The result of the first phase led to CERES, a digital system providing satellite-based environmental compliance monitoring service dedicated to the mining & extractive sector. The system provides both EO & GIS (Geographical Information Systems) datasets answering the specific need of the sector (e.g. monitoring of chemical contamination) as well as a user interface tailored for the services and features required for a mining expert. The service can be used by a series of entities associated with mining activities including mining companies, consulting firms, insurance companies and banks, or governmental agencies and international organisations. It can be integrated into conventional processes and workflows at any stage of the mine life cycle. During this first phase of demonstration, the service has been demonstrated and validated at the stage of mine rehabilitation to monitor the implementation of environmental policies following the closure of a site. |
| CITYSATAIR | More than half of the world’s population is living in cities. According to the WHO air quality database 80% of people living in urban areas that monitor air pollution are exposed to air quality levels that exceed WHO limits. Narrowing down to [...] | KNMI (NL) | Applications | air quality, atmosphere science cluster, atmospheric chemistry, atmospheric indicators, health, permanently open call, public health, science | More than half of the world’s population is living in cities. According to the WHO air quality database 80% of people living in urban areas that monitor air pollution are exposed to air quality levels that exceed WHO limits. Narrowing down to cities in low and middle income countries with more than 100 000 inhabitants, this number increases to 98%. To resolve urban air pollution problems a clear understanding of the local situation is essential. Low-income cities, which are most impacted by unhealthy air, usually have less resources available for a good reference network. It is here where a combination of low-cost sensors and satellite data can make a difference. So far, only very few studies aim at joining heterogeneous data sources of urban air quality, and to our knowledge no previous work has provided practical solutions which can be implemented in cities everywhere. We therefore propose to develop and demonstrate a methodology that is capable of exploiting the various available data sources, to combine them in a mathematically objective and scientifically meaningful manner, and to provide value-added maps of urban air quality at high spatial resolution. |
| CLEAN ARCTIC: GOCE AND ALTIMETRY FOR OCEAN CIRCULATION AND POLLUTION MANAGEMENT IN THE ARCTIC | The objective of the work proposed is to develop and validate a new method to compute Absolute Dynamic Topography (ADT) in the Arctic Ocean. This product will be devoted to clean ocean applications: First, the ADT will be assimilated in the [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Applications | Arctic, GOCE, Ocean Circulation, water quality | The objective of the work proposed is to develop and validate a new method to compute Absolute Dynamic Topography (ADT) in the Arctic Ocean. This product will be devoted to clean ocean applications: First, the ADT will be assimilated in the CCMEP Regional Ice Ocean Prediction System (RIOPS). RIOPS is used operationally to provide numerical guidance for a variety of applications such as: search and rescue, oil spill response efforts, maritime situation awareness and maritime safety (e.g. ice hazards). The impact for oil spill management will be analysed in collaboration with the Canadian Environmental Emergency Response Section. Then, the improved outputs of RIOPS (surface currents and 3D temperature and salinity field) will be used in a model of microplastic dispersion. This will provide a map of microplastic distribution in the Arctic and thus the identification of pollution risk areas and the potential for attribution (namely, the determination of most likely plastic pollution sources). |
| CLIMATE DATA RECORD OF STRATOSPHERIC AEROSOLS (CREST) | Stratospheric aerosols impact the radiative forcing and thus the energy balance of the Earth’s atmosphere, therefore information about their distribution and variability is of high importance for climate related studies. The main [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | Aerosols, atmosphere, atmosphere science cluster, atmospheric chemistry, atmospheric indicators, climate, permanently open call | Stratospheric aerosols impact the radiative forcing and thus the energy balance of the Earth’s atmosphere, therefore information about their distribution and variability is of high importance for climate related studies. The main scientific objective of the project CREST is creating a new merged long-term time series of the vertically resolved aerosol extinction coefficients using data records from six limb and occultation satellite instruments: SAGE II, OSIRIS, GOMOS, SCIAMACHY and OMPS-LP instruments for the years from 1984 to present. The merged aerosol extinction coefficient is computed as the median of the adjusted data from the individual instruments. The merging of aerosol profiles is performed by transformation the aerosol datasets from individual satellite instruments to the same wavelength, i.e., 750 nm, and their de-biasing and homogenization by adjusting the seasonal cycles. The merged time series of vertically resolved monthly mean aerosol extinction coefficients at 750 nm is provided in 10° latitudinal bins from 90°S to 90°N, in the altitude range from 8.5 km to 39.5 km. The time series of the stratospheric aerosol optical depth (SAOD) is created by integration of aerosol extinction profiles from the tropopause to 39.5 km; it is also provided as monthly mean data in 10° latitudinal bins. The created aerosol dataset is in open access at: https://fmi.b2share.csc.fi/records/8bfa485de30840eba42d1d407f4ce19c |
| Cloudfree Mosaic Platform Pathfinder | This activity shall demonstrate platform efficiency in generatong a worldwide cloudfree Sentinel-2 mosaic at full resolution | EOX IT SERVICES GMBH (AT) | Digital Platform Services | platforms | This activity shall demonstrate platform efficiency in generatong a worldwide cloudfree Sentinel-2 mosaic at full resolution |
| Coastal erosion 1 | The Coastal Erosion project shall be conceived as EO application project that aim at developing innovative EO products and methods in response to authoritative end-user requirements. The Coastal Erosion project shall prepare the ground for a [...] | I-SEA (FR) | Applications | applications, Atlantic, coastal zone, ocean science cluster | The Coastal Erosion project shall be conceived as EO application project that aim at developing innovative EO products and methods in response to authoritative end-user requirements. The Coastal Erosion project shall prepare the ground for a long-term exploitation by large user communities, and is expected to provide substantial and concrete benefits to the targeted user communities. The source of EO data used, the novelty of the EO derived products, the innovating algorithmic approaches but also from the awareness and readiness of the user community involved. The innovative aspects of the Coastal Erosion project shall comply with the above prerequisite of the most innovative aspects of the Sentinel-1 and Sentinel-2 missions of the European Copernicus initiative combined with the ERS-1, ERS-2, Envisat and SPOT archives to provide the best products suited to end user requirements over the past 25 year. The scope of the Coastal Erosion project is the development and demonstration of innovative EO products that will be used by users communities responsible to monitor and control this process. Together with the champion user organizations, a set of innovative products and services shall be developed, including a scientifically sound validation, a comprehensive user assessment and a representative service roll-out analysis. While maintaining the openness of the scope and domains of innovation, the Coastal Erosion project shall develop innovative approaches that best exploit the novel observational capabilities of the Sentinel-1 and Sentinel-2 constellations. The Sentinel missions of the European Copernicus initiative brings new observational capabilities that were not available beforehand and, as a consequence, offers unprecedented opportunities to address these R&D priority issues. In particular the Sentinel-1 and Sentinel-2 missions, used individually or jointly, significantly improve the quality and adequacy of High Resolution (HR) satellite observations in both radar and optical domains. In order to fully exploit these new capabilities, additional R&D efforts are needed. The Coastal Erosion project is expected to provide the ideal platform to undertake these R&D activities in close partnership with key user organizations that best represent their respective communities. |
| Coastal erosion 2 | The Coastal Erosion project shall be conceived as EO application project that aim at developing innovative EO products and methods in response to authoritative end-user requirements. The Coastal Erosion project shall prepare the ground for a [...] | ARGANS LIMITED (GB) | Applications | Atlantic, coastal zone, ocean science cluster | The Coastal Erosion project shall be conceived as EO application project that aim at developing innovative EO products and methods in response to authoritative end-user requirements. The Coastal Erosion project shall prepare the ground for a long-term exploitation by large user communities, and is expected to provide substantial and concrete benefits to the targeted user communities. The source of EO data used, the novelty of the EO derived products, the innovating algorithmic approaches but also from the awareness and readiness of the user community involved. The innovative aspects of the Coastal Erosion project shall comply with the above prerequisite of the most innovative aspects of the Sentinel-1 and Sentinel-2 missions of the European Copernicus initiative combined with the ERS-1, ERS-2, Envisat and SPOT archives to provide the best products suited to end user requirements over the past 25 year. The scope of the Coastal Erosion project is the development and demonstration of innovative EO products that will be used by users communities responsible to monitor and control this process. Together with the champion user organizations, a set of innovative products and services shall be developed, including a scientifically sound validation, a comprehensive user assessment and a representative service roll-out analysis. While maintaining the openness of the scope and domains of innovation, the Coastal Erosion project shall develop innovative approaches that best exploit the novel observational capabilities of the Sentinel-1 and Sentinel-2 constellations. The Sentinel missions of the European Copernicus initiative brings new observational capabilities that were not available beforehand and, as a consequence, offers unprecedented opportunities to address these R&D priority issues. In particular the Sentinel-1 and Sentinel-2 missions, used individually or jointly, significantly improve the quality and adequacy of High Resolution (HR) satellite observations in both radar and optical domains. In order to fully exploit these new capabilities, additional R&D efforts are needed. The Coastal Erosion project is expected to provide the ideal platform to undertake these R&D activities in close partnership with key user organizations that best represent their respective communities. |
| Coastal Thematic Exploitation Platform | Through the provision of access to large volumes of EO and in-situ data, computing resources, algorithm development space and the fundamental processing software required to extract temporal and spatial information from Big Data, C-TEP provides [...] | ACRI-ST S.A.S. (FR) | Digital Platform Services | applications, coastal zone, platforms | Through the provision of access to large volumes of EO and in-situ data, computing resources, algorithm development space and the fundamental processing software required to extract temporal and spatial information from Big Data, C-TEP provides a dedicated service for the observation and monitoring of our coastal environment and society. Integration of satellite EO data, in-situ sensor data and model predictions shall provide an effective means of analysing and understanding the many linked coastal processes across a wide range of space and time scales. |
| Commercial Operator Identity Hub (COIH): Identity as a Service for the Network of EO Resources | In the context of Space 4.0 and its “EO Innovation Europe” concept, the European Space Agency (ESA) is forming a new ecosystem for exploitation of EO data under the name “Network of EO Resources”. The main goal is to bring the numerous and [...] | DEIMOS SPACE S.L.U (ES) | Digital Platform Services | platforms | In the context of Space 4.0 and its “EO Innovation Europe” concept, the European Space Agency (ESA) is forming a new ecosystem for exploitation of EO data under the name “Network of EO Resources”. The main goal is to bring the numerous and largely disparate EO datasets into a federated layer of exploitation platforms and enable the End-Users to perform research directly where the data is stored. Thus, the current paradigm “bring the data to the user” (users having to download enormous datasets to their premises and own massive infrastructures to process that data) will be replaced with the “bring the user to the data” paradigm, as the exploitation platforms will not only provide the raw data, but also a computing framework with specific tools and algorithms relevant to Earth Sciences. Federated Authentication and Authorization Infrastructure (AAI) is one of the key building blocks of this new ecosystem, aimed at providing a Single Sign On (SSO) experience for the users of the Network of EO Resources. In this context, the Agency has run several Pathfinder activities with the aim to align the Federation approaches among the various players in the Earth Observation domain and ensure these approaches are in-line with the AARC Blueprint Architecture and the technical practises in EduGain. To ensure the most cohesive operation of the Network of EO Resources, a centralised “IDaaS” (Identity as a Service) has been identified as the most suitable Identity and Access Management model, which is the subject of this service contract. The European Association of Remote Sensing Companies (EARSC) has been chosen by ESA to act as the Data Controller and Statutory Body for governing the IDaaS services resulting from this contract. The operational context of these services is a pure Business to Business (B2B) environment with no general public involved. The actors of this B2B environment are EARSC and the COIH service provider on one side, and commercial companies involved in the Earth Observation business on the other side. |
| COMMUNITY EARTH OBSERVATION INTELLIGENCE SERVICE: PROTOTYPING FOR SCALE | At present NGOs/CSOs have limited expertise in accessing and utilizing EO data. This project is working with NGOs adressinghuman rights concerns and will develop methodologies for integrating in-situ (citizen data collection), drone and EO data [...] | OMANOS ANALYTICS (GB) | Digital Platform Services | permanently open call, platforms, sustainable development | At present NGOs/CSOs have limited expertise in accessing and utilizing EO data. This project is working with NGOs adressinghuman rights concerns and will develop methodologies for integrating in-situ (citizen data collection), drone and EO data to enhance the collection of information and evidence on activities affecting human rights in developing countries |
| ConsIstent Retrieval of Cloud Aerosol Surface | CIRCAS aims at providing a set of atmospheric (cloud and aerosol) and surface (albedo) products derived from S3A/SLSTR observations retrieved using the same radiative transfer physics and assumptions.The retrieval is based on the CISAR (Combined [...] | RAYFERENCE SPRL (BE) | Science | atmosphere, science | CIRCAS aims at providing a set of atmospheric (cloud and aerosol) and surface (albedo) products derived from S3A/SLSTR observations retrieved using the same radiative transfer physics and assumptions.The retrieval is based on the CISAR (Combined Inversion of Surface and Atmosphere pRoperties) algorithm. CISAR is an advanced mathematical method developed by Rayference for the joint retrieval of surface reflectance and atmospheric (cloud and aerosols) properties from observations acquired by space-based imagers.The CISAR algorithm relies on the FASTRE radiative transfer model that describes surface reflectance and atmospheric absorption/scattering processes. The lowest level represents the surface. The lower layer hosts the aerosols. Molecular scattering and absorption are also taking place in that layer which is radiatively coupled with the surface for both the single and the multiple scattering. The upper layer is only subject to molecular absorption.The inversion of the FASTRE model within the CISAR algorithm against satellite observations provides accurate estimates of the surface reflectance field, aerosol or cloud optical thickness and single scattering properties in each processed spectral band. An estimate of the retrieval uncertainty is also provided.As the proposed method retrieved both cloud and aerosol properties with the same retrieval algorithm, no cloud mask is needed to perform the retrieval. Additionally, the same algorithm can be applied over any type of surfaces, including dark or bright surfaces or water bodies. Contributions: The CIRCAS project has been presented in the following conferences and workshops: Marta Luffarelli, Yves Govaerts, Carsten Brockmann, Grit Kirches, Thomas Storm, Simon Pinnock,Towards a consistent retrieval of cloud/aerosol single scattering properties and surface reflectance, The Fifth Sentinel-3 Validation Team Meeting 2019, 7-9 May 2019 – ESA/ESRIN, Frascati, Italy Luffarelli M. , Govaerts Y., Pinat E., Kirches G., Storm T., Pinnock S., Towards a consistent retrieval of cloud/aerosol single scattering properties and surface reflectance, Living Planet Symposium 2019, A1.05: Aerosols and Clouds, 13-17 May 2019, Milan, Italy, April 2019 Marta Luffarelli, Yves Govaerts and Sotiris Sotiriadis,Towards a consistent retrieval of cloud/aerosol single scattering properties and surface reflectance , 7th AeroSAT workshop September 23 – 28, 2019, BSC, Barcelona, Spain Marta Luffarelli, Yves Govaerts, Sotiris Sotiriadis, Carsten Brockmann, Grit Kirches, Thomas Storm, Simon Pinnock, Towards a consistent retrieval of cloud/aerosol single scattering properties and surface reflectance, EGU General Assembly 2020, 6 May 2020 Marta Luffarelli, Yves Govaerts, Carsten Brockmann, Grit Kirches, Thomas Storm, Towards a consistent retrieval of cloud/aerosol single scattering properties and surface reflectance, The 6th Sentinel-3 Validation Team Meeting, 15 December 2020 |
| CONSTRACK – Remote construction site monitoring | Usually, construction projects are structured through different phases: analysis, planning, design, construction, closing and post monitoring. The project execution phase (Phase 2 – Construction) is usually the longest phase in the project [...] | STARLAB BARCELONA SL (ES) | Enterprise | permanently open call, urban | Usually, construction projects are structured through different phases: analysis, planning, design, construction, closing and post monitoring. The project execution phase (Phase 2 – Construction) is usually the longest phase in the project life cycle and it typically consumes the most energy and the most resources. Global construction companies cannot be physically present all along the execution phase to control the implementation of the construction on-site. Then, they are used to control advancement only from local contact reporting that may differ from the exact reality of the project status, and usually have high expenses in travelling around the different project sites to get frequent updates. So, monitoring this phase is crucial to prevent from financial, timing and quality risks. Construction companies are then actively looking after monitoring remotely those construction sites to limit their presence on site and frequently get an unbiased vision of the project status. The difficulty in applying automated techniques based on EO data to this market is the high degree of variability of features and processes to be detected and monitored. This project addresses this issue by concentrating on automated detection of anomalies and involving the construction companies to translate the anomalies into actual engineering information. The project is operating as a series of test cases to determine the viability of an eventual commercial market. |
| CONTINENTAL DEMONSTRATOR LUISA: LAND USE INTENSITYS POTENTIAL, VULNERABILITY AND RESILIENCE FOR SUSTAINABLE AGRICULTURE IN AFRICA | Over Africa, land use intensification is a subject of particular research interest. The African land system is undergoing rapid changes and novel approaches are needed to understand the drivers and consequences of land use intensification, as [...] | UNIVERSITY OF TWENTE (NL) | Applications | africa, agriculture, climate, Continental Demonstrator, EO Africa, sustainable development | Over Africa, land use intensification is a subject of particular research interest. The African land system is undergoing rapid changes and novel approaches are needed to understand the drivers and consequences of land use intensification, as well as the dependency, vulnerability and resilience caused by climate change. It is paramount to understand Africa’s potential, vulnerability and resilience for a sustainable agriculture, defined as one that is low-carbon, resource-efficient, and socially inclusive.The primary objective of this activity is to develop and implement new methods, effectively linking and integrating modelling, satellite EO products (Sentinels, Explorers, Meteo missions, ESA-CCI) and dataset with in-situ, stakeholder-generated, social-economic data to advance the estimation of continental Africa potential, vulnerability and resilience for a sustainable agriculture. |
| Contribution of Swarm data to the prompt detection of Tsunamis and other natural hazards (COSTO) | The main objective of COSTO (Contribution of Swarm data to the prompt detection of Tsunamis and other natural hazards) project is to better characterize, understand and discover coupling processes and interactions between the [...] | UNIVERSITY OF WARMIA AND MAZURY IN (PL) | Science | ionosphere and magnetosphere, science, solid earth | The main objective of COSTO (Contribution of Swarm data to the prompt detection of Tsunamis and other natural hazards) project is to better characterize, understand and discover coupling processes and interactions between the ionosphere/magnetosphere, the lower atmosphere and the Earth’s surface and sea level vertical displacements. Natural Hazards induced by tsunamis, earthquakes and volcano eruptions occurring mostly around the areas with large human population have caused tragedies resulting in death of many people during and after these violent events, as well as inevitable environmental devastation. The proposed research effort targets to tsunamis that are the result of earthquakes, volcano eruptions or landslides. An early warning for tsunami occurrence, and especially an estimation of the amplitude of a tsunami is still a challenge. In the range approximately between 5 and 15 minutes, the waves generated at the sea surface associated with tsunami can reach ionospheric altitudes, creating measurable fluctuations in the ionospheric plasma and consequently in Total Electron Content (TEC). At an altitude of about 300 km, the neutral atmosphere is strongly coupled with the ionospheric plasma producing perturbations in the electron density (ED). These perturbations are visible in the TEC parameter calculated from the data acquired from dual-frequency GNSS receivers, as well as in the ionograms and resulting ED profiles. The COSTO project team will exploit existing modelling techniques for the identification and tracking of Travelling Ionospheric Disturbances (TIDs). Our methods are based on data assimilation methods using empirical models as background. These models based primarily on GNSS and ionosonde networks observations provide maps either of the TEC or of the ED at various altitudes. The less dense is the observing network, the highest is the uncertainty, which is the case over the oceans. The ionospheric-based tsunami detection method is much more accurate when based on the availability of dense networks of GNSS receivers and/or ionospheric sounders. These networks are sufficiently dense in the land, but there is a sparsity of observation points over the oceans. We believe that the use of Swarm data can shall improve the detection capability, especially over the oceans where the tsunami occurrence is expected. Therefore, TEC and ED models will be upgraded with the ingestion of dual-frequency onboard GNSS and Langmuir probe (LP) data from Swarm satellites, and advanced value-added products for tsunami early detection will be proposed. In the COSTO project, we will attempt to assimilate Swarm in situ LP ED data and TEC data into ED maps calculated from the 3D-TaD model at various heights. Ingesting in situ ED data from Swarm in the grids of TEC and ED, as well as taking into account the topside slant electron content observations from the POD GNSS antenna, will provide significant improvement in the temporal and spatial resolution of the ionospheric maps. Therefore, we expect to be able to specify more accurately the characteristics of TIDs triggered by the tsunamis. This is one of the main targets of the project: to ingest the Swarm ionospheric measurements in an evolved version of different algorithms developed by authors of this proposal to detect Medium-Scale TIDs (MSTIDs) related with tsunamis. We will also try to identify the typology of tsunamis that give rise of effects on the ionosphere, and those that do not and focus on different coupling processes and interactions between the ionosphere/magnetosphere and the lower atmosphere. |
| CORRIDOR AND ASSET MONITORING USING EARTH OBSERVATION – CAMEO | CAMEO aims to boost the understanding and integration of satellite Earth Observation (EO) services by companies and agencies managing pipeline and energy transmission corridors, including underground electricity cables. This will be achieved by [...] | Science [&] Technology Norway (NO) | Enterprise | energy and natural resources, enterprise, environmental impacts, generic platform service, infrastructure, security | CAMEO aims to boost the understanding and integration of satellite Earth Observation (EO) services by companies and agencies managing pipeline and energy transmission corridors, including underground electricity cables. This will be achieved by demonstrating the benefits of the EO based services in collaboration with asset managers and in-sector providers that do not traditionally use EO services. CAMEO will complete demonstrations where EO data is combined with traditional on-ground data and cutting-edge data processing and analytics techniques enabling improved monitoring insights. The two-year project is part of ESA’s “Expand Demand” initiatives with a focus on the Security sector. Natural gas pipeline network in Europe (Source: European Parliament) CAMEO OBJECTIVES Show the added value of EO data to stakeholders in the corridor & asset monitoring domain. This will be addressed by gaining a deep understanding of the information needed by the end users and their working processes, and subsequently showcasing information services to The demonstration services will cover a diversity of environments in which the stakeholders operate, with three broad categories of services: Structural integrity (e.g. surface deformation, leak occurrence) Environmental and geo-hazards (e.g. flooding, wildfire, landslides, vegetation change) Threat assessment (e.g. third-party interference, encroachment) Implement the services using a “virtual platform” concept, where distributed sources of EO and non-EO data are integrated regardless of where geospatial data is hosted. EO service providers implement services in scalable cloud computing environments with information products combined with other data sources to deliver information to users. In-sector providers or end-users may process the information provided using their own algorithms thus turning the data into information with operational value. The In-sector providers play a crucial role in the solution as they can translate the end-user priorities and requirements and utilize the EO-based services. CO-DESIGN APPROACH WITH STAKEHOLDERS Successful implementation of CAMEO requires participation of stakeholders and end users in the corridor & asset monitoring domain in all stages of the project. Stakeholders : Gasunie Pembina Innogy Enbridge Full details in the CAMEO project flyer. |
| CORTEX | In the frame of the CORTEX project, AGENIUM Space develops a set of solutions to simplify high performance Deep Neural Networks to make possible AI analysis on-board. AGENIUM Space reduces networks complexity and optimize DNN execution in [...] | AGENIUM SPACE (FR) | AI4EO | AI4EO | In the frame of the CORTEX project, AGENIUM Space develops a set of solutions to simplify high performance Deep Neural Networks to make possible AI analysis on-board. AGENIUM Space reduces networks complexity and optimize DNN execution in on-board hardware (SoC FPGA). The company evaluates different solutions to prepare on-board analysis before launch, as training models with very limited data sets (frugal networks) as well as to monitor model trustworthy, in particular for hyperspectral missions. Multiple applications require on-board high-performance data analysis provided by Deep Learning Networks. Nevertheless, without AGENIUM Space simplification and porting, that AI-based analysis cannot be executed in on-board hardware. Satellite operators will use AGENIUM Space solutions for Deep Learning at the edge to speed up information delivery to their customers without latency of on-ground processing. Extracting target information on-board avoids downlinking useless data and reduces the data volume to transfer, decreasing mission costs. Satellite manufacturers need on-board processing to increase platform capacity as the storage memory is only occupied by data considered as “interesting” after AI analysis. Hardware manufacturers need to provide to their Space clients with hardware plus software solutions including DNN analysis on-board. All of them impose strong requirements in terms of power consumption but also in analysis reliability and tight deadlines for mission preparation. Except for constellations composed by a unique repeated platform, the customers need a solution for training DNN with very reduced datasets. This project aims to reduce DNN complexity by models distillation and quantization with the aim of execute model inference in the reduced resources of the on-board hardware while preserving the original accuracy of the models. Simplified models are ported and optimized for some specific hardware architectures present on-board (Xilinx SoC FPGA). AGENIUM Space simplification workflow is generic, can be applied to different DNN architectures suitable for our clients. It brings high level of model simplification in terms of size and complexity reduction while maintaining roughly initial model performances (precision, accuracy). |
| COVID-19 economic impact assessment from Space in Italian Ports and Logistic Centers – Enabling Industry Growth | Starting from the end of 2019, the virus spread all over the world began a pandemic that has led governments to enforce restrictions aimed at ensuring social distancing and, thus, decreasing Covid-19 spread. Italy has been the first country in [...] | E-GEOS (IT) | Enterprise | covid19, open call, ports, security | Starting from the end of 2019, the virus spread all over the world began a pandemic that has led governments to enforce restrictions aimed at ensuring social distancing and, thus, decreasing Covid-19 spread. Italy has been the first country in Europe to be heavily impacted by this pandemic and to impose such restrictions. These restrictions have directly affected certain production activities but have also reduced people’s mobility and, thus, changed people’s habits, leading to an indirect effect on the Italian economy. These considerations suggest that there is a direct negative effect of Covid-19 restrictions on the Italian economy, but also a more complex indirect effect due to people’s changing purchasing behavior. Based on this observation, the objective of this project is the development of a methodology that allows for the creation of indicators able to describe impact of the COVID-19 restrictions on the Italian economy using space data on representative Italian zone. In particular the test have conducted on two large Italian ports, Genoa (Liguria) and Gioia Tauro (Calabria), characterized by a balanced mix of the main lines of business of ports. Our empirical analyses confirm that port activity has a mediation effect on Covid-19 restrictions’ impact on the Italian economy. Intuitively, changing people’s habits may negatively affect certain industries, but may also a have a positive effect on other industries providing the goods and services that have become more important to people’s lives, such as home appliances and accessories, food, furniture, and home office supplies. Port activity reflects these changes and represents a construct that can help model the economic impact of Covid-19 restrictions. To study port activity, the team leveraged huge time series of data need to be analyzed in order to extract meaningful information related with pollution, night light, ships in port, car traffic, people movement, material stocks. The extracted data are then correlated with economic data of the area of interest, in order to understand how it is possible to translate satellite information in economic information useful for insurances and governments. Within this project, AI techniques are used to detection ad segment objects in satellite images and to create the predictive model able to find new correlations in the data. The Team complemented these data with other sources of data, including traffic and mobility data, as well official sources of information on port economics and on the more general trends of the Italian economy. Finally to provide all result to decision-makers; the project provide the integration of the output of existing services in a dashboard. In this manner, the user can create personalized reports and graph regarding the areas of interest the variation in time of the developed indicators. The creation of a simple and interactive dashboard allows the users to visualize, through a user-friendly web interface, the information extracted from the satellite and mobile data, to further analyze and export data for broader comparative analyses. This simplify the comparison between data from different periods and the monitoring of the changes over time of the indicators, thus it represents a tool that could be useful also in the post-emergency period. |
| CRITE: Coffee Rehabilitation in Timor-Leste | This activity is a follow-up to a successful activation of the ESA EO Clinic offering support to to ADB’s Timor-Leste Resident Mission (ADB project “Preparation of a National Coffee Sector Development Plan for Timor-Leste”). Following the [...] | Planetek Italia (IT) | Sustainable Development | agriculture, forestry, sustainable development | This activity is a follow-up to a successful activation of the ESA EO Clinic offering support to to ADB’s Timor-Leste Resident Mission (ADB project “Preparation of a National Coffee Sector Development Plan for Timor-Leste”). Following the promising first results of the feasibility study in using EO to characterise past and current coffee-growing practices, the main project activities include the definition, implementation and application at large scale of innovative methods to optical and SAR remote sensing data for coffee crop mapping and monitoring in Timor-Leste where most of the coffee plantations grow under a shade tree system. Planetek Italia continues the work with local stakeholders, including a more detailed assessment of the methodology. A dedicated mission to Timor-Leste took place for collection of in-situ validation data and capacity building. A prototype coffee plantation map is ready, based Sentinel-1/2 and an updated classification methodology which combines Machine Learning and Deep Learning Classifiers, integrating the information available about the shadow tree species, obtained in the field. First qualitative validation shows a higher performance of this methodology with respect to the first mapping done in the EO Clinic project. ADB contributes to this activity with logistics support to the validation exercise and capacity building support. |
| Crowds and Machines | The aim of the project is to develop a demonstrator “Crowds & Machines” (C&M) that provides strategic information concerning the impact of Covid-19 on food security and political (in)stability. Crowds & Machines enables decision [...] | BLACKSHORE B.V. (NL) | AI4EO | AI4EO, covid19 | The aim of the project is to develop a demonstrator “Crowds & Machines” (C&M) that provides strategic information concerning the impact of Covid-19 on food security and political (in)stability. Crowds & Machines enables decision makers to track the impact of Covid-19, design scenarios and act on those scenarios effectively. If successful, Crowds & Machines will assist governments, IGOs and international businesses during the outbreak of Covid-19 and prepare for the period when Covid-19 has been diminished. Crowds & Machines enhances and deploys BlackShore’s crowdsourcing platform Cerberus combined with machine learning to measure the impact of Covid-19 on food security and political stability. Specifically, Cerberus uses the power of the crowd (i.e. thousands of gamers) and serious game technologies to analyze satellite imagery. The results of the crowd consist of a training dataset that will be used as input for the machine learning system of 52impact to train the algorithms to classify different types of crops automatically and predict yields, which is essential to assess food security. The satellite-based output will be combined with economic data to provide a holistic perspective on food security and political stability. The target users of the Crowds and Machines demonstrator are policy and decision makers in Europe seeking evidence-based data and predictive tools to support their policy and/or program planning and operations. The value that we provide to customers with C&M is strategic information concerning the impact of Covid-19 on food security and political (in)stability. The strategic information enables decision makers to track the impact of Covid-19, design scenarios and act on those scenarios effectively. Crowds & Machines is designed to develop advanced machine learning, early warning and causal discovery tools that provide the following services: Identify and map crop development, yields, and harvesting using gaming techniques; Assess the medium to longer term impacts of Covid-19 thereon; Mobilize local and regional community expertise for validation of information; Support the design of adequate and effective policy response mechanisms. |
| CROWDVAL: Using Crowdsourcing and Innovative Approaches to Evaluate and Validate ESA’s Land Cover Products | The CrowdVal project had five main objectives: Develop new innovative sampling schemes that allow a stratification and bias removal via road networks and that take other constraints into account for in-situ data collection; Enhance [...] | INTERNATIONAL INSTITUTE FOR APPLIED (AT) | Applications | land cover, permanently open call | The CrowdVal project had five main objectives: Develop new innovative sampling schemes that allow a stratification and bias removal via road networks and that take other constraints into account for in-situ data collection; Enhance LACO-Wiki and LACO-Wiki Mobile with the new sampling strategies, functionality for opportunistic map evaluation on the ground, and the addition of auxiliary data sets including Flickr geo-tagged pictures and time series of NDVI; Create an open source version of LACO-Wiki Mobile; Demonstrate the enhanced tools through crowdsourcing data collection campaigns (online and in-situ) to validate the first land cover map of Africa at a 20m spatial resolution; and Investigate the possibility of developing a business model around an open source version of LACO-Wiki Mobile with a payment model around access to enhanced features, e.g. additional data sources, commercial satellite imagery, increased sample size, etc. |
| CryoSat Plus For Oceans (CP4O) | The “CryoSat Plus for Oceans” (CP4O) project, supported by the ESA Support to Science Element (STSE) Programme and by CNES, was dedicated to the exploitation of CryoSat-2 data over the open and coastal ocean. The general objectives of the CP4O [...] | SATELLITE OCEANOGRAPHIC CONSULTANTS LTD. (GB) | Science | altimeter, coastal zone, oceans, polar science cluster, SAR, SARin, science | The “CryoSat Plus for Oceans” (CP4O) project, supported by the ESA Support to Science Element (STSE) Programme and by CNES, was dedicated to the exploitation of CryoSat-2 data over the open and coastal ocean. The general objectives of the CP4O project were: To build a sound scientific basis for new oceanographic applications of CryoSat-2 data; to generate and evaluate new methods and products that will enable the full exploitation of the capabilities of the CryoSat-2 SIRAL altimeter, and to ensure that the scientific return of the CryoSat-2 mission is maximised. However, whilst the results from CP4O were highly promising and confirmed the potential of SAR altimetry to support new scientific and operational oceanographic applications, it was also apparent that further work was needed in some key areas to fully realise the original project objectives. Thus, after the end of the Project in 2015, additional work in four areas has been supported by ESA under a first Contract Change Notice (CCN): Developments in SARin data processing for Coastal Altimetry. Implementation of a Regional Tidal Atlas for the Arctic Ocean. Improvements to the SAMOSA retracker: Implementation and Evaluation & Optimised Thermal Noise Estimation. Extended evaluation of CryoSat-2 SAR data for Coastal Applications. This CCN ended in 2016 and was followed by a second Contract Change Notice, currently on-going, on the improvement of the arctic ocean bathymetry and regional tidal atlas. A detailed description of the specific objectives under each of the four sub-themes (Open Ocean Altimetry, Polar Ocean Altimetry, Coastal Zone Altimetry & Sea-Floor Altimetry) can be found at http://www.satoc.eu/projects/CP4O/ |
| CryoSat-2 for enhanced sea-ice thickness and ocean observations in Antarctica: “CryoSat+ Antarctic Ocean” | Why has Antarctic sea ice experienced a small increase in extent over the past decades in stark contrast to the rapid decline observed in the Arctic? What role are the Southern Ocean and sea ice playing in controlling the Deep Water formation [...] | MULLARD SPACE SCIENCE LABORATORY-UNIVERSITY COLLEGE LONDON (GB) | Science | Antarctica, oceans, polar science cluster, science, snow and ice | Why has Antarctic sea ice experienced a small increase in extent over the past decades in stark contrast to the rapid decline observed in the Arctic? What role are the Southern Ocean and sea ice playing in controlling the Deep Water formation and thermohaline circulation and the melting of the Antarctic ice shelves and sea level rise? Only satellite remote sensing can provide the pan-Antarctic view required to fully understand these changes to the Southern Hemisphere’s sea ice and ocean fields in response to anthropogenic warming. Over the last 8 years CryoSat-2 (CS2) has allowed a radically new view of the ice covered Arctic Ocean, providing us with the first pan-Arctic sea ice thickness maps, dynamic topography and geostrophic currents, and indirectly a wealth of geophysical products ranging from Eddy kinetic energy (EKE), Ekman upwelling / downwelling, to snow on sea ice, and improved tidal models, or better resolved bathymetry at the bottom ocean. In Antarctica similar products have emerged but remain at a lower level of maturity. Specific challenges in the processing of the radar signal result from the complex surface characteristics of the ice covered Southern Ocean such as the sea ice flooding from snow loading or the highly fragmented and divergent marginal ice zone like nature of the sea ice cover. In addition, validation of sea ice and ocean products is hindered by the observational gap of in-situ and airborne data in the Southern Hemisphere. The overarching objective of this project is to address these issues by developing new approaches and algorithms that could be implemented in ESA’s CryoSat-2 ground segment processor to produce state of the art sea ice and ocean products that will be validated against a comprehensive dataset of airborne and in-situ measurements and result in scientific progress for our understanding of the Antarctic Climate system and ocean circulation. The main objectives of this project are: Perform a thorough review of the scientific and technical challenges Survey, collect and document all relevant data sets needed for the successful development of novel, observational and model-based snow thickness products. Develop, inter-compare and validate multiple approaches to sea surface height and sea ice thickness retrieval on Antarctic sea ice. Specific approaches to be considered are: Novel LRM/SAR/SARIN methods for leads, polynyas, open ocean and sea ice classification Along-track processors over leads, polynyas and open ocean for sea surface estimation Along-track processors over sea ice floes for sea ice thickness estimation Pan-Antarctic gridded products of dynamic ocean topography and geostrophic currents Pan-Antarctic gridded products of sea ice thickness Preliminary inter-comparison of along-track and gridded products developed in steps b-e Validation over selected tracks and key regions against in-situ and airborne data. Implement the algorithms developed above and assess their impact and usefulness in addressing the identified scientific challenges. Build a scientific roadmap for future development and evolution of knowledge about the snow layer on Arctic sea ice. The main outputs of the project will be: An Experimental Dataset and accompanying User Manual Algorithm description documents Validation reports An Impact Assessment A scientific Roadmap The biggest challenges the project faces are the difficulties in validating data products against sparse or preferentially sampled, in-situ data, and in proving that a new method is measurably better than an existing method when applied to inherently noisy data. |
| CryoSat+ Mountain Glaciers | The purpose of this project is to quantify the volume, mass change and contribution to sea level change of mountain glaciers using dataset from the CryoSat satellite radar altimeter. Here we propose to generate mountain glacier elevation and [...] | UNIVERSITY OF EDINBURGH (GB) | Science | CryoSat, cryosphere, polar science cluster, science | The purpose of this project is to quantify the volume, mass change and contribution to sea level change of mountain glaciers using dataset from the CryoSat satellite radar altimeter. Here we propose to generate mountain glacier elevation and elevation change by (i) evaluating the ability of the current CryoSat products, (ii) investigating and implementing processing strategies such as FBR filtering, novel retracking, swath processing, in order to improve the current CryoSat products, (iii) validating elevations and quantifying their errors. The resulting elevation and elevation change will be used to generate estimates of glacier volume and mass change and determine mountain glacier’s contribution to sea level change during the life period of CryoSat. We will integrate our results with existing studies of glaciers change to build a spatial and temporal picture of changes affecting mountain glaciers that will be advertise via scientific presentation and submission as journals articles. Our world is losing ice at record rate Glaciers All Over the World Are Shrinking Fast—See for Yourself Global ice loss accelerating at record rate, study finds |
| CryoSMOS | In recent years the possibility of using L-band space-borne radiometers for monitoring the Cryosphere has been investigated using data available from new space missions ((ESA SMOS and NASA Aquarius and SMAP). The interest in L-band relies on the [...] | IFAC-CNR ISTITUTO DI FISICA APPLICATA ” NELLO CARRARA” (IT) | Science | cryosphere, science, SMOS, snow and ice | In recent years the possibility of using L-band space-borne radiometers for monitoring the Cryosphere has been investigated using data available from new space missions ((ESA SMOS and NASA Aquarius and SMAP). The interest in L-band relies on the very low absorption of ice at L-band and the low scattering by particles that are very small compared to the wavelength. As a consequence, in dry snow and ice the extinction is low and the penetration depth is very high, which open new opportunities to probe the soil or water under the ice, or the internal layers of the ice-sheet. The CryoSMOS project, which was funded by ESA as Support To Science Elements (STSE), aims at investigating this topic by testing the capabilities of SMOS in the monitoring of Antarctica ice sheet and ice shelves. SMOS data were first in-depth analyzed and it has been observed that Tb can show temporal dynamic trends in the ice shelves and near to the coast where the snow could be wet, while it is more stable in time, but presents significant spatial features in the inner parts of the continent. Moreover, small but significant Tb temporal variations are observed also in the internal part at H polarization. Four case studies, which are in-depth analyzed within the project, have been considered: the estimate of the temperature profile of the ice sheet; the capability of investigating bedrock topography; the study of the ice shelves stability ; the monitoring of wet snow. For each study case the SMOS data have been first interpreted by using different microwave emission models which use as inputs data collected on the ground, when available, or from glaciological models. Simulated and measured Tb is in general in good agreement confirming that most of the observed Tb spatial and temporal signatures can be theoretically explained. Model analysis also shows that a better knowledge of dielectric permittivity of ice (especially of its imaginary part which is indeed very small) is required to further improve the results. Starting from this, inversion algorithms have been developed in order to derive geophysical parameters from SMOS data. Main obtained results are: the retrieval of temperature profile of ice sheet for large portion of Antarctica where the ice-sheet is stable (i.e. velocity < 5 m/year) ; the monitoring of significant changes of ice shelf properties and the identification of their origin ( i.e. bottom or surface changes) and the study of its stability; the improvement of bedrock map in the area affected by large incertitude (i.e. > 500 m); the detection of melt events which can be used in combination to information derived from higher passive microwave sensors. SMOS derived products have been delivered and are free available at CATDS (https://www.catds.fr/Products/Available-products-from-CEC-SM/CryoSMOS-project) . Results will be better assessed and validated by additional data (when they will be available). Moreover, future activity should be devoted to the investigation of other regions (i.e. Greenland) and to better evaluate the use of new glaciological models which are able to improve retrieval algorithms. |
| CRYOSPHERE VIRTUAL LABORATORY | Despite considerable research progress in understanding the polar region over the last decades, many gaps remain in observational capabilities and scientific knowledge. These gaps limit present ability to understand and interpret on-going [...] | NORCE Norwegian Research Centre AS (NO) | Science | cryosphere, polar science cluster, science | Despite considerable research progress in understanding the polar region over the last decades, many gaps remain in observational capabilities and scientific knowledge. These gaps limit present ability to understand and interpret on-going processes, prediction capabilities and forecasting in the Arctic region, thereby hampering evidence-based decision-making. Addressing these gaps represents a key priority in order to establish a solid scientific basis for understanding earth science processes in the Polar Regions. The Cryosphere Virtual Lab aims at supporting the cryosphere scientific community to address those gaps promoting an Open Science approach, where sharing of data (e.g., EO satellite, in-situ, airborne, ancillary, high level products), knowledge, tools and results is at the center of the science process. Since more than 20 years, “Earth Observation” (EO) satellites developed or operated by ESA and other satellite operators are providing a wealth of data. The Sentinel missions, along with the Copernicus Contributing Missions, Earth Explorers and many other missions provide routine monitoring of our environment at the global scale, thereby delivering an unprecedented amount of data. This expanding operational capability of global monitoring from space, combined with data from long-term EO archive (e.g. ERS, Envisat, Landsat etc.), in-situ networks and models provide scientists with unprecedented insight into how our oceans, atmosphere, land and ice operate and interact as part of an interconnected Earth System. While the availability of the growing volume of environmental data from space represents a unique opportunity for science, general R&D, and applications, it also poses a major challenge to achieve its full potential in terms of efficiently accessing and combining the different datasets (EO data, airborne, in-situ…) and sharing scientific knowledge, tools and results in order to speed up the scientific process. Firstly, because the emergence of large volumes of data raises new issues in terms of discovery, access, exploitation, and visualization, with implications on how scientists do “data-intensive” Earth Science. Secondly, because the inherent growing diversity and complexity of data and users, whereby different communities – having different needs, methods, languages and protocols – need to cooperate and share knowledge to make sense of a wealth of data of different nature (e.g. EO, in-situ, model), structure, format and error budgets and speed up the scientific development process. Responding to these technological and community challenges requires the development of new ways of working, capitalizing on Information and Communication Technology (ICT) developments to facilitate the exploitation, analysis, sharing, mining and visualization of massive EO data sets and high-level products within Europe and beyond following an Open Science approach. Evolution in information technology provide new opportunities to provide more significant support to EO data exploitation within the Open Science paradigm. In this context, new ITC developments and the concept of Virtual laboratories make scientific networking, on-line collaboration, sharing of data, tools and knowledge among scientific communities not only possible, but also mainstream. The Cryosphere Virtual Laboratory (CVL) will become a community open science tool, where EO satellite data and derived products can be accessed, visualised, processed, shared and validated. In order to achieve this objective, the CVL shall provide access and facilitate sharing of relevant space and non-space data (aerial, UAV, coastal radar, in-situ etc.). Following an Open Science approach, the CVL shall mainly be designed to support scientist to access and share EO data, high-level products, in-situ data, and open source code (algorithms, models) to carry out scientific studies and projects, sharing results, knowledge and resources. The Cryosphere Virtual Laboratory will form part of an ecosystem of thematic laboratories capitalizing on ICT technologies to maximize the scientific exploitation of EO satellite data from past and future missions. |
| CTEO – CryptoTradeable EO | EO derived information are increasingly being used as the basis for a range of sensitive decisions linked to commercial operations, public safety and environmental security. At the same time, developments in ICT capability enable an expanded [...] | Planetek Italia (IT) | Enterprise | blockchain, permanently open call, platforms, security | EO derived information are increasingly being used as the basis for a range of sensitive decisions linked to commercial operations, public safety and environmental security. At the same time, developments in ICT capability enable an expanded volume of information to be generated using distributed approaches such as cloud based storage and processing and platform based interactions, use of algorithms and proprietary datasets. This makes guaranteeing the integrity of both the data and the derived information more and more difficult. This project is testing various Blockchain based approaches to support the different verification elements needed to guarantee the integrity of the data and the analysis. In particular, this project is investigating and testing approaches for dividing, encrypting and distributing large datasets (typical EO imagery) to a group of peers (e.g. in the ground segment and on-board) for enabling tradeable distributed processing, encrypting and distributing metadata in the peer-to-peer network, with guarantee of correct association to the related datasets, signing and uniquely identifying smart contracts (this may be also full-fledged algorithms) based on their input requirements and output products so that the P2P network can guarantee processing traceability and security and implementing a runtime environment suitable for running EO smart contracts, which is able to perform processing with specific execution time constraints, storage constraints, device usage constraints, network usage constraints, metrics constraints applied to output quality. |
| CUSTOMISED FOREST ASSESSMENT SERVICE FOR INSURANCE (CASSIA) | CASSIA’s objective is to develop forest value assessment and temporal forest change detection monitoring service for insurances to detect e.g. storm and insect damages and provide damage evaluation and verification. Based on synergistic use of [...] | REACH-U (EE) | Applications | applications, forestry, Sentinel-1, Sentinel-2 | CASSIA’s objective is to develop forest value assessment and temporal forest change detection monitoring service for insurances to detect e.g. storm and insect damages and provide damage evaluation and verification. Based on synergistic use of Sentinel-1 and -2 monitoring capabilities an early assessment of regional forest loss and related damage probability maps will be generated and provided as web based service. |
| CYMS (Scaling-up Cyclone Monitoring Service with Sentinel-1) | CYMS is an ESA-funded project aiming at scaling up an operational service for Tropical Cyclone (TC) monitoring, in view of its potential integration as part of a Copernicus Service. The main scientific and technical objectives are to:Develop a [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Science | ocean science cluster, oceans, permanently open call, science, Sentinel-1, SMOS | CYMS is an ESA-funded project aiming at scaling up an operational service for Tropical Cyclone (TC) monitoring, in view of its potential integration as part of a Copernicus Service. The main scientific and technical objectives are to: Develop a sustainable acquisition strategy dedicated to TC ; Consolidate S-1 end-to-end processing chains for ocean surface wind field with dedicated and up-to-date algorithms for extreme events ; Build an archive center with homogeneous and consistent l2 products, for the TC product validation purpose and scientific applications ; Build a single integrated portal easing dissemination and outreach activities. |
| DACES – Detection of Anthropogenic CO2 Emissions Sources | The project aims at developing a new methodology for detecting anthropogenic carbon dioxide emission sources. CO2 data from OCO-2 and NO2, SO2 and CO data from Sentinel-5P are collocated. The plan is to analyze these data in synergy to better [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | atmosphere, atmosphere science cluster, carbon cycle, carbon science cluster, permanently open call, science, Sentinel-5P, TROPOMI | The project aims at developing a new methodology for detecting anthropogenic carbon dioxide emission sources. CO2 data from OCO-2 and NO2, SO2 and CO data from Sentinel-5P are collocated. The plan is to analyze these data in synergy to better detect anthropogenic CO2 sources and plumes. In detail OCO-2 XCO2 data is deseasonalized and detrended, and further correlated/clustered to the spatial distribution of other species such as NO2, SO2, CO. Further a direct detection of emission plumes is done for anthropogenic sources using NO2, SO2 and CO datasets, and collocating the plumes with XCO2 data. The corresponding CO2 enhancements and ratios between different species at local level is then calculated. The project has been kicked-off the 5th October. |
| DAS-Tool: Multispectral Data Analysis Toolbox for SNAP | Computer-based image analysis is essential to assist human understanding and semantic annotation of satellite images of the Earth’s surface. The technical objectives of this project were the elaboration and implementation of dedicated algorithms [...] | UNIVERSITY POLITEHNICA OF BUCHAREST (RO) | Enterprise | generic platform service, Sentinel-2 | Computer-based image analysis is essential to assist human understanding and semantic annotation of satellite images of the Earth’s surface. The technical objectives of this project were the elaboration and implementation of dedicated algorithms for Sentinel-2 data analysis. The project proposes an unitary data mining concept that uses advanced data visualisation and explainable features, together with specific graphical instruments to enhance relevant aspects of Sentinel-2 imagery and enable semantic analysis based on a two-stage process: Exploratory visual analysis, aiming to highlight predominant data features for the scene content and help the user perceive certain aspects that are not always reflected in the visible part of the spectrum, maximising the data impact on the human visual system to help image understanding and interpretation. The added value becomes important as the data content representation (the second functionality) will focus more on extracting numerical patterns rather than visual characteristics and the image analysis will provide similarity by data processing. Therefore, the results will not always correspond to the intuitive user perception on the scene. In order to correlate the classification map with its understanding and application, the user can exploit data visualisation to understand the computed correlations and modify the parameters for appropriate content representation. Data content representation, focussing on the identification of relevant spectral, texture, and physical parameters, scene-related features that are further included in a learning process modelling the data content according to statistical similarities. This step will result in a classification map emphasizing the existing categories of objects inside the scene. The analysis entails a compact workflow interconnecting feature extraction and feature classification to describe the Sentinel-2 data content characteristics. Designed to enhance the exploitation of Sentinel-2 data through fast image understanding and analysis, the concept was implemented as Sentinel-2 dedicated data analysis (DAS-Tool) plugin for the Sentinel Application Platform (SNAP) and deployed as an open-source tool empowering the Earth Observation (EO) community with fast and reliable results. Driven by the characteristics of Sentinel-2 data, the project aims at increasing the accuracy of traditional algorithms by combining processes that are fit to the image content. The plugin accommodates multiple solutions for each processing phase and enables flexibility in data exploration and multilevel analysis (locally – at pixel level, contextually – at patch level). The methodology reduces the semantic gap by revealing to the user the kind of patterns that are statistically similar through exploratory visual analysis. This will increase the relevance of the training samples and the accuracy given a specific application. You can find DAS-Tool on the SNAP Community Plugins page. See also the following publication: A.C. Grivei, I. Neagoe, F.A. Georgescu, A. Griparis, C. Vaduva, Z. Bartalis, M. Datcu, “Multispectral data analysis for semantic assessment – A SNAP framework for Sentinel 2 use case scenarios”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 13, pp. 4429 – 4442, 2020, DOI: 10.1109/JSTARS.2020.3013091. https://ieeexplore.ieee.org/document/9153144 Watch a presentation about DAS-Tool at the Phi-Week 2020 here. DAS-Tool Demo Videos: SNAP – Getting started with DAS-Tool. Installation and pixel based Sentinel-2 data analysis SNAP – Interactive Sentinel 2 data analysis with DAS-Tool (patch-based) The project was part of the ESA Romanian Industrial Incentive Scheme. |
| Datacube Demonstration for TPM | The service enables advanced data access and retrieval capabilities on global to local / low to very high resolution EO products, based on OGC WCS and WCPS APIs. The project implements a showcase for Landsat European coverage and validating he [...] | MEEO S.R.L. (IT) | Digital Platform Services | platforms | The service enables advanced data access and retrieval capabilities on global to local / low to very high resolution EO products, based on OGC WCS and WCPS APIs. The project implements a showcase for Landsat European coverage and validating he benefit via an Urban application over Eastern Austria. |
| DEEP EXTREMES | DEEP EXTREMES is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, and contributes to the ESA Extremes and Natural [...] | Leipzig University (DE) | AI4EO | AI4EO, AI4Science, Ecosystems, science | DEEP EXTREMES is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, and contributes to the ESA Extremes and Natural Disasters Science Cluster. The AI4SCIENCE ITT had 2 main objectives: Advancing Earth System Science: advancing our capacity to combine EO and AI to address a major scientific challenge: The observation, understanding and characterisation of multi-hazards, compound and cascade events and its impacts on society and ecosystems. Advancing Artificial Intelligence for EO: unlocking the full potential of Artificial Intelligence for Earth System Science with focus on two main AI challenges: physics-driven Artificial Intelligence and explainable AI. The DEEP EXTREMES project has a focus on compound heat and drought events at global scale, looking at detection based on long-term climate and land-surface data, combining EO archives and other observation data, with methods tailored to multivariate event detection. The principle is to start from sampling a subset of large events in Sentinel era and zooming into the events and in unaffected areas around the event with high-dimensional “mini cubes”. The activity then aims to train complementary deep-learning methods for prediction and understanding dynamics in such events, implement the tested and validated workflow in a cloud environment and developing it further based on community feedback. Science community engagement is planned via workshops and science discussions to further develop the proposed framework. Additional information and resources can be found at the project website https://rsc4earth.de/project/deepextremes/ RESULTS DeepExtremes/cv-groups-minicubes: v1.0.0 (Collection of Julia scripts to download DeepExtremes minicubes registry and split the dataset into cross-validation folds based on location). Cite as: Mélanie, Weynants, and Fabian Gans. ‘Deepextremes/cv-groups-minicubes: V1.0.0’. Zenodo, 21 December 2023. https://doi.org/10.5281/zenodo.10417312. |
| Deep Learning for Hyperspectral (BEETLES) | Hyperspectral imaging can capture hundreds of images acquired for narrow and continuous spectral bands across the electromagnetic spectrum, hence can allow us to precisely analyze the materials that are present in a scene of interest. [...] | KP Labs Sp. z o.o. (PL) | AI4EO | AI4EO, generic platform service, hyperspectral | Hyperspectral imaging can capture hundreds of images acquired for narrow and continuous spectral bands across the electromagnetic spectrum, hence can allow us to precisely analyze the materials that are present in a scene of interest. However, the large volume of hyperspectral images (HSIs) makes their manual analysis and transfer very costly and time-expensive, especially when they are acquired on-board imaging satellites. Therefore, deploying automated algorithms for the efficient HSI processing on-board satellites is an important scientific and engineering topic, and on-board artificial intelligence – employed both in the context of hyperspectral data reduction through band selection or feature extraction, and HSI analysis aiming at extracting the value from raw data – has a potential to speed up adoption of hyperspectral analysis in emerging use cases through bringing “the brain” just next to “the eye”. The objectives of BEETLES focuses on enabling effective adoption of deep learning in the field of remote sensing and hyperspectral image analysis, where – in most use cases – the availability of ground-truth hyperspectral data is extremely limited or non-existent. Thus, making deep learning algorithms ready-to-use on-board imaging satellites in hardware- and energy-constrained execution environments is of utmost importance. This activity allows to provide the evidence that the designed deep neural networks are applicable in real-life Earth observation use cases. Approaches were designed for quantitatively, qualitatively, and statistically proving their robustness against noise of various distributions that can reflect sensor failures or thermal noise. Finally, we can build better understanding of the underlying materials captured by HSIs through incorporating hyperspectral unmixing into the analysis pipeline. The algorithms and approaches developed in BEETLES are application-agnostic and can be effectively deployed in orbit and on the ground in a variety of applications. The missions that aim at benefiting from on-board machine and deep learning in Earth observation, space debris monitoring, risk management, deep space missions, and many more, would be the target of BEETLES. All algorithms were thoroughly verified using multi-fold analysis (quantitatively, qualitatively, and statistically) which helped us understand their operational and non-functional capabilities. The outcomes of the project were presented at the most important conferences in the field (IEEE IGARSS 2020, ɸ-week 2020, IAC 2020, OBPDC 2020) and papers published in top-tier journals. |
| DeepSent – Deep Learning-Based Multiple-Image Super-Resolution for Sentinel-2 Data | The aim of the activity is to apply super-resolution reconstruction multispectral Sentinel-2 images, using multiple images of the same region, captured at different points in time (MISR, multiple-image super-resolution). This is achieved by [...] | KP Labs Sp. z o.o. (PL) | Enterprise | AI4EO, permanently open call, Sentinel-2 | The aim of the activity is to apply super-resolution reconstruction multispectral Sentinel-2 images, using multiple images of the same region, captured at different points in time (MISR, multiple-image super-resolution). This is achieved by adapting recent deep neural networks that were recently proposed for dealing with MISR, to the particularities of Sentinel-2 data. In particular the project focusses on three aspects: adapting the existing networks to process multispectral images, proposing techniques for preparing the training data, and selecting and pre-processing the input low-resolution data. The existing networks are applied to super-resolve the Sentinel-2 images in a band-wise manner (each band treated independently), followed by exploiting the correlation among the multiple bands. The output contains a panchromatic image, as well as an RGB/multispectral image of higher resolution than the one presented at the input. Read about the project achievements in the following publications: 1. M. Kawulok, J. Nalepa, P. Benecki, D. Kostrzewa (2020): Deep learning for super-resolution reconstruction of Sentinel-2 images, Phi-Week 2020. 2. M. Kawulok, T. Tarasiewicz, J. Nalepa, D. Tyrna, D Kostrzewa (2021): Deep learning for multiple-image super-resolution of Sentinel-2 data, in Proc. IEEE IGARSS 2021, pp. 3885–3888. 3. J. Nalepa, K. Hrynczenko, and M. Kawulok (2021): Multiple-image super-resolution using deep learning and statistical features, in Proc. Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR). Springer, 2021, pp. 261–271. |
| Delay-Doppler Altimetry Studio | This project aims at providing to the scientific community the means to understand and use the low levels of Altimetry data and how these data are processed, by providing them with a Fully Adaptable and Configureable Delay Doppler [...] | ISARDSAT LTD. (GB) | Science | altimeter, applications | This project aims at providing to the scientific community the means to understand and use the low levels of Altimetry data and how these data are processed, by providing them with a Fully Adaptable and Configureable Delay Doppler Processor (DDP) and a friendly user interface (the Tool, to help them interacting with the DDP. The proposed DDP has different options from which the user will be able to choose in favour of their particular field of interest. The project also presents various (9) demonstrations of new features that can be investigated and retrieved when using these lower data processing levels. They are presented as successful cases tudies. |
| Demonstrator Precursor Digital Assistant Interface For Digital Twin Earth (DA4DTE) | There is a growing need for accurate and scalable techniques for satellite EO images understanding, search and retrieval from the massive archives (e.g., Copernicus archives) has appeared. However, in the era of big data, the semantic content of [...] | E-GEOS (IT) | AI4EO | There is a growing need for accurate and scalable techniques for satellite EO images understanding, search and retrieval from the massive archives (e.g., Copernicus archives) has appeared. However, in the era of big data, the semantic content of the satellite data is much more relevant than the keywords/tags. To keep up with the growing need of automatization, image search engines that extract and exploit the content of the satellite images are necessary, exploiting cutting-edge technologies and advances in Natural Language Processing (NLP), Machine Learning (ML) and Computer Vision (CV) applied to Earth Observation challenges (NLP4EO). In other words, the need is emerging of being able to go beyond the traditional query of EO data catalogues based on technical image metadata (location, time of acquisition, technical parameters) and enrich the semantic content of image catalogues enabling a brand new class of query possibilities powered by the combination of NLP (to understand the query and to describe the content of the data) and CV to massively annotate data and implement multi-modal text-to-image and image-to-image searches. Such search engines with ‘query by content’ functionalities are not existing yet neither within the DIAS platforms nor in other satellite EO data platforms. Moreover, the added value of a Digital Assistant capable to understand complex requests related to geospatial data searches could go well beyond the expansion of dimensions that we are able to use to query EO data archives and include also advanced capabilities to understand and process a User request, selecting the most suitable workflow to satisfy the request, being able to autonomously execute processing on EO and non EO data and, finally, answer the initial question posed by the User. In this scenario, the development of a precursor demonstrator of a Digital Assistant will adhere to the following high-level objectives: [OBJ-1] Explore innovative CV and NLP techniques for Content Based Image Retrieval (CBIR), taking into account both their level of maturity and the applicability to real EO Use Cases. [OBJ-2] Develop a prototype Digital Assistant exploiting the currently available capabilities in terms of massive processing of EO data for both the training of the “Content-based” Query Engines and for the implementation of the prototype Digital Assistant capable to let the Users interact with the EO data i.e., asking questions in natural language and starting a conversation with the Digital Assistant. [OBJ-3] Demonstrate the value of the Digital Assistant in real life EO Use Cases, to make sure that the demonstrator Digital Assistant can have a positive impact in the community of users [OBJ-4] Engage with the community of ML, NLP and CV, since the osmosis between different fields of application of similar technologies is extremely important to accelerate the development of innovative solutions. | |
| deteCtion and threAts of maRinE Heat waves (CAREHeat) | CNR-INSTITUTE OF MARINE SCIENCES-ISMAR (IT) | Science | biodiversity science cluster, blue economy, carbon cycle, climate, Ecosystems, marine environment, ocean health flagship, ocean heat budget, ocean science cluster, oceans, SST | ||
| Development and interpretation of improved Nitrous Acid Retrievals project – DINAR | The importance of nitrous acid (HONO) in atmospheric chemistry stems from its role as precursor of the OH radical.The latter is among the most important oxidizing molecules and controls the degradation of pollutants and greenhouse gases, and [...] | BELGIAN INSTITUTE OF SPACE AERONOMY (BIRA-IASB) (BE) | Science | air quality, atmosphere, atmospheric chemistry | The importance of nitrous acid (HONO) in atmospheric chemistry stems from its role as precursor of the OH radical.The latter is among the most important oxidizing molecules and controls the degradation of pollutants and greenhouse gases, and contributes to ozone formation and photochemical smog. Accurate representation of HONO sources is highly relevant to the modeling of climate and air quality. However, many uncertainties remain on the formation mechanisms, in part due to the lack of large-scale HONO measurements,consequently, the impact of HONO emissions on tropospheric chemistry remains particularly uncertain although it is believed to be important. Recent global space measurements of HONO in freshly emitted biomass burning plumes using the Sentinel-5Precursor/TROPOMI instrument have provided unprecedented information on the distribution and emissions of this compound, and have opened new research possibilities. The DINAR project addresses the need for highly sensitive, mature and easily accessible HONO space-based data. DINAR aims at developing HONO products from multiple and complementary satellite payloads including polar-orbiting and geostationary platforms, operating in the ultraviolet-visible (TROPOMI, OMI, GEMS) and thermal infrared (IASI, GIIRS) spectral ranges. Using improved retrieval techniques, the observation of atmospheric HONO sampled at different overpass time (including night time) has a large and exciting potential for innovative science and for improving our understanding of HONO formation and its impact on atmospheric chemistry. |
| Development of an AI-based Cloud Mask Processor for Sentinel-2 | The objective of this activity is to develop the most accurate free and open cloud mask for Sentinel-2 with global coverage and to make it available for global Earth Observation community and promote its usage. For this it is required to [...] | KAPPAZETA LTD (EE) | AI4EO | AI4EO, Sentinel-2 | The objective of this activity is to develop the most accurate free and open cloud mask for Sentinel-2 with global coverage and to make it available for global Earth Observation community and promote its usage. For this it is required to separate cloud free areas from cloud- and cloud shadow-corrupted areas as accurately as possible in the automatic processing chains for higher level products derivation. Using an AI model all the pixels are divided into four classes following the CMIX standard: Cloud free; Cloud; Semi-transparent cloud; Cloud shadow. Output cloud masks are with 10 m spatial resolution and Sentinel-2 data is ready to use for higher level products derivation. Cloud and cloud-shadow corrupted areas are reliably separated. The output of this project targets all users who need Sentinel-2 data, including private companies, academia, and governmental users. Currently global coverage support is added by increasing the training set using existing free and open labelled Sentinel-2 imagery data sets and labelling additional products by KappaZeta team. |
| Development of pan-European Multi-Sensor Snow Mapping Methods Exploiting Sentinel-1 | The main objective is the development, implementation and validation of methods and tools for generating maps of snowmelt area based on SAR data of the Sentinel-1 mission and the combination with snow products derived from optical sensors of [...] | ENVEO – ENVIRONMENTAL EARTH OBSERVATION GMBH (AT) | Science | applications, polar science cluster, SAR, science | The main objective is the development, implementation and validation of methods and tools for generating maps of snowmelt area based on SAR data of the Sentinel-1 mission and the combination with snow products derived from optical sensors of Sentinel-2 and Sentinel-3 missions. The developed algorithm will be used to generate multi-sensor pan-European snow products. A key activity of the project is the development of a retrieval algorithm for mapping extent of wet snow areas which exploits the full technical and operational potential of the Sentinel-1 mission. Round robin experiments between available algorithms will be carried out to select the optimum algorithm. The focus will be on the use of Interferometric Wide swath mode data which is the standard operation mode of Sentinel-1 over land surfaces. Particular attention will be paid to the capability of dual polarization data, and the exploitation of the high spatial resolution and geometric accuracy of the Sentinel-1 data. Because C-band SAR is not sensitive to dry snow, the combination with snow maps derived from optical sensor is required in order to obtain complete pan-European snow maps. We plan to use data of the Sentinel-3 sensors SLSTR and OLCI for the pan-European snow maps, and coincident Sentinel-2 based snow maps (with high spatial resolution) primarily for evaluation and assessment of uncertainty for the combined Sentinel-1 and Sentinel-3 snow product. The method for mapping wet snow using Sentinel-1 developed within this project is the basis for the SAR wet snow service implemented within the Copernicus Land Monitoring Service – pan-European High Resolution Snow and Ice Service – Part II. |
| DFIS – Multispectral Imaging Data Fusion in Space | The main objectives of the activity are:to develop and evaluate an approach to performing effective data fusion of multispectral data on-board satellites (SWIR imager of TRISAT mission). The focus of the activity was on identifying (in [...] | SKYLABS D.O.O. (SI) | AI4EO | Sentinel-1, Sentinel-2 | The main objectives of the activity are: to develop and evaluate an approach to performing effective data fusion of multispectral data on-board satellites (SWIR imager of TRISAT mission). The focus of the activity was on identifying (in collaboration with downstream users) Regions-of-Interest, then developing image processing techniques (band selection, compression, fingerprinting and classification) that can be used to perform on-board image processing on-board a satellite. To verify the developed approach to multispectral data fusion using relevant multispectral imaging data. The techniques developed in the previous step were evaluated based on their data reduction performance, as well as resources for their execution on-board a satellite. |
| DIGITAL TWIN EARTH PRECURSORS – OCEANS | Considering the long-term goal for Digital Twin Ocean (DTO) of being a virtual representation of the marine environment including all its known features and dynamics, the DTO-p project proposes to:Define a concept of a DTO, implement and [...] | IFREMER (FR) | Science | marine environment, oceans, regional initiatives, science | Considering the long-term goal for Digital Twin Ocean (DTO) of being a virtual representation of the marine environment including all its known features and dynamics, the DTO-p project proposes to: Define a concept of a DTO, implement and demonstrate to a relevant stakeholder community and ESA; Create a solid scientific and technical basis upon which the Destination Earth vision proposed by the EU can be realized Explain and simulate two very distinct ocean phenomena in two very contrasting marine basins: marine heatwaves in the Mediterranean Sea and sea ice breaking in the Arctic Ocean. |
| Discrete Bayesian Inversion of Satellite Gravity (DISG) | Living Planet Fellowship research project carried out by Wolfgang Szwillus. Density variations inside the mantle not only drive mantle convection but are also important indicators of rock composition variation. Satellite gravity measurements, [...] | CHRISTIAN-ALBRECHTS-UNIVERSITAET ZU (DE) | Science | GOCE, living planet fellowship, science, solid earth | Living Planet Fellowship research project carried out by Wolfgang Szwillus. Density variations inside the mantle not only drive mantle convection but are also important indicators of rock composition variation. Satellite gravity measurements, like GOCE, are directly sensitive to large-scale density variations inside the Earth, but their potential is not yet fully used. Instead, density is typically estimated based on variations of seismic shear wave velocity. The gravity field is only used in a second step to estimate the viscosity structure of the Earth. Thus, in the classic approach, resolution of Earth’s structure and dynamics become entangled and there is no possibility for density variations unrelated to velocity variations. In this project I will rely on gravity data and seismological constraints to estimate the density distribution inside the mantle, without including any dynamical modelling. To achieve a fair combination of seismology and gravity, a good understanding of their respective uncertainties is required. For the gravity field, this mainly relates to uncertainties due to crustal structure and has already been studied, while seismic tomography models suffer from uncertainties due to different smoothing approaches. To estimate these, an ensemble of recent seismic tomography models will be converted to its equivalent representation as surface wave phase speeds, eliminating vertical smoothing. The gravity field and the surface wave speed maps will be used to find discrete anomalous volumes in the mantle in terms of their location, shape, density and seismic wave speed. Since both the number as well as the properties of the anomalous volumes are unknown, a novel Bayesian inversion method will be developed, that uses the transdimensional Monte-Carlo-Markov-Chain algorithm. With this technique an in-depth study of required model complexity, resolution limits and trade-offs is possible. |
| DryPan: Novel EO data for improved agricultural drought impact forecasting in the Pannonian basin | The Pannonian basin is a sheltered region, with relatively low levels of precipitation (< 600 mm/year), therefore its surrounding mountains are considered a key water source. Over the last decades several drought episodes took place. [...] | EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT) | Science | agriculture, applications, Black Sea and Danube, climate, climate adaptation flagship, regional initiatives, science, water resources | The Pannonian basin is a sheltered region, with relatively low levels of precipitation (< 600 mm/year), therefore its surrounding mountains are considered a key water source. Over the last decades several drought episodes took place. Scientific research groups with cross-border cooperation on drought monitoring and management were established including the Drought Management Centre for South-Eastern Europe (DMCSEE) (hwww.dmcsee.org) and the Pannonian Basin Experiment (PannEx). These act as a response to combat the increased frequency and intensity of dry spells and heat waves under climate change and the need to increase the capacity of the relevant stakeholders to manage drought events and their impacts. The DryPan project is funded by ESA and builds upon the experiences of the Interreg funded DriDanube products. DryPan’s objectives include: i) to develop and validate a set of novel Earth Observation products and enhanced data sets dedicated to characterise Drought processes in the Pannonian basin; ii) to foster new scientific results addressing some of the main priority areas of research in the region, where space technology may provide a valuable input; iii) to promote the use of advanced EO datasets for Drought Early Warning in the region by facilitating access to the developed products and results through a professional project web site exploiting advanced data access and visualisation tools; and iv) to develop a roadmap identifying additional science priorities as a driver for launching potential new development activities addressing the priorities of the Danube science communities in the timeframe 2020-2021. |
| DTUP – Digital Twin Urban Pilot | The urban environment we live in is more and more complex. Interrelations and dependencies as well as the effects of changes are becoming increasingly difficult to assess. In this framework, the Digital Twin Urban Pilot (DTUP) concept is of [...] | DLR – GERMAN AEROSPACE CENTER (DE) | AI4EO | AI4EO, applications, mapping/cartography | The urban environment we live in is more and more complex. Interrelations and dependencies as well as the effects of changes are becoming increasingly difficult to assess. In this framework, the Digital Twin Urban Pilot (DTUP) concept is of key importance: It allows to create an image of the reality on which one can effectively test and simulate the effects of new solutions, plans or system changes in the digital image first, before they are then implemented – or showing an effect – in the real world. The DTUP goals are: i) to develop a system that allows to create, visualise and explore pilot 4D digital twins (DTs) generated from drone and street-view imagery; and ii) to showcase their high potential for integrated and advanced analyses once combined with different types of spatiotemporal data and by means of state-of-the-art machine- and deep-learning (ML/DL) techniques. DTUP builds on the experience acquired during the Artificial Intelligence for Smart Cities (AI4SC) project, which concluded in July 2020. Specifically, its main objective was the generation of a set of indicators at global scale to track the effects of widespread urbanization processes and, concurrently, a set of indicators to help addressing key challenges at local scale. In this latter framework, from constructing exchanges with the project users, it clearly emerged the need for more detailed 4D information which allows to characterize in high detail the morphology of the urban environment and, alongside, the possibility of integrating any spatiotemporal georeferenced dataset for advanced analyses. These requirements represented the basis of the DTUP activity. The project study areas include the Frascati town center and the ESRIN establishment. The envisaged DTs consist in modern and responsive platforms which allow to explore detailed textured 3D models of ESRIN and Frascati generated from drone imagery, along with different EO-based products and ancillary datsets. Specifically, the DTs are organized in 3 different components, namely: a browser web application, an Android application for Smartphone, and an Android application for Wearable Devices. In this framework, use cases are being designed where the integration of satellite-based data, as well as mobility records and in-situ weather/air quality sensors allow to effectively support different thematic applications (including end-to-end decision-support ‘what-if’ scenarios). Here, two different approaches are considered: To exploit the unique 4D visualization features of the DTs (which enables experts, non-experts and decision makers to easily interpret complex information and consider dependencies, trends and patterns); To employ advanced AI approaches for jointly exploiting different multisource datasets included in the DTs at once and generate novel products. |
| DYNAMIC TOPOGRAPHY AND SATELLITE GRAVITY DATA JOINT INVERSION USING REDUCED ORDER MODELS (DYGIRO) | Geophysical observables (e.g. surface elevation, gravity anomalies, seismic data, surface heat flow, etc.) are one of the main sources of information used to make inferences about the interior of the Earth. Obtaining consistent models requires [...] | Universidad Complutense de Madrid (ES) | Science | GOCE, gravity and gravitational fields, living planet fellowship, solid earth | Geophysical observables (e.g. surface elevation, gravity anomalies, seismic data, surface heat flow, etc.) are one of the main sources of information used to make inferences about the interior of the Earth. Obtaining consistent models requires combining simultaneously different observable datasets into joint inversions. Among geophysical data, gravity data from ESA’s GOCE satellite mission provides key information in properly constraining the Earth’s density distribution. WINTERCG is a new global thermochemical model of the lithosphere and upper mantle (currently being extended to transition zone) that, among other observables, uses global satellite gravity from GOCE to constrain the model. Its inversion scheme has two main steps. In step 1, 1D inversion is performed using waveform seismic tomographic data and isostasy primarily. Then, in step 2, the output model from step 1 is used as prior information for the inversion of GOCE’s gravity field data for the 3D crustal density and upper mantle composition. As a consequence, the density field changes and modifies the isostatic balance previously achieved in step 1. It originates a residual isostatic topography that can be regarded as a proxy for dynamic topography. However, within a rigorous framework, residual topography and computed dynamic topography (i.e. solving the Stokes equation) should be consistently integrated into a joint inversion with feedback from both the static and dynamic sides. This is currently missing in WINTERC-G and the goal of this project is to add a third step to WINTERC-G global inversion scheme that consistently integrates dynamic topography as an additional model constrain. To do that, we will explicitly compute dynamic topography solving the associated Stokes equation fed by the model 3D distributions of densities and viscosities within the upper mantle and transition zone. Furthermore, the dynamic effects related to mantle convection affect geoid sensitivity kernels; in this project we will also consistently modify the description of the gravity field to include viscosity effects. |
| DYNAMOS – Dynamic Mosaic Service | DYNAMOS is being implemented as a cloud-based, dynamic mosaicking service, initially focussing on Sentinel-2 data. The service will provide users the ability to request the creation of large area mosaics according to their requirements, [...] | SPACEMETRIC AB (SE) | Digital Platform Services | generic platform service, permanently open call, platforms, Sentinel-2 | DYNAMOS is being implemented as a cloud-based, dynamic mosaicking service, initially focussing on Sentinel-2 data. The service will provide users the ability to request the creation of large area mosaics according to their requirements, primarily in terms of area and time frames, image selection and prioritisation considerations. DYNAMOS is building on the concept of dynamic mosaic creation. Here “mosaic recipes” capture the required data details and processing steps for the on-demand creation of the mosaic. This also allows actual processing operations to only occur for areas directly demanded e.g. for visualisation or storing only the virtual recipe rather than a large dataset. The DYNAMOS activity is driven by a set of use cases in the agriculture and forestry application areas. The service is currently being designed for and deployed in AWS. |
| E-COMMERCE PLATFORM FOR MICRO-GEOSERVICES (Store4EO) | Innovative approaches to distribute services to both public and private markets, being more automated and interoperable, are expected to support EO companies in getting the best return on investment.Micro geo-services based on the use of [...] | Deimos Engenharia (PT) | Digital Platform Services | generic platform service, platforms | Innovative approaches to distribute services to both public and private markets, being more automated and interoperable, are expected to support EO companies in getting the best return on investment. Micro geo-services based on the use of satellite data, delivering very focused earth measurements (e.g. burnt area map/index, NDVI, land use, etc..), address potentially a wide audience, available to pay only a small amount, typically ordering products for a few tens of Euros, for their geo-temporal area ofinterest. Given the rather limited revenue margin, it is essential that scalable data storage and processing environments (e.g. on the cloud), but also e-commerce platform capabilities can be shared across value adding providers. In particular, the EO value adding sector is characterised by a high number of small and specialized companies operating in specific application domains; building the complete vertical stack by themselves. While they excel in their core business, they may lack IT competences and/or resources to publish and market their information extraction algorithms via modern on-line platforms. The purpose of this project is aimed then at simplifying and automating overall ICT deployment and commercial exploitation of micro geo-services from the Earth Observation sector. Through an online e-commerce platform (Store4EO) enabling advanced capabilities for publishing, ordering, delivery, accounting and billing, the elapsed time between service demand and service output shall be shortened, avoiding repetitive ICT tasks non related to EO value adder core activities, with an overall efficiency improvement and cost reduction. These micro geo services will be deployed and processed at remote cloud infrastructure (e.g DIAS) and will be executed on demand and scheduled for execution (e.g subscription based) . The Store4EO platform will matchmake EO value adders the customers of EO services by providing the capability to commercialise their processing algorithm. The will be able to order these services and integrate in their decision making process or even to chain a set of micro geo services to create a work a complex workflow.The Store4EO eCommerce service aims to close the gap between the vast number of EO services available in the EO sector and discoverability of these services to the end users. Store4EO will then foster: B2B commerce where other value adders could also build high-value added services from further concatenation of micro services (e.g. through APIs and workflows)B2G benefitting from trusted and ready-to-use micro services easy to integrate in their processes B2G benefitting from trusted and ready-to-use micro services easy to integrate in their processes B2C commerce where users likely make heavy usage of mobile devices in their daily life A validated pre-operational platform within 4 months of the project. This first version of the pre-operational platform will be ready for the services providers to register and publish their services for the end users. A business model will be defined. It will incorporate the price model, the subscription schemes , the revenue sharing model with the EO services providers , the envisioned cost structure etc.In terms of high level functionality, the Store4EO service will offer interfaces for the service providers to register and deploy their services in the platform. The platform will provide a user interface for the end users to browse through the service catalogue and select the service they prefer. The catalogue will contain all the necessary information to assist the purchasing decision making process of the end user. The end users will be able to order the service after successfully payment. The users will also be view the status of the orders and receive notification when the product is ready for delivery. The end users will have the option to get the output data from the platform or via API. |
| e-Drift (Disaster risk financing and transfer) | Disaster Risk Financing (DRF) can increase the ability of national and local governments, homeowners, businesses, agricultural producers, and low-income populations to respond more quickly and resiliently to disasters by strengthening public [...] | CIMA RESEARCH FOUNDATION (IT) | Enterprise | disaster risk | Disaster Risk Financing (DRF) can increase the ability of national and local governments, homeowners, businesses, agricultural producers, and low-income populations to respond more quickly and resiliently to disasters by strengthening public financial management and promoting market-based disaster risk financing. Recent improvements in quality and availability of satellite-derived characteristics increased the usability of EO products, allowing for better results and further synergies between actors, potentially expanding the market of Disaster Risk Financing applications. The Project: e-Drift (Disaster RIsk Financing and Transfer), financed by ESA and led by CIMA Research Foundation (IT), aims at improving the performance of the EO products and determine a fully automatic and reproducible way to service DRF applications. The e-Drift Virtual Platform enables an easy and timely access to various services and products guaranteeing high computing capability and direct access to the EO datasets of the Sentinel constellation. Services will cover several key areas of interest of the insurance market and of Countries that would like to transfer their sovereign risk. The e-Drift Virtual Platform will be released as a PAAS, so that can be embedded in the IT systems of the In-Sector Providers, and as a SAAS, so that can be used by In-Sector Providers by a unique and KISS End User Interface. The project is also creating a strong network between providers of value-added services utilizing EO data, In-Sector service providers for the insurance market and reinsurance companies as well as other concerned actors in the field like the World Bank, with the final purpose to create new or improved products and solutions for the Insurance sector. The project consortium includes leading companies in the EO value adding, and leading actors in the insurance market and concentrates as a pilot study area in South East Asia, more specifically on Myanmar, Laos and Cambodia. |
| E. Ccoli Alert Data Service (EADS) | The aim of this activity is to investigate the viability of developing an Escherichia coli (E. coli) Alert Data Service for environmental agencies and local authorities. This will be carried out via the development of an analysis method for the [...] | TECHWORKS MARINE LTD (IE) | Enterprise | coastal zone, generic platform service, natural hazards and disaster risk, permanently open call | The aim of this activity is to investigate the viability of developing an Escherichia coli (E. coli) Alert Data Service for environmental agencies and local authorities. This will be carried out via the development of an analysis method for the fusion of in-situ (lab and sensor measurements) and satellite data (optical and radar), validated by stakeholders with an interest in investing in a long term commercial service. The information from the service will be available on TechWorks Marine’s CoastEye platform, which allows access to a wide range of geospatial data. The expected impact of this service would be to provide local authorities, environmental agencies and government departments with improved information on the likelihood of a contamination event occurring, allowing for an informed decision on whether or not to restrict access to a given coastal area. The benefit of this would be to reduce the risk of illnesses associated with the presence of E. coli in coastal waters, as the areas could be closed as a precautionary measure before the E. coli reaches these areas. |
| Earth Observation Advanced science Tools for Sea level Extreme Events (EOatSEE) | Earth Observation Advanced science Tools for Sea level Extreme Events (EOatSEE) is a project funded by ESA and proposed by a consortium of institutions and companies that are internationally recognized for their work in the Marine, Coastal and [...] | Deimos Engenharia (PT) | Science | altimeter, bathymetry and seafloor topography, coastal processes, coastal zone, Erosion and Sedimentation, natural hazards and disaster risk, ocean science cluster, ocean waves, oceans, rivers, science, Sentinel-1, Sentinel-2, Sentinel-3, Sentinel-6, surface water, tides | Earth Observation Advanced science Tools for Sea level Extreme Events (EOatSEE) is a project funded by ESA and proposed by a consortium of institutions and companies that are internationally recognized for their work in the Marine, Coastal and Earth Observation topics. It aims to provide an advanced reconstruction of the relevant processes included in extreme sea level (ESL) events and its related coastal hazards, by taking advantage of the novel capabilities and synergies offered by the latest advances in EO technology. The solid scientific knowledge arising from EOatSEE therefore shall enhance the fundamental scientific understanding and predictive capacity of such events, as well as our potential to better assess the related risk and the vulnerability of coastal zones. Therefore, following an initial phase for scientific requirements consolidation, EOatSEE will address the following three main science cases domains, which represent the main drivers for the proposed work: Science case 1 – Predictability: drivers of extreme sea level flooding hazards Science case 2 – Process understanding: the cascade effect of extreme sea level events on long-term coastal evolution considering the dynamic morphological response Science case 3 – Assessment and risk and vulnerability: the tipping points of coastal systems To accomplish such scientific and technical objectives, EOatSEE methodological approach is divided in two main domains: short-term – where Science case 1 will be addressed using three distinct approaches: a high resolution downscaling process-based modelling approach (HRDW), together with the new EO-products implemented in the model chain; a linear summation empirical modelling downscaling method (LSDW), considering coastal morphology as passive (no changes along time); a reduced complexity forecasting coastal evolution model (ForCE), which adds the capacity to simulate active morphology (morphological response along the time, due to changes in water levels and waves). long-term – where Science cases 1 and 2 will be addressed using the LSDW and ForCE approaches, considering the extremely high computational cost of performing long-term high-resolution numerical modelling as in HRDW; a combination of both short-term and long-term approaches shall also be employed to address Science case 3. The project also includes the development of a pilot program of scientific research and knowledge transfer to early-adopters, focused on six different use cases located in key vulnerable areas. Specific applications are to be employed by these engaged end-users for knowledge-based decision making, evaluating the added value of EO-products on the high-resolution downscaling modelling tools and within historical analysis and future projections of ESL events. Moreover, a community Scientific Roadmap should be developed aimed at transferring the outcomes of the EOatSEE into future scientific activities and indicating potential topics for additional research. The kickoff meeting for EOatSEE was held on Friday 24 June 2022. If you are interested in contributing to the scientific discussion or accessing any of the data sets it will produce, please contact the Project Manager via the web site above. |
| Earth Observation and Geology for Artisanal and Small Scale Mining Monitoring – ASM alert | The project sets out to use EO and geologic information to detect and monitor artisanal & small-scale mining (ASM) activities in tropical areas. ASM is an important economic factor in developing countries but poses serious environmental, [...] | GAF AG (DE) | Enterprise | environmental impacts, security, sustainable development | The project sets out to use EO and geologic information to detect and monitor artisanal & small-scale mining (ASM) activities in tropical areas. ASM is an important economic factor in developing countries but poses serious environmental, health, and criminal threats to local communities. The associated deforestation is also a considerable factor in regional and global climate change.Public, high-resolution (HR, 10m) and multi-temporal Sentinel-2 satellite imagery allows to detect and monitor indicators of ASM. The imagery is processed in a “cloud” environment and the resulting indicators are retrieved by a user-friendly internet front-end platform – the ASM alert tool – that demands no IT- or image processing knowledge on side of the user.The geologic information (rock units, tectonic structures, known gold occurrences) are analyzed and reclassified according their potential to bear gold, resulting in “gold potential” map. This gold potential map helps to prioritize EO HR indicators and to decide to acquire additional up-to-date very-high-resolution satellite imagery that may be used as evidence for legal disputes. The project sets out to develop, implement, test and train the ASM alert tool. The second focus of the project is to maximize the political outreach of the project results. For this purpose GAF is teaming with the Institute for Environmental Security (IES). The project will promote the results to decision makers at the international court in Den Hague, the OECD, the OAS and the World Bank beyond others key stakeholders (e.g. the Convention on Biological Diversity, the Climate Convention, the Convention to Combat Desertification, the World Heritage Convention,the Inter-American Court on Human Rights). |
| Earth Observation Best Practices: Earth Observation for the Mining of Raw Materials (EO4RM) | Mining takes place across the globe, often in very remote locations, dispersed amongst countries of differing degrees of wealth. Companies are facing multiple challenges throughout all life cycle stages from the exploration phase to mine closure [...] | Deltares (NL) | Enterprise | best practices, energy and natural resources, enterprise, mining, raw materials | Mining takes place across the globe, often in very remote locations, dispersed amongst countries of differing degrees of wealth. Companies are facing multiple challenges throughout all life cycle stages from the exploration phase to mine closure and aftercare. Information derived from Earth Observation satellites can provide a continuous flow of information for the monitoring and management of subsidence, geology, biology, ecology, socio-economic development, resource availability and much more. It can also provide data about very remote and inaccessible areas. The Earth Observation for the mining of Raw Materials (EO4RM) project brings together experts from both the mining and the Earth Observation sector to identify key challenges of the sector and suitable solutions drawing from modern and future Earth Observation capabilities. The objective of the activity is to establish current information needs and best practices for the use of Earth Observation-based products and services. The scope of the activity includes all relevant business processes (“the mining life cycle”), from exploration and impact assessment to exploitation and post-closure, as well as the geoinformation needs of relevant regulatory agencies. The expected outputs of the project are: To unlock current Earth Observation services and products for the mining sector To showcase some of these services and products in a virtual platform To build a roadmap towards EO services best practice uptake. As part of the project, the consortium has engaged an International Industry Board (IIB), who will advise the consortium on the project throughout each stage. |
| EARTH OBSERVATION COLLABORATIVE RESEARCH NETWORK | The project aims to build a Collaborative Research Network (CRN) to foster collaborations among Earth Observation and Transformative Technologies researchers and experts. The CRN will be created through different schemes, whose common goal is to [...] | PI SCHOOL S.R.L. (IT) | AI4EO | The project aims to build a Collaborative Research Network (CRN) to foster collaborations among Earth Observation and Transformative Technologies researchers and experts. The CRN will be created through different schemes, whose common goal is to attract, towards ESA Φ-lab, key leaders in the sectors mentioned above. | |
| Earth Observation data For Science and Innovation in the Black Sea (EO4SIBS) | In the frame of the ESA Regional Initiatives, a set of coordinated activities between science, public sector, industry growth and infrastructure components focussing on regional priorities with high interest for Member States, a number of [...] | UNIVERSITY OF LIEGE (BE) | Science | Black Sea and Danube, carbon science cluster, ocean science cluster, oceans, regional initiatives, science, Sentinel-2, Sentinel-3 | In the frame of the ESA Regional Initiatives, a set of coordinated activities between science, public sector, industry growth and infrastructure components focussing on regional priorities with high interest for Member States, a number of Science and Application projects are being runned for the Black Sea and Danube region. In this context, the EO4SIBS (Earth Observation data For Science and Innovation in the Black Sea) project is dedicated to Ocean Science. The objectives of this project are: To develop a new generation of algorithms that can ingest the wealth of spatial, temporal and spectral information provided by recent sensors providing high quality reference products for the blue and green ocean. In particular, regarding Ocean Colour derived products, innovative, high quality reference products of Chl-a, Total Suspended Matter (TSM) and turbidity products will be generated for the whole Black Sea geographical area, with a special focus on the western part directly influenced by the Danube River plume. Merged products will be generated to combine the high temporal resolution of S-3 OLCI and high spatial resolution of S-2 MSI satellite products and capture the optimal spatio-temporal coverage over the Black Sea waters. Concerning altimeter datasets, Level-3 Sentinel-3A [2016, 2018] and Cryosat-2 [2011, 2018] along-track product will be generated and their impact for coastal sea level trend study in the Black Sea assessed, and Level-4 multi-mission gridded products over the [2011, 2018] for improved mesoscale studies. Finally, 10 year (2010-2020) of improved gap-free high resolution salinity products will be generated. To collect new data to support the development of novel algorithms and to propose laboratory analyses of the highest quality To build novel composite products that integrate the satellite information with that from robotic platforms and numerical ocean models; To assess how the use of EO data improves our knowledge of good environmental status (GES) and climate change in the Black Sea. In particular three scientific use cases will be assessed : Physical oceanography and biochemical ecosystems; Black Sea level dynamics and trends; Deoxygenation. To disseminate the developed tools and products to the regional and international scientific and end-user community through the setting of a web platform, the organization of dissemination events, the participation to conferences. |
| Earth Observation for Air Quality and Health ‘AlpAirEO’ – Alps regional initiative | Recently, the European Environmental Agency (EEA) reported that air pollution contributed to 400.000 annual deaths in the EU. The Alps are special. They host 14 million people and attract many tourists and businesses. Due to the diverse [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Regional Initiatives | air quality, Alps, atmosphere science cluster, climate, health, regional initiatives, Sentinel-3, Sentinel-5P | Recently, the European Environmental Agency (EEA) reported that air pollution contributed to 400.000 annual deaths in the EU. The Alps are special. They host 14 million people and attract many tourists and businesses. Due to the diverse landscape and climate, pollution hotspots can develop in certain areas while pristine environments prevail throughout most of the high Alpine regions. As part of the “eo4alps” initiative ESA held a workshop in June 2018 with leading scientists to discuss the potential benefits of earth observation of the Alpine region. “Air quality & health” was identified as one of four priority actions. The project “AlpAirEO” will use state-of-the-art technology to deliver innovative science and information services to support expert and non-expert stakeholders and thereby help to improve the general quality of life in the Alps. By approach of co-design, the needs of the health community will be addressed. Satellites EO in conjunction with atmospheric models and surface observations can deliver the spatial coverage and quality needed. The project will look into the available data from operational instruments like MODIS and GOME-2 and especially the new Sentinel mission instruments starting with Sentinel 3 SLSTR for aerosols and Sentinel 5P TropOMI covering NO2. Additionally, the Copernicus Atmospheric Monitoring Service (CAMS) and Copernicus Climate Change Service (C3S) will provide important information on atmospheric constituents and climate indicators. For reference, surface-based data from observation networks for the Alpine region will also be taken into consideration. The unprecedented capabilities of the new Sentinels and the Copernicus services will be combined with available environmental information and demographic data, e.g. population density. By following the recommendations of WMO-CCI and WHO, the findings of epidemiological studies and evidence of regional health statistics, daily information on health risk due to environmental stress can be derived.Results will be made freely available based on the Bioclimatic Information System hosted by AlpEnDAC as part of the Virtual Alpine Observatory. Project lead: German Aerospace Center (DLR) Project Duration: 2020 – 2022 Discover more projects, activities and resources on the Alps regional initiative (EO4ALPS) page. |
| Earth Observation for Alpine ecosystems ‘eco4alps’ – Alps regional initiative | The project is an Application element of EO4ALPS Regional Initiative. It will develop 6 EO services on ecosystem mapping and monitoring in the alpine region, addressing the specific requirements of national and regional stakeholders and being [...] | Solenix Schweiz GmbH (CH) | Regional Initiatives | Alps, ecosystems/vegetation, forestry, platforms, regional initiatives | The project is an Application element of EO4ALPS Regional Initiative. It will develop 6 EO services on ecosystem mapping and monitoring in the alpine region, addressing the specific requirements of national and regional stakeholders and being sufficiently large in scope and content to strengthen regional cooperation across alpine countries: ecosystem mapping, forest disturbance, forest phenology, forest fire recovery, grassland management and grassland abandonment. A 2nd objective of the project is to demonstrate the added value of an open and federated network of platforms to provide these services at regional scale. A proof of concept on a transboundary area of 50,000 km2 will demonstrate the adequacy and usefulness of the proposed services. Discover more projects, activities and resources on the Alps regional initiative (EO4ALPS) page. |
| Earth Observation for Landslides ‘eo4alps landslides’ – Alps regional initiative | The project focuses on implementing regional geoinformation services and products for landslide risk assessment over the Alpine mountain range. EO4ALPS-landslides will set the basis for the creation of harmonized and advanced landslide [...] | SATT CONECTUS ALSACE (FR) | Regional Initiatives | Alps, disaster risk, land, regional initiatives, thematic exploitation platform | The project focuses on implementing regional geoinformation services and products for landslide risk assessment over the Alpine mountain range. EO4ALPS-landslides will set the basis for the creation of harmonized and advanced landslide inventories and susceptibility/hazard maps based on EO ground motion services linked to advanced modelling capabilities all embedded in the user-driven GeoHazard Exploitation Platform (GEP). The project is user-driven with the engagement of more than 20 authorities and other stakeholders responsible for landslide disaster risk management involved in all project phases. An online survey was conducted among more than 100 potential end-users of the eo4alps-landslides geoinformation system. Fifty-four survey answers representing 49 stakeholders were collected. These respondents are mostly active at national or regional level with operational mandates in landslide hazard and risk management, monitoring, mapping, mitigation, disaster intervention and land-use planning. |
| Earth Observation for operational hydrology ‘eo4alps snow’ – Alps regional initiative | The project focuses on implementing a high-resolution quasi real-time snow monitoring to improve water resource management. It is taking advantage of the recent developments in physically-based snow modelling and is based on high-resolution [...] | MobyGIS Srl (IT) | Regional Initiatives | Alps, regional initiatives, Sentinel-1, Sentinel-2, snow and ice, water cycle and hydrology | The project focuses on implementing a high-resolution quasi real-time snow monitoring to improve water resource management. It is taking advantage of the recent developments in physically-based snow modelling and is based on high-resolution optical and radar EO missions such as Sentinel-1 and 2. The core service is a snow water equivalent (SWE) product generated using a cloud based processing environment to be delivered over the entire Alpine arc region. The eo4alps team is planning to engage users from public and private sectors, such as public agencies, research centers, associations and hydropower companies. |
| Earth Observation for Poverty – EO4Poverty | Poverty is one of the chronic problems of the XXI century and, despite the recent decrease of global economic inequalities between and within countries, in 2016 about 800 million people still lived in extreme poverty condition, with many of them [...] | MindEarth (CH) | Applications | mapping/cartography, permanently open call | Poverty is one of the chronic problems of the XXI century and, despite the recent decrease of global economic inequalities between and within countries, in 2016 about 800 million people still lived in extreme poverty condition, with many of them located in sub-Saharan Africa and Southern Asia. In this context, poverty alleviation programmes generally rely on data about local economic livelihood for identifying places with highest need for aid. Nevertheless, this information traditionally comes from patchy and logistically challenging household surveys which normally happen to be extremely expensive. As a result, policymakers and public sector stakeholders lack key data necessary for targeting anti-poverty programs or properly measuring their effectiveness. Given the challenges of scaling up traditional data collection efforts, in the past few years alternative strategies have been proposed for assessing the degree of poverty based on satellite data. The main objective of EO4Poverty is to implement a novel system based on advanced machine- and deep-learning techniques for generating national spatial poverty maps by jointly exploiting EO-based products (in particular derived from Copernicus Sentinel data) and non-EO based products (e.g., roads and transportation networks, social media) coupled with in-situ reference information gathered from publicly available household surveys. The project aims to improve existing approaches and to provide an easily transferable service for creating maps of actual support to the end-users. |
| Earth Observation for Surface Mass Balance (EO4SMB) | The aim of the Earth Observation for Surface Mass Balance (EO4SMB) study is to investigate the feasibility of measuring ice sheet Surface Mass Balance from space. Accurate measurements of Ice Sheet Surface Mass Balance (SMB) are key to [...] | UNIVERSITY OF LANCASTER ENVIROMENT CENTRE (GB) | Science | Glaciers and Ice Sheets, polar science cluster, science | The aim of the Earth Observation for Surface Mass Balance (EO4SMB) study is to investigate the feasibility of measuring ice sheet Surface Mass Balance from space. Accurate measurements of Ice Sheet Surface Mass Balance (SMB) are key to understanding the response of ice sheets to a changing polar climate. However, traditionally information on SMB has come from climate model simulations alone. This exploratory study will therefore investigate whether a new generation of satellite instruments can be used to directly quantify SMB, thereby addressing the growing need within the polar community for such data. In the EO4SMB study, we will focus primarily on exploiting measurements from ESA’s ice mission, CryoSat-2, to derive a portfolio of SMB parameters, which will cover the period 2010-2020. The study will focus on developing, validating and interpreting measurements at three test sites in Greenland, producing a proof-of-concept prototype SMB product, and undertaking several science use cases. Alongside this core activity, we shall also develop two exploratory techniques to leverage more information from satellite measurements; firstly by combining altimetry measurements with gravimetry data, and secondly by exploring the potential of Deep Learning to extract additional information from the CryoSat-2 satellite data. Through this project, we aim to demonstrate the feasibility of measuring SMB from space, and thereby establish the firm foundations for future operationally-derived SMB products. |
| Earth Observation for the Sustainable Development Goals (EO for SDGs) | The international community recently engaged in an ambitious universal agenda on sustainable development with the aim to end poverty, promote prosperity and people’s well-being while protecting the environment. The 2030 Agenda on Sustainable [...] | DHI WATER – ENVIRONMENT HEALTH (DK) | Sustainable Development | sustainable development | The international community recently engaged in an ambitious universal agenda on sustainable development with the aim to end poverty, promote prosperity and people’s well-being while protecting the environment. The 2030 Agenda on Sustainable Development ratified by the UN General Assembly in September 2015, is a new transformative and integrated development agenda that promotes shared economic prosperity, social development and environmental protection. In total 17 Sustainable Development Goals (SDGs) and 169 Targets have been adopted by the world leaders and will drive the agenda on sustainable development for the next 15 years, for both the United Nations and its Member States. The UN System has established a range of formal processes for achieving the sustainable development goals and monitoring progress towards the SDG Targets, with a particular focus to supporting the least developed economies and leaving no one behind. A robust monitoring mechanism for the implementation of the SDGs requires a solid framework of indicators, and consequently good and reliable statistical data, to measure, monitor and report progress, inform policy and ensure accountability of all stakeholders. The United Nations has adopted a Global Indicator Framework of 232 SDG Indicators that collectively provide a management tool for countries to implement development strategies and report on progress toward the SDG Targets. The 2030 Agenda for Sustainable Development stressed the importance of Geospatial Information and Earth Observations (including satellite observations) to inform the SDG Targets and Indicators. An effective monitoring of the SDG Indicators and reporting of the progresses towards the SDG Targets require the use of multiple types of data that go well beyond the traditional socioeconomical data that countries have been exploiting to assess their development policies. Satellite observations, with their global spatial coverage and high frequency of observations, prove essential in capturing important aspects of sustainable development and in particular the environmental dimension of the SDGs. An effective integration within national statistical systems can also significantly reduce the monitoring costs and consequently enable countries to meet their engagement to monitor and report progress on the Goals and Targets. The main goal of the project was to support the efforts of the European Space Agency and its partners, essentially the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS) to promote the use and showcase the utility of satellite Observations in the 2030 Agenda on sustainable development and in particular in the Global Indicator Framework. The project conducted a number of key tasks that helped streamlining the EO community efforts in its collaborative engagement on SDGs. These tasks included a thorough study of the contributions of satellite Observations to the SDG Targets and to the SDG Global Indicator Framework; a review of methodological guidelines for a number of key SDG Indicators; a national showcase of the integration of satellite Observations in country monitoring and reporting on SDG Indicators (in partnership with the National Statistical Office and line ministries of the selected country); and an analysis of the cloud computing infrastructures required to facilitate the uptake of satellite observations by the SDG stakeholders both at global and country levels. |
| Earth Observation services for the Black Sea Coastal Zone Management (EO4CZM) | The Black Sea is a region of particular interest in terms of its past and present level of ecological degradation by anthropogenic influences among the European Seas and highly dynamic and complex eddy-driven circulation system. The Black Sea [...] | TERRASIGNA (RO) | Enterprise | Black Sea and Danube, coastal zone, enterprise, generic platform service, regional initiatives, Sentinel-2 | The Black Sea is a region of particular interest in terms of its past and present level of ecological degradation by anthropogenic influences among the European Seas and highly dynamic and complex eddy-driven circulation system. The Black Sea receives drainage from almost one-third of the continental Europe (five times its surface area) which, it is relatively isolated from the world ocean and is highly vulnerable to external environmental stresses. Its coastal areas are at the forefront of these pressures. Integrated Coastal Zone Management (ICZM) should be used as a long term management tool, in order to protect the population, sustain exploitation of coastal resources and mitigate the effects of climate change and coastal hazards. A crucial element of the restoration and rehabilitation initiatives is the implementation of a continuous monitoring and operational observing system in the region. Earth Observation (EO) data can significantly contribute to the advance of oceanographic knowledge in the area. Services proposed to be developed will act as a multi-thematic information collection and analysis tool to support the decision-makers responsible for integrated coastal management implementation in the Black Sea coastal areas. It will also support the strategy concerning the Blue Growth in the region, by facilitating the access to key environmental variables related to aquaculture, pollution and habitat management. It will help develop sectors that have a high potential for sustainable jobs and growth, such as mussels farming, fisheries or coastal tourism.The following 5 thematic services are envisaged to be developed under the EO4CZM project: S1. Provision of a Sentinel-2 atmospheric corrected seamless mosaic, which will be available on-demand, for user defined regions and time periods. It will be produced taking full advantage of the high spatial resolution (10 m) and the multiple spectral wavelengths offered by the MSI sensor. S2. Thematic adapted remote sensing indices. This service will address particular, less complex needs and will include two categories of indices: i) general, well known indices, from an extensive list of pre-defined ones, such as Normalized Difference Vegetation Index (NDVI) and ii) new custom defined indices (e.g. ice detection on the Danube main branches and water bodies extent). S3. High-resolution products for water quality monitoring in Danube Delta – high resolution, high quality datasets related to deltaic environments will be produces. The service will address several water related indicators, such as turbidity, Suspended Particulate Matter (SPM) or Chlorophyll (Chl-a) concentrations. S4. Aquaculture resources management – improved EO based products will be developed in order to assist aquaculture activities in the coastal region of the Black Sea. Of prime interest are coastal SPM and Chl-a concentration datasets, improved in terms of regional algorithms and spatial resolution (300 m and better). Such products can help stakeholders, using long time series of EO data, to better assess the potential of specific sites and to analyze the occurrence of negative effects of nutrient pollution that can trigger eutrophication processes. These essential water quality indicators will be afterwards integrated into an added value product, in the form of an aquaculture suitability index. S5. Mapping of coastal geomorphological features – anthropic modifications of sedimentary budget in the coastal region, together with other engineering works have led to an increased pressure on the coastal area and development of multiple erosion sectors, with important impacts on the economic activities (loss of beach areas for touristic purposes) or biodiversity (through habitat degradation). Thus, the current service will develop tools to analyze and monitor, based on time series of high resolution satellite data (Sentinel-2), the evolution of submerged sandbars, which are natural bathymetric features with significant role in coastal protection. |
| Earth Observation Training Data Lab (EO-TDL) | One of the most limiting factors of ML and AI for EO applications is the scarcity of suitable and accessible training datasets. Currently, the main barrier is that the generation of such datasets is a time consuming and expensive process. [...] | EARTHPULSE SPAIN, SL (ES) | AI4EO | applications, Sentinel-1, Sentinel-2 | One of the most limiting factors of ML and AI for EO applications is the scarcity of suitable and accessible training datasets. Currently, the main barrier is that the generation of such datasets is a time consuming and expensive process. Typically access to high quality training datasets is very restricted; in some cases, domain experts or in-situ data annotation campaigns are necessary to generate the ground truth for remote sensing applications. Consequently, the field of AI/ML for EO is lagging when compared to other sectors, hindering the development of new applications that can fully exploit AI capabilities. The ESA Earth Observation Training Data Lab (EO-TDL) will address these key limitations by providing a cloud repository to create, share, and improve training datasets as well as ML/DL algorithms. The goals of EO-TDL are: host, import and maintain a wide range of dataset types: training, validation, test, benchmark and reference datasets (in-situ data, product validation datasets) offer a set of integrated open-source tools compatible with the major ML/DL frameworks to develop and export processing pipelines for Extract Transform Load (ETL) operations, data ingestion, model training and inference enable the description, versioning and tracking of data using Spatio Temporal Asset Catalog (STAC) to guarantee data discoverability and accountability allow data exploration to uncover biases, detect anomalies, verify assumptions maximizing the understanding of the data (Exploratory Data Analysis – EDA) build a centralised Feature Store to access, search, create EO data derived features and serving them at training and inference time thus increasing model efficiency enable automated data quality mechanisms through deterministic and non-deterministic testing deploy a containerized multi-GPU environment for distributed training processing provide interoperability with third party platforms, such as Radiant Earth MLHub implement accessibility at multiple levels by means of user interfaces, web APIs, CLIs and Python libraries Moreover, community engagement will be incentivised through a reward-mechanism to stimulate collaboration in dataset creation, enhancement and quality assurance. All the code will be hosted on GitHub and a public Discord server will enable further discussion between members. Within the first year of activity the data population will comprise over 100 selected datasets covering a wide range of applications: from computer vision tasks (such as object detection), super resolution to bio/geophysical parameter estimation or 3D applications on different data sources (such as Sentinel 1 and 2, Airbus SPOT and PLEIADES, UAV imagery or vector data). Many users will benefit from this training data laboratory: the availability of quality training data will strengthen science and industry capabilities of exploiting EO data as a whole helping accelerate EO market penetration. Researchers and engineers can take advantage of using EO-TDL to build highly accurate models of the Earth system such as Digital Twin Earth simulations. |
| Earth Observing Dashboard | A Tri-Agency Dashboard by NASA, ESA, JAXA International collaboration among space agencies is central to the success of satellite Earth observations and data analysis. These partnerships foster more comprehensive measurements, robust datasets, [...] | NASA, JAXA and ESA (IT) | Digital Platform Services | covid19, platforms, science | A Tri-Agency Dashboard by NASA, ESA, JAXA International collaboration among space agencies is central to the success of satellite Earth observations and data analysis. These partnerships foster more comprehensive measurements, robust datasets, and cost-effective missions. The tri-agency COVID-19 Dashboard is a concerted effort between the European Space Agency (ESA), Japan Aerospace Exploration Agency (JAXA), and National Aeronautics and Space Administration (NASA). The dashboard combines the resources, technical knowledge and expertise of the three partner agencies to strengthen our global understanding of the environmental and economic effects of the COVID-19 pandemic. Use the dashboard to explore environmental and economic indicators based on remote sensing data from ESA, JAXA and NASA, and investigate how social distancing measures and regional shelter-in-place guidelines have affected Earth’s air, land, and water. Explore individual countries and regions across the world to see how the indicators in each specific location have changed over time. EO Dashboard Hackathon From June 23- 29, coders, scientists, entrepreneurs, designers, storytellers, makers, builders, artists, technologists, and space enthusiasts from around the world joined NASA (National Aeronautics and Space Administration), ESA (European Space Agency), and JAXA (Japan Aerospace Exploration Agency) for the all-virtual, global Earth Observation Dashboard Hackathon. Go to the hackathon webpage. |
| Earth System Data Lab (ESDL) | The main objective of the Earth System Data Lab (ESDL) project is to establish and operate a service to the scientific community that greatly facilitates access and exploitation of the multivariate data set in the ESDL and by this means advances [...] | BROCKMANN CONSULT GMBH (DE) | Science | land, marine environment, oceans, platforms, science | The main objective of the Earth System Data Lab (ESDL) project is to establish and operate a service to the scientific community that greatly facilitates access and exploitation of the multivariate data set in the ESDL and by this means advances the understanding of the interactions between the ocean-land-atmosphere system and society. To this end, the main tasks of the project fall into four main categories: infrastructure and operations, data sets and tools, use cases and scientific exploitation, and communication and outreach. The core part of the ESDL is the data in analysis-ready form, together with tools and methods to generate, access, and exploit the ESDL. The software to generate the ESDL and the data access APIs have been developed in the preceding project CAB-LAB. The modular open source approach adopted in CAB-LAB has proven to be convenient, flexible, and powerful and effectively meets user requirements. ESDL further evolves the range of available tools according to the requirements formulated by the different user groups of the service, while users may also contribute their own solutions and share them with others on github. The project continuously extends the datasets included in the ESDL. The additions imply both extending the data coverage in time as well as the introduction of completely new data sets. Examples for specific requirements include marine parameters and the missing parameters from ESA’s CCI programme, e.g. Land Cover, Clouds, Aerosols, and Green House Gases. As for the software part, the main objective for these additions is to increase the ESDL’s utility and versatility and thus ultimately the uptake of scientific users, who will then have a powerful tool to advance our understanding of the Earth system dynamics. User uptake and scientific exploitation through the implementation of use cases is actively promoted by several tasks. The project adopts a three-stage approach and accordingly defines three different user types, Champion Users (CU, pre-defined use cases), Early Adopters (EA, Open call), and the Scientific Community (SC, free use). All ESDL users have in common that they are using the ESDL for scientific exploitation. While doing so, they are helping to improve the ESDL and the service provided, to increase the awareness for this activity and the offered service, and to extend the ESDL by contributing own source code and data sets. The ESDL is complemented by extensive outreach, communication, and training activites, which will foster user uptake, empower users to optimally exploit the ESDL, and eventually yield tangible scientific results in the form of peer-reviewed articles in international journals. Champion Use Cases: Four Champion use cases will be implemented in collaboration with distinguished experts to demonstrate the wide range of different approaches that may be adopted with the ESDL: EM-DAT: Environmental conditions during societal catastrophes GEO-BON Colombia: Supporting regional initiatives in Colombia towards an Ecological Observation System Marine NPP: Primary productivity models in the ocean MDI: Biogeochemical Model Optimization Results: The Data Lab is accessible via registration https://www.earthsystemdatalab.net/index.php/interact/data-lab/ User Guide and Source code for Python and Julia https://www.earthsystemdatalab.net/index.php/documentation/user-guide/ The Earth System Data Lab is available on the Euro Data Cube https://eurodatacube.com/ |
| EARTH-CODE: EARTH SCIENCE COLLABORATIVE OPEN DEVELOPMENT ENVIRONMENT | EarthCODE (Earth Science Collaborative Open Development Environment) has the objective to: enable adoption of FAIR Open Science Principles throughout ESA-funded Earth System Science activities, to deliver long-term persistence of data, [...] | TELESPAZIO VEGA UK LIMITED (GB) | Science | open science, platforms, science hub | EarthCODE (Earth Science Collaborative Open Development Environment) has the objective to: enable adoption of FAIR Open Science Principles throughout ESA-funded Earth System Science activities, to deliver long-term persistence of data, code and documentation, aiding reproducibility, reuse and consumption of research outputs by a wider community. EarthCODE brings existing pieces together in a single, open-access solution for ESA scientific activities, offering an Open access cloud-based development environment leveraging on federated EO platforms, with: Scalable computing, tools for FAIR management of open data, open-source code, documentation Guidelines, community management, and support to use the tools and apply the principles in practice, including for activities that use own institutional computing resources Persistent storage, cataloguing and discovery services for the activities’ research outputs EarthCODE is being developed incrementally, with subcontractors being selected via annual Best Practice procurements. These Best Practice procurements will address three main Work Streams: Infrastructure and Services – looking to integrate cloud computing services from EO Platforms with the EarthCODE Portal. FAIR Open Science – looking to integrate tools for the management of Open Data and Open Source Software Community – looking to manage and develop the community of scientists contributing to and using EarthCODE Community manager for EarthCODE: Alasdair Kyle <Alasdair.Kyle@telespazio.com> |
| EARTHSIGNATURE_AI | Monitoring of cropland has been critical for several national and international programmes (e.g., Sustainable Development Goals – #2 Zero Hunger, European Common Agriculture Policy). Furthermore, early identification of crops is becoming more [...] | CS SYSTEMES D’INFORMATION (FR) | Enterprise | artificial intelligence, land cover, permanently open call, sustainable development | Monitoring of cropland has been critical for several national and international programmes (e.g., Sustainable Development Goals – #2 Zero Hunger, European Common Agriculture Policy). Furthermore, early identification of crops is becoming more stringent in the context of climate change that can influence severely crop yields in some parts of the world. Given the size of te areas to be addressed and the volume of demand, EO based crop monitoirng must increasingly utiliuze AI based approaches. However, cropland classification is a challenging topic because of the constantly changing radiometric signature of crops due to seasons and weather and climatic conditions. This requires the development of a system capable of taking seasonal and weather and climatic variations into account. WIthin the framework of AI based approaches, in order to be economically sustainable, processing costs must also be reasonable. This project is addressing the entire processing and analysis chain for usiing ML analysis of EO data for crop classificaiton. This includes the identifiaction of which available land cover dataset(s) can provide the best levels of crop information and quality to perform an efficient and conclusive study while meeting specific user needs related to crop monitoring, testing different neural network (NN) configurations, including different input datasets and different approaches to represent data time-series as NN input which are then compared with a baseline classical approach and finally testing different Cloud computing configurations, including the use of the GPU. Beyond the calculation time assessment, this objective will inform on the trade-off between calculation time and platform configuration costs. |
| Ease QC – Development of a Service to detect anomalies in Earth Observation data using AI (Artificial Intelligence) models | The EASEQC project aimed at expanding the use of AI/ML for quality control of EO products. The traditional approach to quality control, usually involving deterministic models together with considerable manual intervention, is no longer feasible [...] | TELESPAZIO VEGA UK LIMITED (GB) | Digital Platform Services | artificial intelligence, generic platform service, permanently open call, platforms | The EASEQC project aimed at expanding the use of AI/ML for quality control of EO products. The traditional approach to quality control, usually involving deterministic models together with considerable manual intervention, is no longer feasible given increasing data volumes of EO data archives. ML/AI has potential to make the process of quality control more efficient. EASEQC focused on the development of semi-supervised ML models for detection anomalies in EO products. This entailed that models can be trained with limited training data and that a model is capable of identifying generally anomalous data products i.e. different anomalies can be detected by the same model. The service has been implemented in a cloud environment and is accessible via an API. Overall, the outcome of the project has seen significant steps made towards the establishment of an operational Ease QC service. Further work is still required to improve the ML models, but the infrastructure successfully developed by the project both with respect to the development of the ML models, and their deployment / operation alongside the data (be that on the cloud or otherwise) is an extremely significant development with respect to the long term objectives of the Ease QC team. |
| Education Platform | This activity has produced a data cube based browser for educational purposes. | SINERGISE LTD. (SI) | Digital Platform Services | platforms, training and education | This activity has produced a data cube based browser for educational purposes. |
| EO AFRICA – Water Resources Management (WRM) | The project plans to estimate crop water stress and evapotranspiration, exploiting ECOSTRESS and PRISMA data by experimental EO analysis techniques. Expected outcome: an open source innovative model will be developed to assess actual crop [...] | Planetek Italia (IT) | Applications | crop, EO Africa, Explorer, water resources | The project plans to estimate crop water stress and evapotranspiration, exploiting ECOSTRESS and PRISMA data by experimental EO analysis techniques. Expected outcome: an open source innovative model will be developed to assess actual crop evapotranspiration (ETa) using EO-derived crop coefficient (Kc) and crop water stress index (CWSI). The solution will be integrated into a web platform as a Decision Support System (DSS) to improve irrigation water management. Demonstration test site: large cultivated area (13.800 ha) located in northern Egypt. |
| EO AFRICA Earth Observation system to Manage Africa’s food systems by Joint-knowledge of crop production and Irrigation digitization – EO-MAJI | Primary objective of this project is to utilize the unique spatial, spectral and temporal characteristics of ECOSTRESS thermal sensor and PRISMA hyperspectral sensor to develop novel methods addressing the growing challenges affecting the nexus [...] | AGENCIA ESTATAL CONSEJO SUPERIOR DE (ES) | Applications | africa, agriculture, crops and yields, EO Africa, Explorer, Food Security, hyperspectral, water cycle and hydrology | Primary objective of this project is to utilize the unique spatial, spectral and temporal characteristics of ECOSTRESS thermal sensor and PRISMA hyperspectral sensor to develop novel methods addressing the growing challenges affecting the nexus of water resource management and food security in Africa. Irrigated agriculture is right in the centre of those two domains and the project monitors irrigation schemes with the aim of inventorying existing perimeters and improving their performance, enhancing the management of water licensing and permits and laying ground for sustainable development of irrigated agriculture in Africa. This will be achieved through development and application of state-of-the-art evapotranspiration modelling making full use of ECOSTRESS and PRISMA data. |
| EO AfRIca ExplorerS – ARIES | Within “ARIES” experimental EO analysis techniques will be developed and validated, addressing water resources management and food security matters. Those techniques,algorithms and prototype solutions will leverage a new generation of [...] | VISTA GEOWISSENSCHAFTLICHE FERNERKUNDUNG GMBH (DE) | Applications | africa, agriculture, agriculture science cluster, applications, EO Africa, Explorer, Food Security, hyperspectral, Sentinel-2, Sentinel-3, water cycle and hydrology | Within “ARIES” experimental EO analysis techniques will be developed and validated, addressing water resources management and food security matters. Those techniques,algorithms and prototype solutions will leverage a new generation of upcoming operational EO data: thermal and hyperspectral. In addition to established EO resources, especially Copernicus driven Sentinel-2 and Sentinel-3, the intended ECOSTRESS and PRISMA data will deliver urgently needed new insights in status and processes in water resources management and food security issues. |
| EO AFRICA Food Security and Safety in Africa – AFRI4Cast | Afri4Cast project will develop a modeling platform making full exploitation of satellite remote sensing of PRISMA and ECOSTRESS sensors for climate change impact analyses on agriculture and making it available to African stakeholders for shaping [...] | AGROAPPS PC (GR) | Applications | africa, agriculture, agriculture science cluster, crops and yields, EO Africa, Explorer, Food Security, hyperspectral | Afri4Cast project will develop a modeling platform making full exploitation of satellite remote sensing of PRISMA and ECOSTRESS sensors for climate change impact analyses on agriculture and making it available to African stakeholders for shaping future agricultural policies in the African Continent. Afri4Cast will provide national-, regional-, parcel-, pixel-specific in season production estimates, mycotoxin formation risk and disease outbreak probability. Apart from the in-season yield forecast production line, AFRI4CAst will execute seasonal and long-term model simulations for multiannual yield predictions and mycotoxigenic fungi contamination risk under various climate scenarios at a coarse spatial scale. |
| EO AFRICA HyRELIEF: Enhancing ECOSTRESS drought monitoring with hyperspectral narrowbands | HyRELIEF will exploit hyperspectral narrowbands (HNBs) captured by Hyperspectral Precursor and Application Mission (PRISMA) and employ a co-production approach with knowledge users to increase the reliability and usability of ECOSTRESS ET and [...] | UNIVERSITY OF TWENTE (NL) | Applications | africa, EO Africa, Explorer, Food Security, hyperspectral, water cycle and hydrology | HyRELIEF will exploit hyperspectral narrowbands (HNBs) captured by Hyperspectral Precursor and Application Mission (PRISMA) and employ a co-production approach with knowledge users to increase the reliability and usability of ECOSTRESS ET and ESI for drought monitoring in Kenya. |
| EO AFRICA Integrated use of multisource remote sensing data for national scale Agricultural Drought Monitoring in Kenya (ADM-Kenya) | ADM Kenya project aims to co-develop solutions for monitoring crop condition and cropping systems with EO time-series observations to derive evidence-based quantitative vegetation condition estimates with high spatial and temporal resolution. We [...] | Leibniz Centre for Agricultural Landscape Research (ZALF) (DE) | Applications | africa, agriculture, crops and yields, EO Africa, Food Security, National Incubator | ADM Kenya project aims to co-develop solutions for monitoring crop condition and cropping systems with EO time-series observations to derive evidence-based quantitative vegetation condition estimates with high spatial and temporal resolution. We will develop novel EO-based solutions for drought monitoring at a national scale in Kenya. ADM Kenya will provide cloud-based processing algorithms that will allow improving spatially explicit drought hazard/impact analysis. Furthermore, the project aims to develop drought-relevant agricultural information. This includes high-resolution crop management information based on multisource remote sensing data such as irrigation (at a national level) and contextual (localized) information on cropping practices (for pilot areas). For contextualization/validation, we develop innovative data fusion approaches based on field observations. |
| EO AFRIca multi-scale SMART agricultural water management – AFRI-SMART | The project investigates how sustainable agriculture can be achieved in the Africa continent under drought conditions, by co-developing innovative scientific EO-based and state-of-the-art modelling solutions together with African experts [...] | POLITECNICO DI MILANO (IT) | Applications | africa, agriculture, crops and yields, EO Africa, Food Security, National Incubator | The project investigates how sustainable agriculture can be achieved in the Africa continent under drought conditions, by co-developing innovative scientific EO-based and state-of-the-art modelling solutions together with African experts increasing their knowledge and capacity, developing an operative platform and database for results visualization and sharing with the end-users. |
| EO Africa National INcubators – ANIN | The ANIN projects aims to:Develop and validate, together with South African experts, innovative EO-based solutions addressing drought monitoring at national scaleInvolve South African end-user entities throughout the project and facilitate [...] | GMV AEROSPACE AND DEFENCE, SA (ES) | Applications | africa, EO Africa, Food Security, National Incubator, water cycle and hydrology | The ANIN projects aims to: Develop and validate, together with South African experts, innovative EO-based solutions addressing drought monitoring at national scale Involve South African end-user entities throughout the project and facilitate integration of the developed solutions into their current operational working practices demonstrating the achieved benefits Fully exploit the capacity offered by ESA EO missions in synergy with state-of-the-art models and non-EO data and leverage on cutting edge information technologies |
| EO AFRICA PRISMA 4 AFRICA | This project aims to exploit new opportunities offered by the EO technological advances, in order to favour the development of EO local experts in Africa, by providing geospatial information and natural resources mapping/monitoring. Policy [...] | E-GEOS (IT) | Applications | africa, crops and yields, EO Africa, Explorer, hyperspectral | This project aims to exploit new opportunities offered by the EO technological advances, in order to favour the development of EO local experts in Africa, by providing geospatial information and natural resources mapping/monitoring. Policy makers and relevant regional stakeholders (”Early Adopters”) will take a direct advantage on the availability of EO products describing the status of the cultivar within their agricultural areas of interest. |
| EO AFRICA RAngeland MONitoring for Africa using earth observation – RAMONA | RAMONA aims for developing an innovative monitoring system for rangeland ecosystems in Africa at the continental scale and at 10m resolution. It will exploit the full data record provided by the Sentinels (primarily Sentinel-1 SAR, Sentinel-2 [...] | AARHUS UNIVERSITY (DK) | Applications | africa, Continental Demonstrator, EO Africa, land cover, SAR, Sentinel-1, Sentinel-2, Sentinel-3 | RAMONA aims for developing an innovative monitoring system for rangeland ecosystems in Africa at the continental scale and at 10m resolution. It will exploit the full data record provided by the Sentinels (primarily Sentinel-1 SAR, Sentinel-2 multi-spectral supported with Sentinel-3 multi-spectral), taking advantage of the synergies offered by SAR and multi-spectral observations. The activity will develop a suite on dedicated products, including as core products rangeland type/extent, herbaceous above ground biomass and biomass. Further a set of experimental products is being developed including herbaceous biomass anomalies, near real time phenology and carrying capacity. |
| EO AFRICA Research and Development Facility | The flagship of the EO AFRICA initiative is the EO AFRICA R&D Facility. The overarching goal of the Facility is to foster an African-European R&D collaboration enabling an active research community and creative innovation processes for [...] | UNIVERSITY OF TWENTE (NL) | Applications | africa, applications, EO Africa | The flagship of the EO AFRICA initiative is the EO AFRICA R&D Facility. The overarching goal of the Facility is to foster an African-European R&D collaboration enabling an active research community and creative innovation processes for continuous development of EO capabilities in Africa. The R&D Facility will review the African EO research challenges and issue research calls for addressing the most relevant ones. It will offer modern cloud computing & digital tools for the researchers and support a range of collaborative activities and initiatives between the African and European research communities. |
| EO AFRICA Water Stress and Climate Indices for Africa – WASCIA | ‘Water Stress and Climate Indices for Africa’ (WaSCIA) is an ESA funded project that aims to deliver high-quality Water Stress and Climate Indices through an easy-to-use web interface to help the management of drought and water stress in [...] | TELESPAZIO VEGA UK LIMITED (GB) | Applications | climate, crops and yields, EO Africa, National Incubator, water resources | ‘Water Stress and Climate Indices for Africa’ (WaSCIA) is an ESA funded project that aims to deliver high-quality Water Stress and Climate Indices through an easy-to-use web interface to help the management of drought and water stress in Africa. The project is led by Telespazio UK with the partnership of RSS-Hydro, Telespazio France, AGRHYMET (Centre Regional de Formation et d’Application en Agrométéorologie et Hydrologie Opérationnelle), LPAOSF (Laboratoire Physique de l’Atmosphère et de l’Océan Simeon Fongang) and DGPRE (Direction de la Gestion et de la Planification des Ressources en Eau Sénégal). The benefits of an effective drought monitoring solution include: Detection of early onsets of water stress related to drought conditions, its severity and spatial extent Improvement in understanding water-crop productivity in the long term Assisting yield forecasting efforts and food security The solution aims to deliver weekly water stress information derived from Earth Observation (EO) data and climate indices derived from ERA5 reanalysis data. It will provide this information at national level for Senegal, with the goal of being extended to other African countries. The service will leverage on open-source innovative information technology and be deployed using an existing cloud-based platform, Web Advanced Space Developer Interface (WASDI). A decision support tool will provide end users with threshold warning information that will help to manage risks associated with drought conditions. Project consortium Telespazio UK (a Telespazio Group company) is an experienced consulting, technology, engineering, space operations and service development business headquartered in Luton, UK. The company has built its first-class reputation, through >40 years of working in the UK space industry, by exploiting technology developments in Earth Observation and Satellite Navigation & Communications, pioneering innovative services in space operations and applications. RSS-Hydro, a Luxembourg R&D company founded in 2017, is a single-entity business, with activities focusing on innovative uses of remote sensing and space technologies for geospatial services in environmental applications. The company’s activities pivot around three business pillars: research and development, commercial products and services, and expert consulting. RSS-Hydro’s main business consists of developing science-driven products and services focusing on environment and water-related hazards and risks, in particular floods, using computer simulations and remote sensing technologies. Telespazio France, the French subsidiary of the Telespazio Group operates in the main space markets of telecommunications, earth observation, navigation, and satellite operations. Telespazio France has a complete range of Earth Observation tools and algorithms; and offers high value-added products and services in fields as varied as defence, maritime surveillance, agriculture, insurance and the environment. Through its involvement in major European programmes such as Galileo, EGNOS and Copernicus, Telespazio France confirms its experience in managing large-scale projects in the field of spatial geo-information. Centre Régional de Formation et d’Application en Agrométéorologie et Hydrologie Opérationnelle (AGRHYMET), a specialised agency of the Permanent Inter-State Committee against Drought in the Sahel (CILSS) composed of nine member States, including Senegal. It aims to achieve food security and increased agricultural production in the member States and to improve natural resources management in the Sahel region by providing training and information to development stakeholders and partners. It is also a regional institute specialised in the science and techniques applied to agricultural development, rural development and natural resource management. AGRHYMET has participated in previous ESA studies (including AQUIFER) and has long established links with African end users which will be leveraged upon within this project. Laboratoire Physique de l’Atmosphère et de l’Océan Simeon Fongang (LPAOSF), who, within the Université Cheikh Anta Diop (UCAD) in Dakar has a strong track record in international interdisciplinary research on climate and its impacts. LPAOSF has more than 17 years of experience in working with African climate services, governments, and national and international NGOs, and in conducting large-scale interdisciplinary projects. Direction de la Gestion et de la Planification des Ressources en Eau (DGPRE), a department under the remit of the Senegal Ministry of Water and Sanitation in Senegal, in charge of the management and planning of Senegalese water resources. DGPRE has established links with end users in Senegal which will be leveraged upon within this project. |
| EO BALTIC PLATFORM FOR GOVERNMENTAL SERVICES (EO-BALP) | The goal of the EO-BALP project is to develop a cloud service platform for Earth Observation (EO) data access and processing and provide six different applications that will demonstrate the practical use of satellite data in different [...] | Baltic Satellite Service (LV) | Enterprise | agriculture, Baltic, clouds, coastal processes, human settlements, natural hazards and disaster risk, platforms, water quality | The goal of the EO-BALP project is to develop a cloud service platform for Earth Observation (EO) data access and processing and provide six different applications that will demonstrate the practical use of satellite data in different domains: Monitoring application of infrastructure and settlements with more than 60,000 inhabitants, which will help to detect and characterize ground movements from satellite data, and to identify dangerous places in infrastructure protection zones; A water quality monitoring application that will help determine water quality and pollution, as well as pollution sources in the Baltic Sea, coastal waters and inland waters; A forest change monitoring application, which will help to regularly detect clear-cuts and wind falls, as well as forest damage caused by diseases, pests, fires, water, etc.) and will provide the latest satellite data mosaic service in all Baltic countries; An agricultural land monitoring application that will help to assess crops, yield, soil quality, generate burnt area map delineating agricultural lands affected by grassland fires and flooded agriculture field areas. Natural resource extraction monitoring application that will help identify illegal resource extraction sites (sand, gravel, etc. mineral resources); A maritime monitoring application that will help identify ships, their type, location and movement. To achieve the technical goals, the initial phase of the project will gather business and functionality requirements from potential end users of the platform, who will also be involved in testing and validating the applications. Currently, various organizations from all Baltic countries have shown their interest in the project and in the possibility of using satellite data, such as the cities of Tallinn and Riga, the Environmental Protection Agency under Ministry of Environment of Lithuania, the Klaipeda State Seaport Authority, the Latvian State Forest Service, the Latvian Peat Association, the Latvian Institute of Aquatic Ecology and many others. The new EO-BALP platform is planned to be designed in such a way that it can be easily used by users without specific knowledge and also by professionals in the field. The EO platform will enable all participating stakeholders in the three Baltic countries to deploy, operate and deliver EO-based services to national governments and institutions. The platform will therefore support activities allowing users to discover and select data, pre-existing processing services, EO based services, products and applications, visualize and analyze them or select and apply data manipulation tools to the result. The Platform will also allow users to discover and select data samples and software components, upload and validate applications and deploy them on the platform for use also by other users. Users will be able to authenticate, upload and deploy a new application software, discover and select data, process the data and eventually publish the resulting product. In addition, the interoperability of EO Platform with existing e-government platforms will be ensured, by: importing existing geospatial data from governmental and other public/private entities to the platform to be used for provision of specialised services; developing functionality allowing to integrate XYZ/TMS, WMS web services and JSON/GeoJSON data from governmental and other public/private entities directly into specialised service web applications; publishing all geographic data produced by specialised applications based on standard and widely used web service formats (XYZ/TMS, WMS, GeoJSON) which allow using them by governmental and other public/private entities in their own web applications and in desktop GIS software (QGIS, ArcGIS, etc). |
| EO Clinic: Agricultural Statistics Data Collection Support in the Cook Islands | EO Clinic support requested by: Asian Development Bank (ADB), Statistics and Data Innovation Unit within the Office of the Chief Economist and Director General (EROD-SDI) of the Economic Research and Regional Cooperation Department [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | EO Clinic support requested by: Asian Development Bank (ADB), Statistics and Data Innovation Unit within the Office of the Chief Economist and Director General (EROD-SDI) of the Economic Research and Regional Cooperation Department (ERCD) Requesting activity: Data for Development (Phase II) – KSTA 9646 Requesting activity type: Knowledge Support Technical Assistance (KSTA) EO Clinic relevant Thematic Groups: TG1 (Agriculture) Work Order number: EOC0026 Work Order status: Under Execution Work Order start: 2021 Nov 26 Work Order end: Background Agriculture and fisheries remain at the forefront of Cook Islands economic growth strategy. The agriculture sector provides a livelihood for many people and is important for food production and food security. The country’s development strategy focuses on increasing agricultural production to improve food security and nutrition, within the framework of sustainable natural resources management and improving quality of life. The key to crafting effective policies to support these goals is the availability of reliable statistics. Three agricultural censuses were undertaken in the country – in 1988, 2000, and 2011. The Government has decided to carry out another census: the Census of Agriculture and Fisheries 2021 (CoA 2021) to gather data on changes in the structure of the agriculture sector over the last ten years, as well as key data to help monitor the SDGs. The Asian Development Bank (ADB) Knowledge Support Technical Assistance (KSTA) 9646 Data for Development (Phase II) aims to enhance the capacity of the national statistical systems (NSSs) of selected developing member countries in support of the Sustainable Development Goals (SDGs). The KSTA’s intended impact is increased data-driven monitoring of development goals and evidence-based policymaking. Its expected outcome is enhanced capacity of NSSs to meet the data requirements of the 2030 Sustainable Development Agenda. The Sampling component particularly for the agricultural statistics of KSTA 9646 will focus on the implementation of a post-census validation activity in selected pilot countries, including in the Cook Islands, to fine-tune the results of the country’s Census of Agriculture. The activities will focus on the application of sampling techniques and employment of land measurement methods to validate national parcel area estimates significant at the provincial level. Further, ADB will support the implementing agency in comparing the farmer estimates with satellite-based location data, and possible use of remote sensing data as an auxiliary data source. The results of the data collection will be used to improve the census data estimates on agricultural landholdings, which form the basis for various program planning activities and policy formulation in the agriculture sector. Problems to be Addressed and Geospatial Information Gaps The collaboration between ADB and the Cook Islands Ministry of Agriculture aims to assess the utility of an area sampling frame approach to estimate the area of land utilised for crop production. In the area frame approach, the sampling units for enumeration are defined by a geometric grid, usually points, squares, or circles. A multistage stratified approach can then be implemented based on an area frame to select a sample of grids within each stratum of land cover and/or land use, depending on the survey objective. For census and survey mapping, an accurate land use and land cover map would provide an updated baseline that can be useful in several phases of statistical analysis, more specifically in relation to stratification. Subsequently, this enables the generation of an updated frame that improves the efficiency of sample allocation, selection, and estimation. Information Services to be Delivered Service 1: Land Use/Land Cover Mapping Service 2: Expansion of Coverage Service 3: Concept Note for a Future Service on Further Pilot Areas | ||
| EO Clinic: Assessment of the Potential of Gum and Resin-Bearing Tree Species in Ethiopia | EO Clinic support requested by: GIZ Ethiopia Requesting activity: Assessment of the potential of Gum/Resin bearing tree species in the Horn of Africa Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: [...] | E-GEOS (IT) | EO Clinic support requested by: GIZ Ethiopia Requesting activity: Assessment of the potential of Gum/Resin bearing tree species in the Horn of Africa Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG6 (Forestry) Work Order number: EOC0028 Work Order status: KO Pending Work Order start: Work Order end: Background The GIZ country programs include different activities surrounding natural products. The natural products of interest include honey and beeswax, but more particularly the promotion of supply chains for gums and resins. These are saps and exudates of indigenous tree species, such as frankincense, myrrh or Gum Arabic. The products are traded on domestic and international markets. Internationally they find applications in the food, cosmetic, pharmaceutical industry and in aromatherapy. The trade value of these products goes into millions of US$. Probably most known are frankincense (used as a scent in Catholic churches and in aromatherapy) and Gum Arabic (used as an anti-coagulant in soft drinks like Coca-Cola). Sudan is the largest supplier of Gum Arabic in the world, covering about 85% of the world market. The GIZ programs which involve natural products as an activity are three: Biodiversity (myrrh, honey), Green Innovation Center (mainly honey and waxes), and Cross-border Cooperation West-Ethiopia/East Sudan (gums/resins). All projects within these programmes have in common that they want to support measures to help smallholders become involved into such supply chains. At present the GIZ SDR (strengthening drought resilience) Program has no measures in place but the potential is there and there is interest in working with potential EO products. Problems to be Addressed and Geospatial Information Gaps A recent GIZ-commissioned study revealed that Ethiopia has a large potential to provide gums/resins and honey/wax products, which is entirely underutilised. Findings from this study are: 1) Defining the size of the natural resource is critical, at present there is no estimation on how large the resource is; 2) There is no knowledge on which environmental parameters are connected with the natural re-source (soils, water situation, altitude, etc.); 3) There is no information on the health status of the tree population; 4) Scientists and interviewees especially mentioned the regeneration as one of the major critical issues; and 5) There are estimates over the distribution of the different species but they seem to be outdated and inaccurate. It is also worthwhile mentioning that the Convention on International Trade in Endangered Species (CITES) intends to protect gum and resin-bearing species. This would mean that the trade becomes restricted at the minimum, with unforeseen consequences for the collectors (most of them women actually). This should be seen in the context of the large amounts of money that are turned over with such products along the supply chain – at collectors’ level, at the level of processing and local trade, and as a forex income earner for exporting countries. A valuable trade can act as an incentive to better protect and sustainably use these resources. According to the above, the priority geospatial needs identified are: 1) size of the natural resource; 2) tree/population health status; 3) tree/species distribution; 4) tree regeneration; 5) density of stands; and 6) maturity of trees. Information Services to be Delivered Service 1: Classification of Gum and Resin-Bearing Tree Species Service 2: Assessment of Vegetation Health Service 3: Mapping Distinct Tree Species | ||
| EO Clinic: Characterisation of Dilijan National Park Forest Ecosystems, Armenia | EO Clinic support requested by: UNDP Armenia Office Requesting activity: Mountain Forest Ecosystems Transformations Digital Platform Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG6 [...] | GeoVille (AT) | Sustainable Development | ecosystems/vegetation, forestry, land cover, sustainable development | EO Clinic support requested by: UNDP Armenia Office Requesting activity: Mountain Forest Ecosystems Transformations Digital Platform Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG6 (Forestry) Work Order number: EOC0004 Work Order status: Completed Work Order start: 2020 May 06 Work Order end: 2020 Sep 25 Background Armenia is located at the junction of the biogeographic zones of the Lesser Caucasus and the Iranian and Mediterranean zones and exhibits both a great range of altitudinal variation and a diversity of climatic zones. Together, this has resulted in a diversity of landscapes and ecological communities with a distinct flora and fauna, including many regionally endemic, relict, and rare species. Across much of the country, these landscapes face moderate to severe deforestation and overgrazing pressures, corresponding in high rates of erosion, increasing soil salinity, lowered soil fertility, and loss of biodiversity. The main cause of land and forest degradation in North-Eastern Armenia, where the majority of the forests of the country are located is the deforestation and overexploitation of forest resources. Dilijan National Park is one of the four national parks of Armenia. Most of it is located in Tavush Province. It is known for its forest landscapes, rich biodiversity, medicinal mineral water springs, natural and cultural monuments, and extensive network of hiking trails. The National Park was established in 2002 on the basis of the Dilijan State Nature Reserve, which in its turn was established in 1958 on the basis of the former Dilijan and Kuybishev forest enterprises. The change of the status from state reserve to national park was conditioned by several objective reasons, such as inevitability of commercial activity in the area, presence of numerous settlements, including Dilijan town with its mineral water resorts, Yerevan-Ijevan railway line passing through its whole territory and others. Despite its unique biodiversity, rich natural-historical and cultural landscapes and huge eco-touristic potential, serious treats to ecosystems exists due to a dense population living within the national park, developed infrastructures, uncontrolled tourism, illegal logging, poaching and non-sustainable use of natural resources. In order to support the Armenian government strategy to rehabilitate degraded forests and increase forest cover significantly, in the Dilijan National Park area UNDP Armenia is focussing its efforts to better understand the past forest ecosystems transformations, the land use and land cover changes, and in general, all the socio-environmental processes in the past and today that affect the sustainable management of forest resources. In the earlier project “Mainstreaming sustainable land and forest management in mountain landscapes of north-eastern Armenia” in collaboration with the Global Environment Facility (GEF), UNDP Armenia concentrated efforts on analysing seven forest enterprises out of existing 19 forest enterprises in country. UNDP Armenia is looking to develop an updated methodology for forest inventory and management, also including satellite EO inputs. A successful demonstration of the methodology could essentially ease the way for activities planned for the remaining 12 forest enterprises and protected areas. Problems to be Addressed and Geospatial Information Gaps The required EO services shall be designed to reveal important lessons on management efficiencies for the Dilijan area as a state reserve (before 2002) and for Dilijan National Park (since 2002). Understanding the impact of population, infrastructure development and increasing tourism the forest ecosystems is crucial to develop more effective management and nature conservation measures. Information Services to be Delivered Service 1: Land Cover and Land Use Classification and Associated Changes Service 2: Forest Mapping Project Documents Work Order Report: EOC0004_WOR_V1.0.pdf |
| EO Clinic: Characterisation of Waste Sites Along the Lim River in Serbia | EO Clinic support requested by: UNDP Serbia Office Requesting activity: Automated Floating Waste Mapping Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG5 (Energy and Natural Resources), TG8 (Transport), TG9 (Urban), [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | Sustainable Development | energy and natural resources, rivers, surface water, sustainable development, transport, urban, water resources | EO Clinic support requested by: UNDP Serbia Office Requesting activity: Automated Floating Waste Mapping Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG5 (Energy and Natural Resources), TG8 (Transport), TG9 (Urban), TG10 (Water Resources Management) Work Order number: EOC0005 Work Order status: Completed Work Order start: 2020 Mar 18 Work Order end: 2020 Oct 05 Background Environmental protection continues to present challenges in Serbia, inadequate waste management being one of the most serious threats to the environment. River pollution, poor waste management in areas that can affect rivers, and illegal dumping are significant problems. UNDP Serbia needs help in identifying the exact locations and volume of waste along the rivers and thus provide input for the plans to remove the sources of pollution and prevent creation of new ones. This initiative is a part of UNDP’s support to the Serbian Ministry of Environmental Protection in their efforts to tackle the problem of floating waste in rivers, in particular in the Drina and Lim rivers. The Serbian ministry cooperates with environmental ministries in Bosnia and Herzegovina and Montenegro in a joint regional initiative, since the Drina and the Lim are transboundary rivers. An important aspect of the required support is mapping the illegal dump sites along the riverbeds. This waste gets into streams at times when water level rises, thus causing environmental harm to watercourses downstream, as well as economic losses (e.g. lost revenues from hydropower electricity generation, tourism, fishing, shipping). The UNDP Serbia project is in the concept phase. Apart from mapping (illegal) dump sites, the initiative also includes actions aimed at improving local waste management practices, local actions, and development of a roadmap for resource mobilisation by municipalities. UNDP Serbia is also coordinating the plans with the Ministry of Environmental Protection in order to exploit the synergy with their ongoing efforts on improving waste management nationally and regionally. Information Services to be Delivered Service 1: Waste Site Inventory Project Documents Work Order Report: EOC0005_WOR.pdf |
| EO Clinic: City Diagnostics and Action Planning in Bizerte, Tunisia | EO Clinic support requested by: African Development Bank Group (AfDB), Urban and Municipal Development Fund Requesting activity: AfDB African Cities Program: City Diagnostics and Action Planning Requesting activity type: Technical Assistance [...] | GeoVille (AT) | EO Clinic support requested by: African Development Bank Group (AfDB), Urban and Municipal Development Fund Requesting activity: AfDB African Cities Program: City Diagnostics and Action Planning Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG2 (Climate Change), TG3 (Coastal Zone Management), TG4 (Disaster Risk Management), TG8 (Transport), TG9 (Urban), TG11 (Non-EO Information and Analytics) Work Order number: EOC0025 Work Order status: Under Execution Work Order start: 2021 Dec 16 Work Order end: Background Rapid urbanisation and overwhelmed municipal administrations with insufficient resources lead to unplanned urban growth and insufficient infrastructure and service provision, negatively impacting sustainability and liveability of African cities. The results are uncontrolled sprawl, transit chaos, a widening infrastructure gap and environmental degradation. The African Development Bank’s African Cities Program tries to break this vicious cycle by providing evidence-based analysis and data for long-term development planning and by supporting cities with project preparation resources to turn plans into bankable projects, to be financed by downstream AfDB operations. Launched in 2020 with five cities, the Cities Program is working intensively with selected cities to undertake a comprehensive city diagnostic and through this develop a detailed action plan for overall UMDF support. In addition to the broader UMDF support outlined, the aim of the Bank in the pilot cities is to prioritise investments, preparing at least one urban infrastructure project investment to take to market. Furthermore, the Bank will support these cities with trainings, learnings and dialogue, by connecting them to other cities in Africa and beyond, as well as other institutions in the urban development space. Through this the Bank will establish a network of reform-minded municipalities, working towards sustainable, productive and liveable urban development. Problems to be Addressed and Geospatial Information Gaps One critical barrier in the path towards sustainable urban development is the capacity to understand spatial data and use this data for planning of long-term city growth and infrastructure investments. Spatial data and the technologies related to it, such as remote sensing, can be powerful tools to overcome such barriers, allowing a better understanding of the dynamics of urban growth. Connecting development priorities and spatial data makes it possible to have a better localisation and specification of interventions. Geospatial data and maps are scarce in the Tunisian context, and typically outdated or of low quality. This often hampers understanding the spatial dimension and making of location-based decisions. In the case of Bizerte city and governorate, the Bank and its partners are seeking to better understand the present situation and past evolution of the basic land use and land cover, trunk urban infrastructure and climate change risks in general. Information Services to be Delivered Service 1: Urban Land Use/Land Cover Classification and Associated Changes Service 2: Regional Land Use/Land Cover Classification and Associated Changes Service 3: Climate Change-Related Risk Mapping | ||
| EO Clinic: COVID-19 Impact on Agricultural Practices in Moldova | EO Clinic support requested by: UNDP Moldova Office Requesting activity: Collaborative UNDP platform response to COVID-19 Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG11 [...] | E-GEOS (IT) | Sustainable Development | agriculture, covid19, sustainable development | EO Clinic support requested by: UNDP Moldova Office Requesting activity: Collaborative UNDP platform response to COVID-19 Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG11 (Non-EO Information and Analytics) Work Order number: EOC0007 Work Order status: Completed Work Order start: 2020 May 28 Work Order end: 2020 Sep 18 Background The impact of the COVID-19 crisis on a small and open economy and a fragile local business community as the one in the Republic of Moldova is expected to be significant. The crisis is transforming the landscape, new business models will be adopted, once solid supply chains will disappear, and new ones will be established. The vulnerable groups in Moldova will disproportionately suffer from the crisis and the losses due to decreased mobility and economic activity. The rising income and non-income inequalities will affect the modest yet positive achievements of the country and its people when it comes to achieving the localized SDGs. With around 1 million of migrant Moldovans abroad, and given the deteriorating conditions in many destination countries, migration is an important crisis transmission channel and declining remittances will hardly hit the local economy. Under the current circumstances and given the unpredictable and complex conditions in which we all operate on the ground, the Government of Moldova managed to come up with specific targeted immediate response measures (for the duration of the State of Emergency) and specific short-term initiatives to support the most vulnerable people and the business community. While such measures are lifesaving for many, a comprehensive impact assessment is required to understand the depth of the crisis and provide for medium and long-term measures commensurable with the negative impact and responding to the local emerging needs. Moreover, additional robust evidence is needed by the Government to take rapid tactical decisions to minimize spread and the future losses due to the impact of the crisis on the social, economic and environmental dimensions of human development. In order to respond to the current crisis, raise awareness of the central and local administrations, support with evidence-based decision making, and assess the impact of the crisis induced by the COVID-19 pandemic, UNDP and the Government are merging efforts to create a national collaborative platform for new evidence, to include satellite Earth Observation, big data (in particular on mobility) and other types of data in a multi-layered platform with multiple points and levels of access and visualisation of core products at national level, with the possibility to zoom in at the most granular level. Problems to be Addressed and Geospatial Information Gaps Geospatial EO data is missing to a large extent and not used in Moldova and other countries in this region for development purposes. Moreover, given the current COVID-19, EO and other new types of data is urgently required to provide for: 1) Additional evidence around what is happening on the ground; 2) Improve situational awareness of the local authorities around COVID-19 and spread; 3) Support in assessing the immediate and long-term social and economic impact of COVID-19; 4) Support in building an Early Warning System for the Government of the Republic of Moldova. Approximately 70% of the Moldovan population in rural areas depends on agriculture for their livelihoods. About 55% of the approximately 2 million ha of agricultural land is arable, and used for annual crop production: maize, wheat, sunflower, barley, oilseed, soybean, sugar beet. Highly fertile soils can be found mostly in the north of the country and the Dniester River Valley. Here, conditions are adequate especially for the production of cereal grains, maize, fruits (apples, plums, walnuts), vegetables, etc. In the current COVID-19 pandemic context, many of the Moldovans living in affected Western European countries (Italy, Spain, etc.) have returned or are returning to Moldova. It is believed this segment of the population is at the moment taking on employment opportunities in the agricultural sector, outside of urban areas. The limitations in mobility due to the pandemic, additionally to the influx of previously expatriated citizens creates a complex situation, with an obvious lack of overview information on the status and timing of the agriculture-related seasonal activities, and the possible impact on food production and supply chains. The present EO Clinic support will contribute to the monitoring of the agricultural production (focused on strategic crops) and the estimation of the impact of COVID-19 on the local agricultural practices, with particular focus on HVA (high value-added) agriculture. Information Services to be Delivered Service 1: Cropland Distribution and Status Service 2: Mobility Trends to Reveal Agricultural Practice Anomalies Project Documents Work Order Report: EOC0007_WOR_v01.pdf Final Presentation: EOC0007_FPR_v4.pdf |
| EO Clinic: COVID-19 Impact on Air Quality in Ukraine and the Republic of Moldova | EO Clinic support requested by: UNDP Ukraine Office, UNDP Moldova Office Requesting activity: Collaborative UNDP platform response to COVID-19 Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG2 [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | Sustainable Development | air quality, covid19, sustainable development, transport | EO Clinic support requested by: UNDP Ukraine Office, UNDP Moldova Office Requesting activity: Collaborative UNDP platform response to COVID-19 Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG2 (Climate Change), TG8 (Transport), TG9 (Urban), TG11 (Non-EO Information and Analytics) Work Order number: EOC0009 Work Order status: Completed Work Order start: 2020 Jul 21 Work Order end: 2020 Oct 05 Background The COVID-19 crisis is transforming the social and economic landscape of many countries, with measures adopted including physical distancing, travel restrictions, transition to teleworking, etc., depending on epidemic phase and local context. With the lockdowns many new business models are adopted, solid supply chains are affected and new approaches are appearing. COVID-19 in Ukraine: In Ukraine, the national authorities imposed comprehensive quarantine measures at an early stage of the COVID-19 surge. Mobility and transport within and between cities and regions (Oblasts) reduced drastically. Negative effects across the country’s growing economy quickly emerged, as enterprises in large numbers had to halt operations completely or were forced to adapt to a minimum of demand and market activity. The Ukrainian Chamber of Commerce and Industry estimates that about 700,000 small and medium enterprises in the service sector and educational institutions which employ 3.5 to 4 million people have closed. Whereas the full impact is yet to be established, diminishing of productive sectors and decline in income from both formal and informal economic activity will cause a significant backlash to progress that has been recorded on important social and economic development indicators, especially at local and regional level. COVID-19 in Moldova: The impact of the COVID-19 crisis on a small and open economy and a fragile local business community as the one in the Republic of Moldova is expected to be significant. The vulnerable groups in Moldova will disproportionately suffer from the crisis and the losses due to decreased mobility and economic activity. The rising income and non-income inequalities will affect the modest yet positive achievements of the country and its people when it comes to achieving the localised SDGs. With around 1 million of migrant Moldovans abroad, and given the deteriorating conditions in many destination countries, migration is an important crisis transmission channel and declining remittances will hit the local economy hardly. The Republic of Moldova responded to the COVID-19 outbreak by imposing a set of restrictive measures which covered travel bans in and outside of the country, implementing social distancing and sanitation protocols, as well as restricting on business activities. The policies aimed at reducing the spread of the virus and supporting the nation healthcare system have significantly disrupted public life and economic activity, with World Bank forecasting a 5.4 decrease in GDP due to the Coronavirus pandemic. In the long-term the impact of the pandemic is yet to be determined but the forecasts suggest a sharp deterioration in activity. A fall in remittances will further depress private consumption while the disruption of supply chains and recession in key economic partners will reduce exports. On the production side, the outbreak will reduce reducing domestic output, with HORECA, construction, transport and manufacturing being most affected. The optimistic forecasts suggest that the economy is expected to bounce back to around 4 percent in 2021 and to moderate at 3.6 percent in 2022, however the recovery is conditioned on the capacity of Governments to understand how the crisis continues to affect national business community and society. Crisis Response: In order to respond to the current crisis, raise awareness of the central and local administrations, support with evidence-based decision making, and assess the impact of the crisis induced by the COVID-19 pandemic, UNDP together with the Ukrainian and Moldovan governments are stepping up efforts to collect new evidence, including from satellite Earth Observation (EO), in a multi-layered and multi-granular information approach. Problems to be Addressed and Geospatial Information Gaps Geospatial EO data is missing to a large extent and not yet fully used in Ukraine and Moldova for development purposes. Moreover, given the current COVID-19 crisis, EO and other new types of data is urgently required to provide for: 1) Additional evidence around what is happening on the ground, especially in the absence or delayed collecting of statistical and other public data; 2) Improve situational awareness of the local and regional authorities around COVID-19 and its spread; 3) Support in assessing the immediate and long-term social and economic impact of COVID-19; 4) Support in building an Early Warning System (for the Government of the Republic of Moldova). In the current COVID-19 pandemic context, the governments of Ukraine and Moldova have expressed strong interest in having the capability to characterise the consequences of the pandemic on environmental conditions (i.e. environmental indictors). One of the information gaps concerns overview and detailed information on the status of air quality and emissions due to transport and industry. The present EO Clinic support will contribute to the work of UNDP and the governments to close this information gap and to better understand the complex “before and after” situation in both countries, created by the limitations in mobility, changes in economic activity, and the additional influx of previously expatriated citizens. Information Services to be Delivered Service 1: Regional and Local Air Quality Indicators Project Documents Work Order Report: EOC0009_WOR.pdf |
| EO Clinic: Drought Monitoring and Early Warning in Afghanistan | EO Clinic support requested by: World Bank Group (WBG) Urban, Resilience and Land Global Practice, Regional Team Africa Requesting activity: Afghanistan - Early Warning, Early Finance and Early Action Project (P173387) Requesting activity [...] | EO Clinic support requested by: World Bank Group (WBG) Urban, Resilience and Land Global Practice, Regional Team Africa Requesting activity: Afghanistan – Early Warning, Early Finance and Early Action Project (P173387) Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG4 (Disaster Risk Management), TG10 (Water Resources Management) Work Order number: EOC0022 Work Order status: On Hold Work Order start: Work Order end: Background Afghanistan is highly vulnerable to intense and recurring natural hazards that further threatens growth and stability and droughts have the most widespread impact. Weather, water and climate (hydromet) services, and early warning mechanisms in Afghanistan are incomplete and fragmented. Vulnerability to food insecurity is pervasive and rising, exacerbated by drought, displacement due to conflict and climate-drivers and now the economic disruption of COVID-19. In 2016–2017, an estimated 45% of the population of Afghanistan were considered food insecure. This succession of crises has highlighted the urgent need to establish a shock-responsive approach to managing food insecurity to strengthen the humanitarian-development nexus. The early warning component (Component 1) of the Bank project will support the Government of the Islamic Republic of Afghanistan (GoIRA) in 1) establishing and operationalising drought early warning decision support (Afghanistan Drought Early Warning Decision Support – AF-DEWS), 2) improving its capacity to develop and deliver critical weather, water, and climate information services, and 3) strengthening disaster preparedness for community resilience. In addition to building systems, these activities will support planning in Component 2 (for example, identification of risk-informed plans for community public works) and Component 3 (for example, information that can support leveraging of layered financing). The AF-DEWS is a cloud-based system which enables data sharing with all relevant hydromet agencies and relevant stakeholders. The Early Warning Component is implemented by the Ministry of Rural Development and Reconstruction (MRRD) with the support of key technical partners. There are six key Government agencies involved in the development of the tool: the hydromet agencies (Afghanistan Meteorological Department, AMD and the Water Resource Directorate, WRD), the Ministry of Agriculture (MAIL), the DRM Agency (State Ministry for Disaster Management, SMDM) and the National Statistics and Information Authority (NSIA). Problems to be Addressed and Geospatial Information Gaps In Afghanistan, the Bank project requires support with: 1) better monitoring, identifying and assessing meteorological, hydrological, and agricultural droughts; 2) the definition of drought thresholds and validation using on-ground datasets; and 3) inclusion of additional medium/long range and seasonal weather forecasts (in particular temperature and precipitation). The AF-DEWS currently relies on Numerical Weather Prediction (NWP) data from the Indian Meteorological Department (IMD), and agricultural drought indices mostly from MODIS, via Google Earth Engine. The project would like to enhance the essential meteorological and satellite data holdings in the system and leverage APIs to allow near-real-time processing and provision of additional products. Especially in relation to agricultural drought indices, the AF-DEWS is mostly relying on MODIS dataset (250 m spatial resolution). The Bank team would like to explore the potential to use higher resolution and more frequent datasets such as Sentinel-2 and/or Landsat 7/8 products to improve the overall spatial resolution (and accuracy) of the data. Information Services to be Delivered Service 1: Drought Monitoring and Early Warning | |||
| EO Clinic: Ecosystem-Based Management in River Basins in the Philippines | EO Clinic support requested by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Philippines Office Requesting activity: Ecosystem-based management and application of ecosystem values in two river basins in the Philippines [...] | E-GEOS (IT) | EO Clinic support requested by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Philippines Office Requesting activity: Ecosystem-based management and application of ecosystem values in two river basins in the Philippines (E2RB) Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG6 (Forestry) Work Order number: EOC0016 Work Order status: Completed Work Order start: 2021 May 26 Work Order end: 2021 Sep 23 Background River basins provide habitats and resources for threatened species and at the same time, livelihood for people within the basin and adjacent areas. However, they are subjected to degradation through uncontrolled and excessive exploitation caused by increasing population and unsustainable management of natural resources. This poses a threat to the country’s economy, social and human well-being, and environment. The use of biodiversity and ecosystem services as part of an overall adaptation strategy to help people to adapt to the adverse effects of climate change, or in short Ecosystem-based Adaptation (EbA), together with effective governance and integrated ecosystem-based management of watersheds and their resources are overarching solution to these problems. The GIZ project Ecosystem-based management and application of ecosystem values in two river basins in the Philippines (E2RB) therefore supports the Department of Environment and Natural Resources (DENR) and local communities in the Philippines to strengthen ecosystem services, protect biodiversity and reduce vulnerability to climate change and natural disasters in the Ilog-Hilabangan River Basin in the Visayas Region and the Tagum-Libuganon River Basin in Mindanao through integrated management and application of ecosystem services valuation and ecosystem-based adaptation measures. The project supports national policies and contributes to improved coordination and integration of sectors through an ecosystem-based approach. It will provide impetus for improving the fragmented water governance regime and aims at using the values of ecosystem services as a basis for the private sector buy-in, to contribute to the financing of conservation and protection measures that help to maintain ecosystem services. The GIZ support to the Philippine government foresees the development of a system that would alert DENR about the likelihood of evolution of landscapes from forest to agriculture, based on the model developed by Nowosad and Stepinski (2019) [1]. The system/tool would enable DENR to identify these hotspots and act timely – for example by implementing stricter monitoring and protection measures. Problems to be Addressed and Geospatial Information Gaps The land cover maps of the Philippines are updated every 5 years and are rarely assessed for accuracy at the local level (accuracy assessment is implemented at national level). Currently any recent satellite-based information are considered to be more reliable than the available 2015 national land cover maps. More frequent land cover maps (e.g. twice per year) with an estimated accuracy of at least 80% would be sufficient for local stakeholders such as DENR regional offices, to determine where to assign their limited human and other resources in terms of protecting specific forest areas that are likely to experience rapid forest loss. An additional requirement originates in the Philippine forest definition, where tree crops such as coconut palm, banana, etc. should not be considered as forest. The team is also seeking support for a clear approach for handling the dynamics of the losses, i.e. determining when the tree loss becomes more rapid, according to the aforementioned scientific paper. Information Services to be Delivered Service 1: Long-Term Forest Dynamics Service 2: Forest Loss Rate Methodology Project Documents Work Order Report: EOC0016_WOR_v01.pdf References [1] J. Nowosad, T. F. Stepinski (2019) “Stochastic, Empirically Informed Model of Landscape Dynamics and Its Application to Deforestation Scenarios”. Geophysical Research Letters 46 (23): 13845-13852. | ||
| EO Clinic: Estimating Irrigation Potential in Romania | EO Clinic support requested by: World Bank Group (WBG) Agriculture and Food Global Practice, Eastern Europe and Central Asia Department Requesting activity: Romania – Common Agriculture Policy Programming Support Requesting activity type: [...] | GeoVille (AT) | EO Clinic support requested by: World Bank Group (WBG) Agriculture and Food Global Practice, Eastern Europe and Central Asia Department Requesting activity: Romania – Common Agriculture Policy Programming Support Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG10 (Water Resources Management) Work Order number: EOC0018 Work Order status: Completed Work Order start: 2021 Apr 09 Work Order end: 2021 May 18 Background The Ministry of Agriculture and Rural Development (MARD) of Romania is collaborating with the World Bank in preparing Romania’s CAP (Common Agricultural Policy) Strategic Plan for 2021–2027. Under this collaboration project, the Bank provides support through a number of conceptual and technical studies that are expected to inform the formulation of the Strategic Plan, including an irrigation sector study (Study 1). The study will support the identification, spatial analysis, and mapping of current irrigation areas in Romania and, in addition, an assessment of Romania’s principal irrigation potential based on available water resources. In addition, the World Bank team will also provide support to strengthen MARD’s administrative and technical capacity to prepare the CAP Strategic Plan. This type of support is demand-driven and will be specified as the implementation of the assistance proceeds. The expected results of the World Bank’s technical assistance support include the timely preparation and delivery of these analytical studies that provide (a) a sound quantitative and/ or qualitative analysis of the status and constraints in selected sub-sectors and/or rural areas; (b) menus of interventions to ensure expected CAP impacts and outcomes; and (c) the principles and delivery modalities of future CAP measures to beneficiaries in Romania. The expected outcome of the project is to allow MARD to prepare a forward-looking comprehensive CAP Strategic Plan that meets EU requirements and expectations, based on relevant analytical input and through strengthened administrative capacity in sector strategy formulation. The current EO Clinic support would be input into the first study mentioned above, to develop a pilot and demonstration approach to mapping and assessing irrigation areas and areas with irrigation potential in Romania. Problems to be Addressed and Geospatial Information Gaps A good overview of the complex irrigation situation in Romania and its associated issues are given in the 2018 publication by the World Bank Group’s Water Global Practice: Romania Water Diagnostic Report – Moving toward EU Compliance, Inclusion, and Water Security [1], in particular in Section 5 of its Executive Summary and chapters 5 and 6. Information Services to be Delivered Service 1: Irrigated Crops and Irrigation Potential Mapping Project Documents Work Order Report: EOC0018_WOR_final.pdf Final Presentation: EOC0018_FPR.pdf References [1] http://documents1.worldbank.org/curated/en/114311530025860150/pdf/127630-REVISED-W18010.pdf. | ||
| EO Clinic: Estimating the Magnitude and Spatial Distribution of Informal Trade in Central Asia | EO Clinic support requested by: World Bank Group (WBG) Global Trade and Regional Integration Unit Requesting activity: Central Asia: Regional Trade Connectivity Linkages Requesting activity type: Other: ASA (Advisory Services and [...] | E-GEOS (IT) | Sustainable Development | infrastructure, sustainable development, transport, urban | EO Clinic support requested by: World Bank Group (WBG) Global Trade and Regional Integration Unit Requesting activity: Central Asia: Regional Trade Connectivity Linkages Requesting activity type: Other: ASA (Advisory Services and Analytics) EO Clinic relevant Thematic Groups: TG8 (Transport), TG9 (Urban), TG11 (Non-EO Information and Analytics) Work Order number: EOC0014 Work Order status: Completed Work Order start: 2021 Apr 09 Work Order end: 2021 Jun 29 Background The World Bank Group is supporting client countries in Central Asia with the objective of enhancing regional trade, investment and connectivity. Regional trade, in these geographies, is characterized by a large presence of informal trade (informal activity, which involves undeclared cross-border trade) mostly along borders and in markets and so-called bazaars. This form of trade is known to provide a large amount of employment in these countries. But this economic activity involving cross-border trade, taking place in these markets, is generally not recorded in official statistics. This “shadow” economy, often representing a large proportion of economic transactions is difficult to measure and its omission can lead to wrongful policy design and recommendations, the undermining of tax collection and the hurting of law-abiding local firms that compete with undeclared goods. Sometimes, ad hoc surveys are conducted, but they generally aren’t done on a regular basis and are prone to different methodological shortcomings, such as underreporting. The current EO Clinic support would be incorporated to an ongoing 2-year analytical project implemented by the World Bank (Central Asia: Regional Trade Connectivity Linkages – project number P171131) aimed at improving regional trade integration in Central Asia, that will have as main deliverable a publication but also policy dialogue with all governments in the region. Problems to be Addressed and Geospatial Information Gaps Capturing the size of the informal trading sector in certain Central Asian regions, even roughly, could represent a big leap forward in terms policy design in border compliance, and fiscal management for resource-starved countries. Sustained growth in informal cross-border trade typically leads to densification of man-made structures in the local hinterland, usually in the form of commercial real estate, small shops and warehousing structures. Increased trade is also most noticeable in terms of vehicle presence (e.g. trucks, cars, motorbikes, bicycles) and pedestrians shopping in these markets. Usually these markets are contained within a very small geographical area, of a few square kilometres at most, which makes them easier to observe in time with satellite Earth Observation methods. The objective of the present work is to use remote sensing methods to observe the peri-urban landscape of inland bazaars as a conduit to estimate current and past informal trade (directly or indirectly). Conceptually speaking, EO methods to fill in these gaps are not very different from those currently used in predictive analytics (e.g. estimation of retailer chains’ revenues by means of vehicle count in parking lots). Information Services to be Delivered Service 1: Past and Present Analysis of Markets and Bazaars Service 2: Predictive Analysis Project Documents Work Order Report: EOC0014_WOR_v01.pdf Final Presentation: EOC0014_EXS.pdf |
| EO Clinic: Increasing Agro-Climatic Resilience in Nigeria | EO Clinic support requested by: World Bank Group (WBG) Agriculture and Food Global Practice, West Africa Sustainable Development Department (SAWA4) Requesting activity: Nigeria – Agro-Climatic Resilience in Semi-Arid Landscapes [...] | GeoVille (AT) | EO Clinic support requested by: World Bank Group (WBG) Agriculture and Food Global Practice, West Africa Sustainable Development Department (SAWA4) Requesting activity: Nigeria – Agro-Climatic Resilience in Semi-Arid Landscapes (ACRESAL) Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG10 (Water Resources Management) Work Order number: EOC0019 Work Order status: Completed Work Order start: 2021 Jun 17 Work Order end: 2021 Nov 12 Background “The World Bank is currently preparing an investment project together with the Government of Nigeria, with the objective to increase the adoption of climate resilient landscape management practices in target-ed arid/semi-arid watersheds in central-north Nigeria. The multi-sector operation covering environment, agriculture and water will have three key components: 1. Desertification Control and Landscape Management; 2. Community Resilience and 3. Institutional Strengthening. For the preparation of the project and prioritisation of interventions, the Bank team are seeking satellite EO support to assess the current level of land degradation and water scarcity in the project area. This current situation, to be used as a baseline, will be used to select the states where the project will be implemented. During the implementation phase, the team is equally interested in using EO to monitor project achievements, as well as in capacity building with key stakeholders in Nigeria (Ministries of Environment, Agriculture, and Water, and the Nigerian Space Agency). Problems to be Addressed and Geospatial Information Gaps The project would benefit from a variety of geoinformation datasets related to land use, land cover, land degradation, water scarcity or drought, biophysical (related to suitability for water retention and solar irrigation) and agriculture performance. Overall, however, the primary aim of the present EO Clinic support is to better understand the extent and severity of land degradation and desertification in central-north Nigeria. The existing literature on the subject is usually equivocal. For example, in a 1999 national report on the implementation of the United Nations Convention to Combat Desertification (CCD)[1], it is stated: “The extent and severity of desertification in Nigeria has not been fully established neither the rate of its progression properly documented. Nevertheless, it is estimated that the country is currently losing about 351,000 hectares of its landmass to desert conditions annually, and such conditions are estimated to be advancing southwards at the rate of about 0.6 km per year.” Another uncertainty is related to the definition of deserts, which appears challenging, not less because often it is considered an irreversible process. Yet few processes are really irreversible [2]. For instance, in a recent Nature article [3] it was estimated that part of the Sahara desert in Mauritania has around 1.8 billion trees, or 13.4 trees per hectare. This is quite different from what one imagines as a “desert”. Despite these challenges of defining desert and degraded land, the Bank team would like to have a better estimate for the historical trends of land degradation and/or desertification, for the main purpose of ranking states according to their needs and land degradation risks. Information Services to be Delivered Service 1: Land Degradation and Desertification Assessment Project Documents Work Order Report: EOC0019_WOR_v01.pdf References [1] “Combating Desertification and Mitigating the Effects of Drought in Nigeria”, National Report on the Implementation of the United Nations Convention to Combat Desertification in those Countries Experiencing Serious Drought and/or Desertification, Particularly in Africa (CCD). For Submission at the Third Session of the Conference of the Parties, Recife, Brazil, November 1999. [2] See for example https://earthobservatory.nasa.gov/features/Desertification/desertification2.php. [3] M. Brandt et al (2020): An unexpectedly large count of trees in the West African Sahara and Sahel, Nature 587, pages 78–82(2020). | ||
| EO Clinic: Infrastructure Projects Implementation and Economic Outcomes in Armenia | EO Clinic support requested by: Asian Development Bank (ADB), Central West Regional Department (CWRD), Urban Development and Water Division (CWUW) Requesting activity: Infrastructure Projects: Implementation and Economic Outcomes in [...] | GeoVille (AT) | Sustainable Development | infrastructure, sustainable development, urban | EO Clinic support requested by: Asian Development Bank (ADB), Central West Regional Department (CWRD), Urban Development and Water Division (CWUW) Requesting activity: Infrastructure Projects: Implementation and Economic Outcomes in Armenia Requesting activity type: Loan EO Clinic relevant Thematic Groups: TG9 (Urban), TG11 (Non-EO Information and Analytics) Work Order number: EOC0013 Work Order status: Completed Work Order start: 2021 Jan 27 Work Order end: 2021 Dec 17 Background Regions of Armenia are characterized by deep and persistent disparities in terms of levels of their economic development. The regional disparities in Armenia worsened as the country moved from a centrally-planned economy to a market economy after independence from the Soviet Union in 1991. Armenia’s urban sector is characterized by the dominance of Yerevan, which hosts over a third of the national population and accounted for 57.7% of Armenia’s GDP (2016). With an urbanization structure which is con-sistent with comparator countries (Balkans, former Soviet Union and allied countries with a population be-tween 1 and 5 million inhabitants), urban sector investments are consistently dominating in the primate cap-ital city. Armenia has only one secondary city with more than 100,000 inhabitants, Gyumri. While Armenia’s single-centre national economic model allows for agglomeration effects, it also raises ques-tion about the development possibilities of other regions, especially of secondary cities at considerable dis-tance from the capital. Therefore, the main question is how to achieve more balanced economic growth, while harvesting productivity gains from agglomeration in Yerevan. Infrastructure investment is increasingly recognized as one of the key factors behind long-run economic growth, as well as enabler of more equal regional growth—higher mobility of resources between and within regions can build equitable growth and spread economic gains more widely across growth centres and regions. During the last decades Armenia has made a sizeable improvement in hard infrastructure renovation and building; thousands got access to better education, healthcare and more. Nevertheless, significant gaps in the implementation of large-scale infrastructure projects remain. Certainly, this is not a purely Armenian phe-nomenon—advanced economies face similar challenges. As a result, many developed countries have gradually moved towards more robust institutional setups. For example, Governments of UK, Ireland and Australia have established corresponding institutions, which are equipped with the necessary level of independence and ex-pertise to bring the uncertainty related to infrastructure project delivery down. The institutional setup and the capacity building for sophisticated infrastructure projects are likely to be at the front and centre of the discus-sion about public capital spending in a foreseeable future. Problems to be Addressed and Geospatial Information Gaps The EO Clinic activation shall help identifying areas of permanent change in the physical urban- and periurban landscape in Armenia, reflecting changes in the economic activity, as observed via EO. The analysis will exploit optical and/or radar datasets to generate indicators spanning from the 90s (e.g. archived Landsat-6 and ERS data) until present (latest Sentinel-1 and Sentinel-2 data). A set of indicators will be derived that best fit the purpose of detecting and characterising some of the major changes over time. This activity is exploratory in nature and provides mapping products and, most importantly, a synthesis of changes over the years. The proposed solution includes indicators on urban and peri-urban expansion, fragmentation and compactness. Land accounting for physical assets including transformation to and from urban on one side, and agriculture, forest and semi-natural/natural land, wetlands or water on the other, are calculated and presented as analytics. Information Services to be Delivered Service 1: Indicators of Permanent Change in the Economy Service 2: Full-Scale Generation of Indicators Service 3: Concept Note on a Possible Platform to Support Investment Prioritisation Project Documents Work Order Report: EOC0013_WOR_v01_1.pdf |
| EO Clinic: Mapping Pollution Hotspots in Iraq | EO Clinic support requested by: World Bank Group (WBG) Environment, Natural Resources and Blue Economy Global Practice Requesting activity: Support to Manage Environmental Hotspots in Iraq (P173049) Requesting activity type: Technical [...] | GeoVille (AT) | EO Clinic support requested by: World Bank Group (WBG) Environment, Natural Resources and Blue Economy Global Practice Requesting activity: Support to Manage Environmental Hotspots in Iraq (P173049) Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG4 (Disaster Risk Management), TG5 (Energy and Natural Resources), TG9 (Urban), TG11 (Non-EO Information and Analytics) Work Order number: EOC0017 Work Order status: Completed Work Order start: 2021 Jun 15 Work Order end: 2022 Jan 26 Background Iraq is struggling with chronic environmental problems and environmental impact of conflict. The World Bank Group activity requesting the current EO Clinic support is primarily informed by the Damage and Needs Assessment (DNA) carried out by The World Bank in 2018[1], that estimated chemical and hydrocarbon contamination of over 10,569 hectares and unusable nature of over 2.3 million hectares of land due to series of conflicts in Iraq. Building on the ongoing efforts of the Chemical Management and Contaminated Sites Assessment Department of the Ministry of Health and Environment (MoHE) and other development partners such as UNEP Crisis Management Unit[2], the activity proposes to carry out the following tasks: 1) Prepare a detailed inventory of critical pollution hotspots in Iraq; 2) Identify priority sites for remediation with emphasis on community health and safety and local economic development; 3) Support preparation of technical studies (including engineering, costing, etc.) for remediation of priority hotspots; 4) Support preparation of a national register of contaminated hotspots, and 5) Develop a road map/ action plan for the program on remediation of hotspot sites in Iraq. These activities will contribute to the establishment of a framework for sound management of environmental and conflict pollution hotspots in Iraq with twin objectives of mitigating health and safety risks and contributing to the local economic development through remediation. Based on the progress of these activities, a recipient-executed activity will also be designed that can implement remediation of priority hotspots, augment the laboratory and detailed assessment infrastructure of MoHE, and design a national program for the remediation of polluted sites in Iraq. Based on the detailed information on critical pollution hotspots, the activity will identify remediation measures through technical studies for priority hotspots where pollution poses a high and immediate risk to communities and opportunities for beneficial use of the land. The current EO Clinic support would feed into the inventory of critical pollution hotspots performed in the Advisory Services and Analytics (ASA) activity mentioned above. Problems to be Addressed and Geospatial Information Gaps Some of the information gaps the World Bank Group together with the Iraqi government are trying to bridge regard a better understanding of the situation on the ground concerning the location and characterisation of contaminated and polluted sites at a national scale, as well as the type of contamination (oil, chemical, waste and demolition waste or others). An inventory in several provinces of Iraq is currently available, from the Ministry of Health and Environment . This however covers only oil polluted sites and doesn’t provide information such extent or land use in the vicinity of the site, etc. This data needs to be updated and information on sites across seven conflict-affected governorates needs to be generated. These governorates are: Ninewa (Nineveh), Al Anbar, Salah Ad-Din (Saladin), Diyala, Kirkuk, Baghdad, and Babel (Babil). Information Services to be Delivered Service 1: Identification of Environmental Pollution Sites Service 2: Characterisation of Environmental Pollution Sites References [1] World Bank Group (2018): Iraq Reconstruction and Investment: Part 2: Damage and Needs Assessment of Affected Governorates. [2] United Nations Environment Programme (2005): Assessment of Environmental ‘Hot Spots’ in Iraq. | ||
| EO Clinic: Mitigation of Climate Change Risks in the Agricultural Sector of Cambodia | EO Clinic support requested by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Regional Economic Development Program IV (RED IV), Cambodia Requesting activity: Identification of surface water resources for the mitigation of [...] | GeoVille (AT) | Sustainable Development | agriculture, climate, disaster risk, sustainable development, water resources | EO Clinic support requested by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Regional Economic Development Program IV (RED IV), Cambodia Requesting activity: Identification of surface water resources for the mitigation of climate change risks in the agricultural sector of north-western Cambodia Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG2 (Climate Change), TG4 (Disaster Risk Management), TG10 (Water Resources Management) Work Order number: EOC0010 Work Order status: Completed Work Order start: 2020 Jul 28 Work Order end: 2020 Sep 21 Background Cambodia is heavily affected by climate change. The rainy season is becoming more irregular and rainfall is often delayed but more frequent. In the Tonle Sap catchment area there have been repeated severe floods in recent years, but at the same time a growing number of droughts (see also the GIZ study Transboundary Water Resource Management in the Lower Mekong Basin – Joint Project Flood and Drought Thailand and Cambodia Sub Basins 9T/9C, August 2018). The droughts, which have now become very severe, directly threaten the existence of thousands of small farmers in the western and northern provinces of Cambodia. The availability of water is of decisive importance for further economic development of north-western Cambodia. It is essential for the fight against rural poverty and malnutrition, since most of the rural population lives from agriculture and the poverty rate in this region is above country average. Every year, marginalised groups of the population which are supported by the GIZ program Regional Economic Development IV (RED IV), are acutely threatened by crop failures to fall (back) below the poverty line. Many households in northwest Cambodia earn their living by growing rice, cassava or vegetables, all agricultural products that depend on sufficient and regular rainfall. The above-mentioned study comes to the conclusion that in the coming years, both floods and droughts can be expected to increase, while at the same time the pressure on water resources increases. RED IV is an extensive program with SDC (Swiss Agency for Development and Cooperation) co-financing working on the promotion of agricultural value chains in the north-western part of Cambodia. Water management is an important issue for the program, which has been working since October 2019 on an analysis of the local availability of surface water in the north-western provinces of Cambodia. The present EO Clinic support will help define options for the construction of water infrastructure and recommendations for the improvement of water management, in order to maintain and secure the water resources of the rural population. Problems to be Addressed and Geospatial Information Gaps There is currently no systematic water management in Cambodia. Some of the reservoirs date back to the 1970s, but they are often in poor condition and completely inadequate in terms of volume and integration into local infrastructures. Local authorities on district and communal level have no comprehensive overview of the existing water infrastructure and the availability of surface water resources (natural or man-made). There is no connection between the development of agricultural clusters and a systematic development of water infrastructure. Local authorities have insufficient capacities and knowledge to develop a water management strategy. Data availability in Cambodia is a challenge, especially when it comes to fine scale. Cambodia has at this point no official data of the nature required by RED IV. Mapping the extent of surface freshwater (streams, rivers, lakes, wetlands, reservoirs, irrigation canals, creeks) at regional scale and monitoring its dynamics at regular and frequent time intervals is sought after. However, currently available data from Cambodian authorities are either out of date or not accurate enough. Presently, GIZ and its partners have some familiarity with products such as the USGS Landsat Dynamic Surface Water Extent. The level of detail of these products is however often considered insufficient. Information Services to be Delivered Service 1: Waterbody Inventory and Dynamics Service 2: Detailed Waterbody Inventory Project Documents Work Order Report: EOC0010_WOR_V1.0.pdf |
| EO Clinic: Natural Wealth and Sovereign Risk | EO Clinic support requested by: World Bank Group (WBG) Finance, Competitiveness & Innovation Global Practice (FCI GP), Long Term Finance Unit (EFNLT) Requesting activity: Natural Wealth and Sovereign Risk Requesting activity type: Other: [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | Sustainable Development | agriculture, sustainable development | EO Clinic support requested by: World Bank Group (WBG) Finance, Competitiveness & Innovation Global Practice (FCI GP), Long Term Finance Unit (EFNLT) Requesting activity: Natural Wealth and Sovereign Risk Requesting activity type: Other: Global Program on Sustainability (GPS) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG11 (Non-EO Information and Analytics) Work Order number: EOC0008 Work Order status: Completed Work Order start: 2020 Jul 15 Work Order end: 2020 Oct 05 Background A well-developed financial sector that enables long-term financing for countries’ strategic sectors– government, SMEs and corporates, physical infrastructure & housing, and agriculture – is crucial for inclusive economic growth and for achieving the World Bank Group’s twin goals of ending extreme poverty and boosting shared prosperity. The activities of the Term Finance Unit (EFNLT) within the World Bank’s Finance, Competitiveness & Innovation Global Practice (FCI GP) assist in bridging funding gaps for these key strategic sectors by developing capital markets and increasing the supply of institutional investors’ assets (primarily pensions and insurance) to fund long-term investments in strategic sectors such as infrastructure, housing and agriculture. The World Bank’s Global Program on Sustainability (GPS) aims to integrate environmental and other sustainability considerations into public and private decisions, by providing policy makers and the financial sector with the necessary metrics and tools. This approach involves looking beyond GDP and traditional financial metrics to include accounting for environmental risks and opportunities and valuing natural capital and ecosystem services. Within the proposed activity “Natural Wealth and Sovereign Risk”, EFNLT aims to conduct assessments on how environmental risks impact the financial sectors of different countries. The project plans to use data from various sources, including on agricultural crop types and crop health, to bring more detail into existing sovereign Environmental, Social and Governance (ESG) data. This aims to build on WAVES, a GPS precursor activity, as part of an ongoing donor-funded program that has been renewed for the next 3 years. Problems to be Addressed and Geospatial Information Gaps The information gaps in the scope of the present World Bank support request are related to agricultural crop status and crop health, compared across countries. At the moment the related data available to the bank team is often inconsistent, not sufficiently granular and not made available with a sufficient frequency. The bank team currently only has country-level wealth data on an annual frequency to compare crop data to. These are highly aggregated and modelled such that direct comparisons are difficult. Information Services to be Delivered Service 1: Crop Types and Crop Health Project Documents Work Order Report: EOC0008_WOR.pdf |
| EO Clinic: Nature-Based Solutions in Cities | EO Clinic support requested by: World Bank Group (WBG) Urban, Resilience and Land Global Practice, Regional Team Africa Requesting activity: Support to the development of a high-resolution suitability mapping methodology for identifying [...] | E-GEOS (IT) | EO Clinic support requested by: World Bank Group (WBG) Urban, Resilience and Land Global Practice, Regional Team Africa Requesting activity: Support to the development of a high-resolution suitability mapping methodology for identifying location of nature-based solutions in cities (NBS) Requesting activity type: Knowledge Product EO Clinic relevant Thematic Groups: TG4 (Disaster Risk Management), TG9 (Urban), TG10 (Water Resources Management), TG11 (Non-EO Information and Analytics) Work Order number: EOC0020 Work Order status: Completed Work Order start: 2021 Jun 08 Work Order end: 2021 Aug 18 Background Nature-Based Solutions (NBS), also referred to as green infrastructure, provide cost-effective solutions to climate, disaster and water problems while bringing multiple benefits for the environment and communities. NBS are applied in a variety of contexts, ranging from urban parks to address localized flooding and heat waves in cities, to the large-scale restoration of inland forests, wetlands, mangroves and coral reefs to protect vulnerable communities from flooding and climate change and provide multiple benefits. The World Bank is requesting support via the EO Clinic to develop a set of EO-derived datasets for at least two pilot cities. In these cities, the World Bank NBS team will develop and pilot a geospatial suitability mapping methodology that enables World Bank Task Teams to better understand the potential of NBS in urban or urbanising regions, and to identify locations for NBS in cities considering their spatial suitability and effectiveness for urban resilience, including flood risk management and urban heat island reduction and co-benefits. The methodology will consider different types of NBS and applications at different scales, from coastal landscape, to basin and to city level. Eventually, after pilot testing and validation, the methodology will be used to develop a geospatial scanning tool for Urban NBS that can identify suitable and effective NBS in any city in the world. This activity is led by the World Bank’s NBS team – a cross-sectoral knowledge program and community of practice with participation from World Bank Global Practices: Urban, Resilience and Land; Environment, Natural Resources and the Blue Economy; and Water Resources Management. The World Bank has invested an estimated 3 billion USD in NBS interventions between 2012 and 2018 with a further steep increase in its application in the last two years. The activity will support this growing portfolio of solutions globally. Problems to be Addressed and Geospatial Information Gaps Cities worldwide are experiencing the impacts from climate change. Extreme precipitation events, flooding, rising temperatures, and droughts are causing economic losses, social insecurity, and affecting human well-being. Flooding, in particular, represents one of the most pervasive and costliest natural disasters. This is even more evident in the urban regions of developing countries, which are rapidly expanding and often deal with unplanned settlements in high-risk areas, such as in floodplains and on steep slopes. The World Bank has a large portfolio of investments and analytical engagements to enhance urban resilience which could benefit from the current project by identifying potential investments in NBS, ranging from investments in improved drainage systems including NBS for flood protection to urban upgrading and creation of new green spaces. In order to perform NBS suitability mapping in any urban area, the Bank requires a variety geospatial data layers from EO and non-EO sources, of sufficient detail and with global availability. For datasets such as high-resolution urban green spaces, the Bank task teams often rely on local land cover data or in some cases commercial very high-resolution datasets. The requesting Bank team is interested in testing the feasibility of replacing some of these datasets by lower-resolution and lower-cost, globally and readily-available or easily-obtainable satellite EO datasets. Information Services to be Delivered Service 1: Consolidated NBS-Relevant EO Mapping Products Project Documents Work Order Report: EOC0020_WOR_v1.pdf | ||
| EO Clinic: Post-Disaster Population and Land Use Planning in St. Vincent and the Grenadines | EO Clinic support requested by: Caribbean Development Bank Requesting activity: Post-disaster Population and Land Use Planning Requesting activity type: Technical Assistance (TA), Loan, Grant EO Clinic relevant Thematic Groups: TG1 [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | EO Clinic support requested by: Caribbean Development Bank Requesting activity: Post-disaster Population and Land Use Planning Requesting activity type: Technical Assistance (TA), Loan, Grant EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG4 (Disaster Risk Management), TG6 (Forestry) Work Order number: EOC0021 Work Order status: Under Execution Work Order start: 2022 Jan 10 Work Order end: Background On 29 December 2020, the La Soufrière volcano alert level in St. Vincent and the Grenadines was elevated due to increased volcanic activity. On 9 April 2021, La Soufrière erupted for the first time after 40 years, sending an ash plume of 10 km into the sky. The resulting ashfall was very heavy in the surrounding areas, reaching nearby islands and halting air traffic in the area. Subsequent eruptions, lava flows, ash plumes and seismic activity continued throughout April. In early May, explosions subsided, but seismic activity and the risk of lahars remain. On 6 May 2021, the Government of St. Vincent and the Grenadines with the National Emergency Management Organization (NEMO) lowered the Volcanic Alert Level from Red to Orange. Persons in the Yellow and Orange zones returned to their homes, being reminded that escalation in activity can still occur with little or no warning, and caution should be taken in crossing river valleys on the volcano due to the increased risk of lahars during periods of rainfall. As of 13 May, approximately 30 evacuees have returned to their homes. Many made their way back to collective centres, finding their homes uninhabitable. Problems to be Addressed and Geospatial Information Gaps CDB would like to use spatial data to ascertain the impact of the volcanic ash clouds and pyroclastic flows from the recent eruption of a the La Soufriere Volcano in St. Vincent and the Grenadines. The present request from the CDB aims support the Bank’s efforts to capture and present geospatial data on population demographics, infrastructure and policy interventions in the CDB’s member countries. Information is sought to enable greater knowledge of key economic, social, and environmental variables and allow better forecasting of some of the main vulnerabilities facing the Caribbean. Empirical data and models of impact are planned to be used to project shock scenarios to inform disaster-risk management strategies and planning for response, recovery, and rehabilitation efforts. The Bank aims to superimpose the satellite-based datasets on nationally-collected data including the population composition by area (age group, gender, presence of disabilities), major public infrastructure including roadways, waterways, electricity grids, agricultural area (preferably by type of crop) and both sea and airports. This analysis will be critical to informing efforts in the country as it presents a better understanding of what happened, who was affected and where efforts should be concentrated. Information Services to be Delivered Service 1: Reference Mapping Service 2: Auxiliary Mapping Products and Visualisation | ||
| EO Clinic: Preparation of a National Coffee Sector Development Plan for Timor-Leste | EO Clinic support requested by: Asian Development Bank (ADB), Timor-Leste Resident Mission (TLRM) Requesting activity: Coffee and Agroforestry Livelihood Improvement Project Requesting activity type: Technical Assistance (TA) EO Clinic [...] | E-GEOS (IT) | Sustainable Development | agriculture, forestry, sustainable development | EO Clinic support requested by: Asian Development Bank (ADB), Timor-Leste Resident Mission (TLRM) Requesting activity: Coffee and Agroforestry Livelihood Improvement Project Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture) Work Order number: EOC0002 Work Order status: Completed Work Order start: 2019 Jul 01 Work Order end: 2019 Sep 12 Background Improvements in coffee production and processing offer one of the clearest pathways for poverty reduction and growth of the non-oil economy in Timor-Leste. Coffee is Timor-Leste’s largest non-oil export and is grown by an estimated 37.6% of all Timorese households. Approximately 52,000 hectares are planted with coffee but it is reported that more than half of the planted area consists of unproductive old trees. As a result, yields are low, with an average yield of 150–200 kg of green beans per ha. This is only 21% of the average yield in Southeast Asia and 10% of the yield achieved by productive plantations. Relatively simple practices including replanting, pruning and improved farm management have been shown to triple the yield per unit area for a typical household and raise households’ net income from coffee production by a factor of 2.7. It is also widely recognized that Timor-Leste has the potential to sell an increasing share of its coffee production to differentiated specialty markets that pay price premiums relating to quality, origin, production processes and environmental sustainability. Achieving this potential re-quires careful processing and handling of coffee as it moves through the value chain from coffee farms to final consumers in the domestic or international market. Several development partners have been supporting farm rehabilitation and quality improvements by providing grant funds to individual cooperatives and NGOs or by providing assistance to the government. There has been good progress in farm some areas but serious challenges remain. This request for support is meant to provide better geospatial data to design the development coffee industry. Problems to be Addressed and Geospatial Information Gaps Information is needed on the location, extent and state of the coffee plantations, as well as patterns in land use change related to (and affecting) coffee plantations. Information Services to be Delivered Service 1: Past and Current Coffee-Growing Areas and Farming Conditions Project Documents Work Order Report: EOC0002_WOR_v03.pdf Additional Resources This EO Clinic activation was followed by a more in-depth study: CRITE: Coffee Rehabilitation in Timor-Leste. |
| EO Clinic: Responsible Banana Supply Chains in the Philippines | EO Clinic support requested by: World Bank Urban, Disaster Risk Management, Resilience, and Land Global Practice Requesting activity: Brought to you by Geodata: Responsible Banana Supply Chain Requesting activity type: Technical Assistance [...] | EO Clinic support requested by: World Bank Urban, Disaster Risk Management, Resilience, and Land Global Practice Requesting activity: Brought to you by Geodata: Responsible Banana Supply Chain Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG2 (Climate Change), TG6 (Forestry), TG11 (Non-EO Information and Analytics) Work Order number: EOC0027 Work Order status: Evaluating Proposals Work Order start: Work Order end: Background The Philippines is the second largest exporter of bananas in the World with exportations reaching 4.40 millions of tons in 2019. According to the Philippine Statistics Authority, banana plantations covered about 454,000 hectares of land in 2012 and 443,000 hectares in 2014/2015. The Cavendish banana is the exported variety of bananas produced in the Philippines, while other bananas and plantains such as the Lakatan and the Sava/Cardaba can be found on the domestic market as a fresh fruit or as processed food. At the national level, bananas are distributed by two types of businesses: large corporations and small and medium enterprises. Businesses that operate globally have to comply with Environment and Social (E&S) Standards, which are a common requirement in agriculture in order to have access to markets, to obtain financing from investors and to maintain a strong brand and reputation. In particular, countries around the world and especially EU member states are increasingly introducing new E&S legal requirements, in parallel to a rise of consumer demands for responsibly-sourced products. In the Philippines, there are prevalent environmental and social risks in the banana supply chain, which include deforestation, soil degradation, biodiversity loss, climate change issues, illegitimate land acquisitions and forced labour. To date, only few Filipino banana producers have embarked on sustainability certification schemes. While large corporations in the Philippines possess their own guidance for producing and distributing agricultural commodities and for complying with national and/or international E&S regulations, small corporations lack experience in strategically engaging into the international markets. Their lack of knowledge to comply with the E&S regulations expose them to less opportunities to the international markets. Problems to be Addressed and Geospatial Information Gaps The Department of Agriculture of the Philippines is trying to bridge the existing gap between large and small groups of corporations, notably through the “Banana Roadmap” strategy plan at the national level. The Department of Agriculture is still working on a paper-based basis, including for the monitoring of various E&S risk indicators identified in the Banana Roadmap strategy report. In support to this initiative, the objective of the World Bank is to provide government, private sector, farmers and other stakeholders with improved information on actual and potential social and environmental adverse impacts for banana production on Mindanao island. In particular, the present pilot project by the World Bank aims to develop a visualising platform of E&S risk indicators along the banana supply chain, including for small-holder farmers, in the region of Mindanao. Earth observation can help monitoring these risks, by providing information on the extent and intensity of banana cultivation, forest cover change, or vegetation health. This project is part of the DT4D Challenge 2.0, and is linked to the Philippines Rural Development Project (PRDP) led by the World Bank. Information Services to be Delivered Service 1: Land Use Analysis Service 2: Production Intensity Service 3: Vegetation Health Monitoring | |||
| EO Clinic: Shoreline Mapping in the Gaza Strip | EO Clinic support requested by: UNDP Gaza Office / Programme of Assistance to the Palestinian People (PAPP) Requesting activity: Building Capacities in Remote Sensing Technologies in the Gaza Strip Requesting activity type: Technical [...] | GeoVille (AT) | Sustainable Development | climate, coastal zone, disaster risk, marine environment, sustainable development, urban | EO Clinic support requested by: UNDP Gaza Office / Programme of Assistance to the Palestinian People (PAPP) Requesting activity: Building Capacities in Remote Sensing Technologies in the Gaza Strip Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG2 (Climate Change), TG3 (Coastal Zone Management), TG4 (Disaster Risk Management), TG9 (Urban) Work Order number: EOC0011 Work Order status: Completed Work Order start: 2020 Aug 18 Work Order end: 2020 Sep 29 Background In the recent years, the Gaza Strip has been experiencing rapidly-evolving environmental changes, related especially to land use, coastal erosion and agricultural production, in conjunction with flooding and drought problems. Due to the lack of planning and monitoring by different stakeholders, this has led to serious and complex problems, including risk to residents in coastal areas and food insecurity. Monitoring and detection of such environmental changes and assessment of their trends as well as their consequences are necessary for future development. UNDP is working to launch projects on the protection of the Gaza shoreline, where detailed information is needed on the forces driving the coastal erosion, which was observed historically and is expected to continue in the coming years. Without adequate measures, this is considered as a real risk for the coastal environments and the residents living near the shoreline, especially in the western side of the Gaza Strip. This also causes considerable economic loss for the people of Gaza. In general, in Palestine and the Gaza Strip the approach of inclusion of remote sensing and satellite Earth Observation (EO) in planning and monitoring activities is still in its early stages, due mainly to the limited number of remote sensing specialists. There is a pressing need to mainstream the culture of remote sensing in the context of Palestine and specifically in the Gaza Strip, where changes are sometimes manmade and can be massive. UNDP is planning an intervention aiming to increase the local capacities in utilising remote sensing in planning and monitoring the different rehabilitation and development activities aiming to overcome relevant knowledge gaps. The supported UNDP project aims to build capacities in remote sensing applications for sustainable development in the Gaza Strip. The present EO Clinic support will contribute to creating a complete and up-to-date analysis of the Gaza shoreline, providing insights in coastal erosion and accretion processes and associated risks. Additionally, it will contribute to the UNDP-supported training programme by providing high-quality EO training materials and support in delivering those trainings. Information Services to be Delivered Service 1: Coastal Change Mapping Service 2: Capacity Building Support Project Documents Work Order Report: EOC0011_WOR_v01.pdf |
| EO Clinic: Snow and Ice Mapping in Kazakhstan | EO Clinic support requested by: Asian Development Bank (ADB), Kazakhstan Resident Mission (KARM) Requesting activity: Republic of Kazakhstan: Mobilizing finance to help achieving Sustainable Development Goals Requesting activity type: [...] | E-GEOS (IT) | Sustainable Development | disaster risk, snow and ice, sustainable development, water resources | EO Clinic support requested by: Asian Development Bank (ADB), Kazakhstan Resident Mission (KARM) Requesting activity: Republic of Kazakhstan: Mobilizing finance to help achieving Sustainable Development Goals Requesting activity type: Knowledge and Support Technical Assistance (KSTA) EO Clinic relevant Thematic Groups: TG4 (Disaster Risk Management), TG10 (Water Resources Management) Work Order number: EOC0006 Work Order status: Completed Work Order start: 2020 May 07 Work Order end: 2020 Sep 15 Background ADB is supporting the government of Kazakhstan in creating a platform among development partners and mobilising finance to help achieve the Sustainable Development Goals (SDGs). Kazakhstan’s commitment to realising the 2030 SDG Agenda is in line with the country’s aspirations to improve people’s quality of life as envisioned in the 2025 Strategic Development Plan as well as in the Kazakhstan 2050 Strategy. The recently kicked-off KSTA is aligned with key operational priorities of Strategy 2030 of ADB by mainstreaming the use of high-level technologies in Developing Member Countries (DMC). The KSTA is also fully aligned with the country partnership strategy for Kazakhstan, 2017–2021, which highlights ADB’s role in assisting with managing the social impact of technology solutions in areas such as municipal services, e-commerce, agri-business, green economy, and finance. National Sustainable Development Strategies (NSDS) are based on several sustainable goals, including SDG 11 – “Make cities and human settlements inclusive, safe resilient and sustainable”. The city of Nur-Sultan and surrounding areas are affected by river floods. In September 2019 ADB in partnership with ESA agreed to provide technical support to KGS (Kazakhstan Gharysh Sapary) to improve flood simulation and calculation of water volume in reservoirs for the Nura and the Ishim river basins. KGS is the state-owned space entity that has been appointed by the Committee on Water Resources of the Ministry of Ecology, Geology and Natural Resources and by the Committee for Emergency Situations of the Ministry of Internal Affairs to provide solutions to mitigate flood-related hazards and risks. Problems to be Addressed and Geospatial Information Gaps The technical approach that is being discussed by the stakeholders for solutions to mitigate the flood-related issues is quite comprehensive. It implies the use of EO, in-situ observations and hydraulic modelling, in order to predict flood scenarios, and how water levels will evolve during certain rainfall regimes. In the end there is a need to develop a model prototype with the following parameters: water velocity and flow directions, and predicted areas of flooding. However, the scope of the foreseen support may be divided in different phases and modules. The scope of the present RFP is limited to demonstrate some baseline products and trend analysis through the use of optical and SAR data to map river and lake ice and their evolution in time. River ice controls the winter flow regime of rivers and compromises the operation of hydrometric stations, governs the water intake and discharge activities of municipalities and businesses. Particularly during spring break-up, ice can create jams and floods that endanger infrastructure such as bridges. The users would like to understand better the advantages and limitations of the EO-based datasets that could contribute to the water balance and flood risk modelling, in particular when confronted with information layers they might have from other sources. Information Services to be Delivered Service 1: Snow Cover Dynamics Service 2: River and Lake Ice Dynamics Project Documents Work Order Report: EOC0006_WOR_v01.pdf |
| EO Clinic: Strengthening Drought Resilience in Arid and Semi-Arid Lands in Ethiopia | EO Clinic support requested by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Ethiopia Office Requesting activity: Strengthening Drought Resilience in Arid and Semi-Arid Lands (SDR-ASAL) Requesting activity type: Technical [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | Sustainable Development | agriculture, climate, rivers, surface water, sustainable development, transport, urban, water resources | EO Clinic support requested by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Ethiopia Office Requesting activity: Strengthening Drought Resilience in Arid and Semi-Arid Lands (SDR-ASAL) Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG2 (Climate Change), TG8 (Transport), TG9 (Urban), TG10 (Water Resources Management), TG11 (Non-EO Information and Analytics) Work Order number: EOC0012 Work Order status: Completed Work Order start: 2020 Sep 25 Work Order end: 2021 Jan 15 Background Over 7 million people live in the Afar and Somali Regions in Ethiopia. Most of them are pastoralists and agro-pastoralists who depend on semi-mobile livestock for their livelihoods. Currently their economic and social systems are under pressure due to population growth and the impact of climate change (increasing frequency and severity of droughts and floods). GIZ has a programme in place, called the Strengthening drought resilience (SDR) programme to help facing this situation. Furthermore, GIZ in collaboration with the Ethiopian Ministry of Agriculture, Livestock and Natural Resources, has developed the “Strengthening Drought Resilience in Arid and Semi-Arid lands” (SDR-ASAL) program. The objective of this programme is to develop a holistic approach for land rehabilitation in this area. One of the main aspects of SDR-ASAL is to rehabilitate degraded water catchments and pasture areas in dry valleys. In this initiative, state and non-state actors together with pastoral and agro-pastoral communities have created the conceptual foundations for the rehabilitation and use of dry valleys and their productive use. Some measures that can be developed are for example simple dry-stone and the construction of weirs to reduce the speed of runoff water and to retain eroded soil in the river channel. The objective is to build water spreading weirs/cascades in suitable locations (dry valleys) to control flash floods from the highlands and direct some of the precious water to low-lying plains where it can be stored in the soil. This will allow reintroducing agricultural practices. In addition, groundwater aquifers can be fed rather than letting the water rush through the valley unused. This technique was developed in the 1990s and tested very successfully in various countries in western Africa. It is now introduced in the Ethiopian lowlands starting 2014 and ever since has been further adjusted to the local conditions. There is a huge potential in the Ethiopian lowlands to improve rural development and the livelihood systems by this type of rehabilitation of degraded watersheds. Problems to be Addressed and Geospatial Information Gaps The overall purpose of the present EO Clinic activation is to support GIZ Ethiopia and its partners in the site selection process (site identification and delineation) for future weir construction project activities using EO data, i.e. to conduct a site suitability analysis. “In order to identify the most suitable project sites dry valleys for their project, GIZ Ethiopia created a catalogue of site selection criteria called “Cascade Suitability Matrix – GIZ SDR”. This catalogue includes physical, biological and social location factors that are combined to identify most suitable areas for project implementation. Examples are physical aspects (sufficient stones and sand available for construction, closest permanent water point, road access), biological aspects (predominant soil type, signs of cultivation), social aspects (proximity of marketplace, presence and maintenance of enclosures, proximity of the next hamlet/village, number of hamlets/villages in this area). In the absence of data on dry streambeds, it is expected that the Contractor develops a limited AoI within the AFAR region by performing a hydrological analysis on an available DEM to identify likely stream beds. The AoI should exclude permanent streams (i.e. streams of the greatest Strahler value). The Contractor shall perform the above analysis and present/discuss the result, a suitable AoI consisting of a buffer region around likely dry stream beds to the stakeholders prior to the main site suitability analysis. The buffer shall be chosen keeping in mind the distances mentioned in the Cascade Suitability Matrix. It is acknowledged that not all factors defined in the Cascade Suitability Matrix (physical, biological and social) can be mapped with EO. The Contractor shall identify which factors can be characterised from space, and select satellite imagery with resolutions suitable for the detection of the features described in the matrix (e.g. villages). No general minimum mapping unit or resolution are defined, as these will depend on the solution provided by the Contractor. Based on EO information, a scoring matrix shall be completed. The data will be used to identify most promising/suitable new project sites for the effective and sustainable rehabilitation and use of degraded land in dry valleys of the Ethiopian lowlands. The most suitable sites will be evaluated for future projects. Information Services to be Delivered Service 1: Factors Identification and Assessment Service 2: Site Suitability Map Project Documents Work Order Report: EOC0012_WOR_v01.pdf |
| EO Clinic: Surface Water Mapping in Kazakhstan | EO Clinic support requested by: Asian Development Bank (ADB), Kazakhstan Resident Mission (KARM) Requesting activity: Republic of Kazakhstan: Mobilizing finance to help achieving Sustainable Development Goals Requesting activity type: [...] | E-GEOS (IT) | Sustainable Development | disaster risk, lakes, natural hazards and disaster risk, rivers, surface water, sustainable development, water resources | EO Clinic support requested by: Asian Development Bank (ADB), Kazakhstan Resident Mission (KARM) Requesting activity: Republic of Kazakhstan: Mobilizing finance to help achieving Sustainable Development Goals Requesting activity type: Knowledge and Support Technical Assistance (KSTA) EO Clinic relevant Thematic Groups: TG10 (Water Resources Management) Work Order number: EOC0003 Work Order status: Completed Work Order start: 2019 Dec 17 Work Order end: 2020 Apr 15 Background ADB is supporting the government of Kazakhstan in creating a platform among development partners and mobilising finance to help achieve the Sustainable Development Goals (SDGs). Kazakhstan’s commitment to realising the 2030 SDG Agenda is in line with the country’s aspirations to improve people’s quality of life as envisioned in the 2025 Strategic Development Plan as well as in the Kazakhstan 2050 Strategy. The requesting KSTA is aligned with key operational priorities of Strategy 2030 of ADB by mainstreaming the use of high-level technologies in Developing Member Countries (DMC). The KSTA is also fully aligned with the country partnership strategy for Kazakhstan, 2017–2021, which highlights ADB’s role in assisting with managing the social impact of technology solutions in areas such as municipal services, e-commerce, agri-business, green economy, and finance. National Sustainable Development Strategies (NSDS) are based on several sustainable goals, including SDG 11 – “Make cities and human settlements inclusive, safe resilient and sustainable”. The city of Nur-Sultan and surrounding areas are affected by river floods. In September 2019 ADB in partnership with ESA agreed to provide technical support to KGS (Kazakhstan Gharysh Sapary) to improve flood simulation and calculation of water volume in reservoirs for the Nura and the Ishim river basins. KGS is the state-owned space entity that has been appointed by the Committee on Water Resources of the Ministry of Ecology, Geology and Natural Resources and by the Committee for Emergency Situations of the Ministry of Internal Affairs to provide solutions to mitigate flood-related hazards and risks. Problems to be Addressed and Geospatial Information Gaps The technical approach that is being discussed by the stakeholders for solutions to mitigate the flood-related issues is quite comprehensive. It implies the use of EO, in-situ observations and hydraulic modelling, in order to predict flood scenarios, and how water levels will evolve during certain rainfall regimes. In the end there is a need to develop a model prototype with the following parameters: water velocity and flow directions, and predicted areas of flooding. However, the scope of the foreseen support may be divided in different phases and modules. The scope of the present request is limited to demonstrate some baseline products and trend analysis through the use of optical and SAR data to map water body extents and monitor their evolution in time, as well as the use of radar altimetry to monitor surface water levels. The users would like to understand better the advantages and limitations of the EO-based datasets that could contribute to the water balance and flood risk modelling, in particular when confronted with information layers they might have from other sources. Visualising multitemporal data via a geoportal is also required, as well as presenting cost estimates for multi-annual service provision. Information Services to be Delivered Service 1: Inventory of Water Bodies and Associated Dynamics Service 2: Virtual Water Level Monitoring Stations Service 3: Estimates of Total Water Volumes Project Documents Work Order Report: EOC0003_WOR_v1.2.pdf |
| EO Clinic: Urban and Territorial Land Use Planning in Mexico and Colombia | EO Clinic support requested by: Inter-American Development Bank Requesting activity: Urban and Territorial Land Use Planning for LAC Cities: Case studies in Hermosillo (Mexico) and Cartagena (Colombia) Requesting activity type: Grant EO [...] | GeoVille (AT) | EO Clinic support requested by: Inter-American Development Bank Requesting activity: Urban and Territorial Land Use Planning for LAC Cities: Case studies in Hermosillo (Mexico) and Cartagena (Colombia) Requesting activity type: Grant EO Clinic relevant Thematic Groups: TG1 (Agriculture), TG3 (Coastal Zone Management), TG4 (Disaster Risk Management), TG6 (Forestry), TG9 (Urban), TG10 (Water Resources Management), TG11 (Non-EO Information and Analytics) Work Order number: EOC0023 Work Order status: Under Execution Work Order start: 2022 Jan 18 Work Order end: Background During the last decades, the rapid and unplanned urbanization process in LAC (Latin America and the Caribbean) has resulted in daunting challenges. While in 1960, only 49.5% of the population lived in cities, by 2019, the urbanisation rate has reached 81%. This rapid urbanisation process, characterised by unplanned growth, has resulted in an uncontrolled and low-density expansion of the urban footprint, exacerbating daunting challenges for the region’s development, such as: 1) disproportionate occupation of land to population growth and inadequate patterns of land use; 2) housing and infrastructure deficits that result in informal housing and settlements; 3) limitation of institutional capacities and resources; 4) increasing proportion of the population living in poverty; and 5) growing environmental and social inequities. Fragmented and unplanned urban sprawl has pushed low-income households to the peripheries, mainly to risk and degraded areas, usually distant and disconnected from the cities’ social and economic activities, driving unregulated informal housing production. Some of the drivers of these issues are the lack of urban and spatial planning capacity at the local level including the lack of tools and urban planning mechanisms, and that urban policies have been focused on finance infrastructure without creating mechanisms to ensure access to serviced and well-situated land for integrated development. Problems to be Addressed and Geospatial Information Gaps Through the proposed activity IDB and its clients would like to gain a better understanding of the interac-ti0ns between urban areas and their wider hinterland, for two cities: Hermosillo (Mexico) and Cartagena (Colombia). While the evolution of the urban areas themselves is relatively well-known, there is little in-formation about the transformations on a wider, regional scale, in particular regarding linkages between urbanisation and water availability, changes in agricultural practices and in general transformations of land use classes before and after some specific historical events that took place in the wider urban areas and relevant major river basins. The Bank activity is part of an initiative that will support the application of mechanisms to manage spatial planning in LAC cities and regions, where IDB’s objectives are twofold: 1) to identify urban densification and expansion patterns of cities, based on evidence from statistical analysis of the spatial dynamics and from case studies, and 2) to understand if the territorial planning processes that cities have undergone are creating adequate room for densification – within existing urban footprints and on their peripheries – for the industrial, commercial, civic, cultural, and residential activities, ensuring that cities are productive, equitable, sustainable and climate-resilient. The initiative will offer evidence for local authorities to get a realistic sense of how much land needs to be prepared to improve urban expansion between 2020 and 2050 and the territorial planning for the hinterland at the regional scale. It will also propose strategies for territorial planning, emphasising the policy implications of the findings and on how they can lead to real improvements in territorial planning practices in the region. The two selected cities represent two extremes in terms of water availability: scarcity in Hermosillo and abundance in Cartagena. Common for both cases is the need for information on the bigger, regional picture, on the connections between urban areas and their hinterland, and the transformations that have taken place affecting the entire landscape. The Bank team is interested in finding and showcasing evidence of how crisis events impact the entire natural environment. The Situation in Hermosillo and the Sonora and Yaqui River Basins, Mexico Hermosillo is the capital and largest city in Sonora State, as well as the primary economic centre for the state and the region. As of 2015, its metropolitan area had a population of approximately 900,000 inhabit-ants, which is effectively more than double of what it was in the 1990’s. The city is critically short of water and needs to reach deep into its rural hinterland to meet its needs. Water reaches the city from a number of sources, including wells and aqueducts along the river Sonora upstream from the city. This often encroaches on local, rural, traditional, and frequently indigenous ways of managing its water and land re-sources, and restricts development of the local and regional economy With the inauguration of the Independencia aqueduct on March 30 2013, the city now receives a substantial share of water also from the Yaqui river basin, adjacent to the Sonora basin. The aqueduct connects to the Plutarco Elias Calles Reservoir at El Novillo. This development often stands against the interest of agricultural producers and Yaqui native people in the basin, with uncertain long-term impacts on the social-ecological systems of the affected basins. A major event to further complicate the water availability and overall situation in the two river basins took place on 6 August 2014 through an accident at the Buenavista del Cobre vast open-pit copper mine at Cananea in the northern part of the Sonora river basin. Considered one of the worst environmental disasters in Mexico in modern times, the spill of copper sulfate solution into a tributary of the Sonora River affected seven municipalities with over 20,000 people. The Arroyo Las Tinajas and Bacanuchi rivers as well as the main stream of the Sonora River were affected. The Situation in Cartagena and the Canal del Dique, Colombia Cartagena is the capital of the Bolívar Department in Colombia. With a population of approximately 1 million, it is the second-largest urban area in the region, and the sixth-largest in the country. The city and its beaches represent the nation’s principal tourist destination. The city faces the Caribbean Sea to the west, and the Cartagena Bay to the south. Since the 17th century the bay is connected to the Magdalena River by the Canal del Dique, a 114 km long navigation route. After Colombian independence the canal was abandoned, increasing centralisation leaving the city without resources to maintain it. Rectification of the canal since the early 20th century, and the increasing deforestation along the banks of the Magdalena River have caused significant sedimentation in Cartagena Bay, affecting coral and wetland ecosystems in the region. The last important maintenance work was done in the 1950’s with some more improvements made by local authorities in the 1980’s. Notwithstanding smaller works, significant maintenance of the canal has been delayed. As a result of unusually strong La Niña year, in November-December 2010 parts of the canal embankments collapsed, causing severe floods with at least 174 casualties and thousands of homeless inhabitants . In recent years the national government is planning or has initiated specific upgrade and maintenance works to improve the navigability of the canal, reduce flood risk and increase overall economic prosperity in the region. Information Services to be Delivered Service 1: Historical Land Use and Land Cover Transitions | ||
| EO Clinic: Urban Mobility Plan Development in Chisinau, Moldova | EO Clinic support requested by: UNDP Moldova Office Requesting activity: Urban Mobility Plan Development / Urban Collaborative New Evidence Platform Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG8 [...] | GeoVille (AT) | Sustainable Development | infrastructure, land cover, population, sustainable development, transport, urban | EO Clinic support requested by: UNDP Moldova Office Requesting activity: Urban Mobility Plan Development / Urban Collaborative New Evidence Platform Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG8 (Transport), TG9 (Urban), TG11 (Non-EO Information and Analytics) Work Order number: EOC0001 Work Order status: Completed Work Order start: 2019 May 23 Work Order end: 2019 Jul 17 Background Massive and speedy urbanisation provides both development opportunities but also threats to sustainable human development and social inclusion. Cities like Chisinau are growing in an uncontrolled manner, without clear development plans and strategies for sustainable and green urban growth. This provides for major risks related to the social exclusion and marginalisation of certain groups, lacking or under-developed infrastructure, threatened urban security and safety, emergence of new problems related to health, air pollution, traffic congestion, unauthorised or illegal constructions, sometimes worst suboptimal urban mobility and so on. On the other hand, urbanization provides for new opportunities in housing, education, urban mobility, development of new infrastructures, energy transition, green technologies, etc. UNDP Moldova is establishing a new evidence platform, i.e. a collaborative platform for engaging all relevant stakeholders in the generation and use of new evidence deriving from big, thick and spatial data. UNDP and its local partners will use the new evidence to generate insights and understand development patterns and then use the new evidence for experimentation work, i.e. generation and testing of safe-to-fail solutions to achieve SDGs at local level. Initially, the platform is to cover capital of the republic, the Municipality of Chisinau. The longer-term ambition is to connect many other municipalities, partners and traditional and emerging donors. Smaller cities that could become poles of growth in the future are of particular interest (Cahul, Ungheni, Balti, Orhei and similar). Problems to be Addressed and Geospatial Information Gaps The Government of Moldova and the Municipality of Chisinau are interested in characterising and understanding the urban development patterns and in co-designing (together with citizens) safe-to-fail experimental solutions to solve emerging problems or (better) anticipate what might happen in the next 5–10 years or so. One major problem in Chisinau is urban mobility. With the support of UNDP, the city is creating an urban mobility plan, in which existing and new options for urban transport will be developed (including public transport). Detailed, up-to-date, consistent and reliable information is however scarce on the size and distribution of the population, on the proportion of the population that has convenient access to public transport, on the location and occurrence patterns of traffic congestions, and on gaps in small infrastructure (bike lanes, paved surfaces, sidewalks, etc.) that could alleviate congestions. Furthermore, information is needed to understand the long-term evolution of land use and fragmentation patterns, for urban planning, for the prevention of the negative impacts of urbanisation, and especially for the siting of new infrastructure (e.g. for a planned city bypass road) and the access to green areas. The latter is seen as key to enable multi-actor partnerships between stakeholders responsible for urbanism, environment, health, education (social cohesion), leisure, etc. UNDP also requires support with the cross-checking and innovative merging of satellite-based information with existing non-satellite data, and the generation of specific insights and patterns to be used for experimentation purposes. Information Services to be Delivered Service 1: Urban and Peri-Urban Land Use/Land Cover Classification and Associated Changes Service 2: Census-Based Population Distribution Service 3: Case Study Definition and First Insights into Recent Population and Mobility Trends Project Documents Work Order Report: EOC0001_WOR_V1.pdf Further Reading July 2019 UNDP article: Chisinau’s Data Collaborative: Moving with the Times August 2019 news item: Supporting the Urban Development in Chișinău, Moldova |
| EO Clinic: West Bengal Drinking Water Sector Improvement Project, India | EO Clinic support requested by: Asian Development Bank (ADB), South Asia Regional Department (SARD), Urban Devel-opment and Water Division (SAUW) Requesting activity: Nature-Based Solutions – Water Storage in West Bengal India Requesting [...] | EVERIS AEROESPACIAL Y DEFENSA S.L.U (ES) | Sustainable Development | land cover, rivers, surface water, sustainable development, water resources | EO Clinic support requested by: Asian Development Bank (ADB), South Asia Regional Department (SARD), Urban Devel-opment and Water Division (SAUW) Requesting activity: Nature-Based Solutions – Water Storage in West Bengal India Requesting activity type: Technical Assistance (TA) EO Clinic relevant Thematic Groups: TG10 (Water Resources Management) Work Order number: EOC0015 Work Order status: Completed Work Order start: 2021 Mar 03 Work Order end: 2021 Jul 26 Background ADB is working with the Government of India to provide safe, sustainable, and inclusive drinking water service to about 1.65 million people in three districts of West Bengal state, India, affected by arsenic, fluoride, and salinity. With about 85% of water in India’s rural areas coming from groundwater, some 27 million people are at risk from arsenic and fluoride contamination. Arsenic in drinking water can lead to a range of problems including cancer, while high exposure to fluoride can cause dental or skeletal fluorosis and bone diseases. Increased withdrawal of groundwater also leaves the area more vulnerable to climate change and disasters, especially regular flooding, and is causing an intrusion of salinity into the water. ADB’s West Bengal Drinking Water Sector Improvement Project (WBDWSIP) will provide safe and sustainable drinking water in the Bankura, North 24 Parganas and Purba Medinipur (East Medinipur) districts of West Bengal state. It will introduce an innovative and sustainable institutional framework and advanced technology for smart water management to enable efficient service delivery in project districts. Due to a combination of monsoon rains and tidal movements, at a proposed groundwater extraction point along the Rupnarayan, the salinity of river water is expected to exceed the desired threshold during certain periods of the year. To help this situation, several options had been explored, and a Nature-Based Solution (NBS) to improve storage of flood water has been shortlisted. The NBS for surface storage is to develop abandoned river channels, as storages, along the river Rupnarayan. These can be identified by mapping inundation before and after the monsoon. Channels that were dry during pre-monsoon, but with water during post-monsoon, are potential NBS sites of storage. Problems to be Addressed and Geospatial Information Gaps ADB and its partners have no comprehensive overview of the history and availability of surface water resources and potential surface storage sites in the three aforementioned districts of West Bengal state. The requested services will help by providing an inventory and detailed characterisation of potential additional water storage sites by focussing on the non-permanent water bodies in the area. The objective is to provide a rapid assessment of suitable NBS water storage sites in Purba Medinipur based on remote sensing. Output will be a prioritised inventory of suitable sites which will serve as background for further detailed investigations. Information Services to be Delivered Service 1: Waterbody Inventory and Dynamics Service 2: Land Use and Land Cover Service 3: Potential Surface Storage Site Inventory Project Documents Work Order Report: EOC0015_WOR_v1_r.1.0.pdf Final Presentation: EOC0015_FPR_v2.1.pdf |
| EO for a Resilient Society: Intertidal Topography Mapping in the temporal domain (SAR-TWL), towards operationalisation of a global monitoring tool. | Intertidal zones form an interface between land and sea. They are important features of the coastal landscape providing a multitude of ecosystem services and forming a critical habitat for a wide range of species. Satellite Earth Observation [...] | National Oceanography Centre (NOC) (GB) | Regional Initiatives | Atlantic, Ecosystems, ocean, permanently open call, regional initiatives, SAR, Sentinel-1 | Intertidal zones form an interface between land and sea. They are important features of the coastal landscape providing a multitude of ecosystem services and forming a critical habitat for a wide range of species. Satellite Earth Observation (EO) unlocks new capabilities for monitoring intertidal zones, which are under significant pressure from multiple sources including coastal development, impacts from upstream land use and changes in sea level. The unique capabilities of EO for intertidal mapping have been demonstrated by research groups such as Murray et al. who, using optical data from the Landsat archive, have shown a declining trend in the global extent of intertidal flats. To meet the higher spatial and temporal monitoring needs of regional and local authorities the UK National Oceanography Centre (NOC) have developed a new approach based on S1 SAR (Synthetic Aperture Radar), making use of temporal waterline methods (TWL). This time domain, or per pixel approach, reduces the manual interpolation steps inherent in optical methods and unlocks a new and unique way of observing intertidal dynamics. The work builds on nearly two decades of research into environmental monitoring with X-Band Marine Radar , complementing the synoptic and temporal frequencies that in-situ radar monitoring provides .Following two years of development and demonstration carried out in partnership with the Channel Coastal Observatory, the Environment Agency, Wales Coastal Monitoring Centre and local authority programmes, this new project will enable further development of the methods and the processing software. The objective is to enable more widespread access to this innovative method, with inherent potential for long term monitoring of intertidal dynamics at local to national scales. Previous development work was carried out as part of the Atlantic Region Initiative, under the Blue Economy, Marine Spatial Planning and Innovation Clusters project. https://eo4society.esa.int/wp-content/uploads/2022/11/MorecambeBay_TWL_POLPRED_MSL_filt.mp4 Video shows intertidal elevations for Morecambe Bay, from January 2017 to August 2022. At 310km2 Morecambe Bay is the largest intertidal area in the UK. ————————————————————————————– Murray N. J., Phinn S. R., DeWitt M., Ferrari R., Johnston R., Lyons M. B., Clinton N., Thau D. & Fuller R. A. “The global distribution and trajectory of tidal flats” Nature. 565:222-225. (2019). See Bell, Bird & Plater “A temporal waterline approach to mapping intertidal areas using X-band marine radar” Coastal Engineering (2016), & Bird, Bell & Plater “Application of marine radar to monitoring seasonal and event-based changes in intertidal morphology” Geomorphology https://marlan-tech.co.uk/ |
| EO FOR YEMEN | EO4YEMEN aims at exploring new technological and scientific approaches to overcome existing limitations and provide an effective support to NGO in Yemen for the planning and implementation of on-field operations. The focus is on: Super [...] | SISTEMA GMBH (AT) | Enterprise | Sentinel-2, sustainable development | EO4YEMEN aims at exploring new technological and scientific approaches to overcome existing limitations and provide an effective support to NGO in Yemen for the planning and implementation of on-field operations. The focus is on: Super resolution algorithms applied to Sentinel-2 AI based Change detection Exploitation of new sources of satellite data ( VHR night times acquisitions), precipitation, temperature or soil moisture measurements Analytics for retrieving events and indicators Three use cases have been defined with the end users: critical infrastructure monitoring, locust impact assessment, population movements analysis |
| EO Innovation Platform Testbed Poland | The project has validate procurement mechanisms for a cloud-based resource tier, offering bundled infrastructure (IaaS) and data services (DaaS) to the users, based at minimum on MERIS full resolution, S-2 and Landsat data, possibly extending to [...] | CREOTECH INSTRUMENTS SA (PL) | Digital Platform Services | platforms | The project has validate procurement mechanisms for a cloud-based resource tier, offering bundled infrastructure (IaaS) and data services (DaaS) to the users, based at minimum on MERIS full resolution, S-2 and Landsat data, possibly extending to S-1 and S-3 data. |
| EO Law – EO derived information in support of Law Enforcement derived information in support of Law Enforcement | The EO Law project aims at demonstrating the benefits of using EO based information together with state of the art ICT data analytics and non-EO data fusion in support of Law Enforcement in various domains, from environment to terrorism, and [...] | GMVIS SKYSOFT S.A. (PT) | Enterprise | platforms, security | The EO Law project aims at demonstrating the benefits of using EO based information together with state of the art ICT data analytics and non-EO data fusion in support of Law Enforcement in various domains, from environment to terrorism, and counter proliferation. For this purpose the consortium that will develop the EO Law has engaged relevant users and stakeholders that work in the domains covered in the project, providing context and related requirements to support the definition of service specifications, in order to develop capabilities that can really tackle operational problems of the various areas in support of law enforcing. The domains and services that will be approached in the project are the following: Environmental Crimes -Illegal Logging. In the last few years, illegal logging has emerged as a serious worldwide concern in the forest sector. By its nature of being illegal it is also clandestine, making it difficult to estimate with precision how much wood is logged illegally, where exactly, and by whom. What is known though, is that illegal logging remains a very big problem despite existing efforts to fight it. In this context, the consortium will develop services that can help on the investigation and mitigation of the consequences that result from the illegal logging activities, namely: Detection of routes for movement of timber Detection of forest change Detection of logging support infrastructure Crimes against humanity – As crimes against humanity are still occurring on a regular basis, there are in contrary often not “visible” to the wider public. This is based mainly on the fact that hostile actions are taken place most of the times in remote and less-accessible areas, where accessibility is limited either due to e.g. armed conflicts or wars, or due to governmental restrictions. As the amount of in-sight information rapidly increased during the last years due to e.g. social media, the confidence level of the information overload was decreasing making it harder to distinguish between “wrong” or “right”. EO-data and EO-derived information can be seen as an independent information source suitable to verify on-sight information and to gain a more sound evidence of actions taken place. The services that will be provided are: Multi-criteria mass grave site suitability model Fire detection in settlements Settlement development & change detection Terrorism and organized crime – Societies today constantly face terrorist and organize crime actions, which require new methods for modelling and analysis, inherited from various sectors and technological domains. Law enforcement organizations, analysts and field operators fighting terrorism and organized crime need front-line integrated technologies to support their cooperative work. The goal of the services will be spatially depict the activities of different terrorist organizations by means of generalized locations, anomaly characterization/interpretation and also activity analysis. Preparing helpful and applicable/realistic services requires the fusion of multi-source data combining unstructured (descriptive and informational data sources) and structured geospatial data (vector and satellite data) as well as information from open source and public databases like social media networks, crowdsource information etc. The services that will be provided are: Comprehensive and contextual imagery intelligence analysis combing EO data and media sources Hotspot detection layer with potential training camps Hotspot detection layer with potential abnormal activities related to terrorism and organized crime All the services will be deployed through a virtual web platform that will be used for service ordering, processing and delivery. This platform will be composed by a set of software components integrated together and implemented on a data-rich cloud infrastructure so that the EO data can be accessed online and without the need to transfer it from external sources. |
| EO Mammals | Earth Observation (EO) data has been extensively used over the years to assist on the management of marine mammal populations either by establishing protected areas where stakeholders’ activity are reduced, or by minimizing the impact of [...] | THE OCEANIC PLATFORM OF THE CANARY ISLANDS (ES) | Applications | applications, permanently open call | Earth Observation (EO) data has been extensively used over the years to assist on the management of marine mammal populations either by establishing protected areas where stakeholders’ activity are reduced, or by minimizing the impact of anthropogenic threats. It is considered a basic and essential tool for the conservation of species, both by researchers and governments. Some examples include weekly predictions of fin whale (Balaenop-tera physalus) distribution that represent a valuable conservation tool in marine protected areas to prevent collisions with ships. Remotely sensed environmental parameters have the potential to identify biological hotspots for cetaceans and to therefore establish areas of marine conservation priority. Satellite measurements of ocean have proved an effective tool to map the environmental variables and processes occurring. It is the main tool for measuring ocean productivity (ocean colour) and its response to climate change/variability. Other variables also related with the presence and movements of cetaceans can be measured from space, e.g. sea surface temperature, sea surface height, etc. This project aims to identify biological hotspots for cetaceans and help the management of marine protected areas, using Earth Observation and other collaborative network’s data. |
| EO Network of Resources | The increasing size of available satellite mission data sets, together with Information Computer Technology (ICT) advances has resulted in a paradigm shift. Data do not need any more to be downloaded by the user to their local machine for [...] | CLOUDEO AG (DE) | Digital Platform Services | platforms | The increasing size of available satellite mission data sets, together with Information Computer Technology (ICT) advances has resulted in a paradigm shift. Data do not need any more to be downloaded by the user to their local machine for further processing, on the contrary it is the user who can find the data and process them in cloud environments hosted by ICT providers with expandable processing capabilities. The Network of Resources (NoR) is an ESA initiative to facilitate the use of cloud environments by users, building on and enlarging the previous Open Science for Earth Observation (OSEO) call, sponsoring R&D users for the use of commercial platform resources. The NoR call supports research, development and pre-commercial users to innovate their working practices, moving from a data download paradigm towards a bring the user to the data paradigm, considered essential for maintaining competitiveness of European data exploitation. |
| EO SERVICES DEMONSTRATION IN SUPPORT TO WEST AFRICA CAPACITY BUILDING PROGRAM OF THE OECD ABOUT GOLD MINING PRACTICES | This collaborative tool on artisanal gold mining (ASM) and security will take the form of a secure web mapping platform. The prototype will include some layers of geographic information and various satellite images of ASM areas resulting from [...] | Geo212 (FR) | Enterprise | africa, AI4EO, mapping/cartography, platforms, security | This collaborative tool on artisanal gold mining (ASM) and security will take the form of a secure web mapping platform. The prototype will include some layers of geographic information and various satellite images of ASM areas resulting from automated detection by artificial intelligence, and will propose spatialized indicators and analytics, for example on the evolution of gold ASM sites, or the impact of gold panning on security. This preliminary one-year project for the Liptako-Gourma Authority (LGA) and its three member states (Mali, Niger and Burkina Faso) also aims to analyse the LGA’s needs for geolocalised information, to set up a roadmap for the development of the final observatory and to address the project’s governance. This project develops an innovative perspective at different levels: The first innovation consists in testing image processing (AI and SAR coherence change detection) to identify artisanal mining in Sahelian environment The second innovation is to consider the cooperation between LGA, ministries, agencies, etc as an important success point addressed, and the involvement of anthropologists to drive this challenge is an original approach. They will introduce social skills to analyse and optimize the collaboration between actors The third innovation consists in developing statistical tools to analyse the spatial and temporal correlation between artisanal mining (legal and illegal) and violent acts. Geo212 is leading this project in association with two partners: Anthropolinks and Pixstart. The OECD is supporting the project, in connection with its work on due diligence for responsible mineral supply chains in conflict or high-risk areas. |
| EO SUPPLY CHAIN QUALITY ASSURANCE, MANAGEMENT AND FACILITIES – EXPRO+ | The EOSure project is examining how to better understand and improve quality assurance of the end-to-end Earth Observation (EO) supply chain, from upstream EO satellite data providers to downstream end users who use products and services based [...] | TELESPAZIO VEGA UK LIMITED (GB) | Enterprise | generic platform service | The EOSure project is examining how to better understand and improve quality assurance of the end-to-end Earth Observation (EO) supply chain, from upstream EO satellite data providers to downstream end users who use products and services based on EO data. EOSure news Telespazio |
| EO tracking of marine debris in the Mediterranean Sea from public satellites | One of the most significant unknown factors in marine debris is the flux of plastic from land based sources into the marine environment. This project is testing techniques to combine EO and UAV data to detect different types and volumes of [...] | ARGANS LIMITED (GB) | Enterprise | oceans, permanently open call | One of the most significant unknown factors in marine debris is the flux of plastic from land based sources into the marine environment. This project is testing techniques to combine EO and UAV data to detect different types and volumes of plastic in order to establish a methodology to characterize this flux in hotspot areas which are the main sources of plastic. |
| EO4CBI: Earth Observation for City Biodiversity Index (DUE Innovator III Series) | Capturing the status and trends of biodiversity and ecosystem services in urban landscapes represents an important part of understanding whether a metropolitan area is developing in a sustainable manner. The City Biodiversity Index (CBI) was [...] | SPACE 4 ENVIRONMENT (LU) | Applications | applications, urban | Capturing the status and trends of biodiversity and ecosystem services in urban landscapes represents an important part of understanding whether a metropolitan area is developing in a sustainable manner. The City Biodiversity Index (CBI) was developed by the Convention on Biological Diversity (CBD) as a tool to evaluate the state of biodiversity in cities and provide further insights to improve conservation efforts in urban areas. It consists of 23 indicators designed to help cities monitor their progress in implementing conservation efforts and their success in halting the loss of biodiversity as formulated in the Aichi biodiversity targets of the CBD. The EO4CBI project assessed how satellite-based data, in combination with appropriate in-situ and ancillary data, can produce innovative and cost-effective solutions to the implementation of the four CBI indicators: – CBI indicator 1 on “Proportion of natural areas in city”; – CBI indicator 2 on “Connectivity measures and ecological networks to counter fragmentation”; – CBI indicator 11 on “Regulation of quantity of water”; – CBI indicator 12 on “Climate regulation: carbon storage and cooling effect of water”. The products were validated on 10 cities (Addis Ababa, Barcelona, Buenos Aires, Edmonton, Hamilton, Lisbon, Portland, Southern Luxembourg, Stockholm and Tallinn). |
| EO4Cerealstress – Theme 3: Crop response to multiple stressors | Despite advances in agricultural production, approximately 800 million people around the globe still face severe food insecurity. Biotic and abiotic agricultural stressors reduce and limit productivity (e.g., yield reduction) and ecosystem [...] | UNIVERSITY OF SOUTHAMPTON (GB) | Science | agriculture, agriculture science cluster, crops and yields, Diseases and Pests, Ecosystems | Despite advances in agricultural production, approximately 800 million people around the globe still face severe food insecurity. Biotic and abiotic agricultural stressors reduce and limit productivity (e.g., yield reduction) and ecosystem services (e.g., loss of carbon sequestration). These devastating impacts are increased by climate change, particularly by frequent and stronger extreme weather events. EO4Cerealstress will evaluate the synergistic use of multi-source Earth Observation data, particularly hyperspectral data, in-situ crop physiological parameters, soil, climate, and other ancillary data- taking advantage of their complementarity – to understand the effects of multiple stressors and their cumulative effects on crops. New and planned European satellite missions are providing data at high spatial, spectral and temporal resolutions, which offer the opportunity not only to understand and monitor the impacts of single crop stressors but also multiple crop stressors. The project aims to develop products that can be used to monitor these stressors and provide a scientific roadmap for the future development of EO products and techniques for monitoring multiple crop stressors. EO4Cerealstress will engage the user community and scientists in order to develop a scientific roadmap that will provide recommendations to the European space agency and the European Commission on priority scientific issues that need to be addressed to further the understanding and monitoring of the impacts of multiple stressors on crops. |
| EO4GHRO: A MULTI-SENSOR SYNTHESIS FOR THE SPATIOTEMPORAL QUANTIFICATION OF NEAR-SURFACE DENSITY ACROSS THE GREENLAND ICE SHEET | Expected sea-level rise through the remainder of the 21st century has been primarily attributed to the continued melting of the Greenland Ice Sheet (GrIS). This loss of ice not only directly threatens coastal infrastructure around Europe but [...] | Technical University of Denmark (DK) | Science | altimeter, Arctic, CryoSat, Glaciers and Ice Sheets, living planet fellowship, Sentinel-3, SMOS | Expected sea-level rise through the remainder of the 21st century has been primarily attributed to the continued melting of the Greenland Ice Sheet (GrIS). This loss of ice not only directly threatens coastal infrastructure around Europe but precipitates second-order effects such as proliferation of diseases, crop instability and increased health stressors. Therefore, there is a necessary and increasingly urgent need to improve our ability to monitor and project the evolution of the GrIS through both time and space. Near-surface density is the means through which spaceborne radar altimetry-derived changes in the surface elevation of the Greenland Ice Sheet (GrIS) are converted to changes in ice mass; the loss of which then contributes to global sea-level rise. Conventional GrIS surface density estimates are derived using numerical regional climate models, whose outputs (e.g., precipitation, temperature, etc.) serve as inputs in firn densification models. These numerical models underlie both calculations of current mass losses and associated sea-level rise from the GrIS (i.e., those observed during the satellite era) as well as projected future mass losses in the face of an ever-warming climate. As such, uncertainty in the nearsurface density of the GrIS directly contributes to uncertainty in projected global sea-level rise. While validated using individual in situ point measurements, there is currently no pan-GrIS observational timeseries against which the modelled near-surface density structure of the GrIS can be compared. The purpose of this work is to fill this fundamental observational gap using novel data analysis algorithms and synthesizing data from multiple European Earth Observation (EO) assets. Timeseries of spatiotemporal changes in the near-surface GrIS dielectric properties will be estimated through the quantitative analysis of Ku-band ESA CryoSat-2 and EC Copernicus Sentinel-3 as well as Kaband CNES/ISRO SARAL radar altimetry data products. These results will then pre-condition the inversion of ESA SMOS passive radiometry measurements in order to produce a final, synthesized, quantitative timeseries of near-surface density across the GrIS. Airborne ESA CryoVEx radar altimetry and swath LiDAR data over the GrIS will be used to validate the joint recovery of both surface roughness and density from radar altimetry and in situ density measurements will be leveraged for both calibration and validation efforts. The state of the European spaceborne EO infrastructure has never been as sophisticated and comprehensive as it is today. And while there are more missions/instruments collecting more data than ever before, the synergistic analysis of these data remains under-developed. This research will synthesize a decade’s worth of EO data in order to produce a new observational dataset aimed at addressing a primary source of uncertainty in projections of global sea-level rise due to melting from the GrIS. Increasing confidence in future sea-level rise estimates will enable more robust assessments of coastal infrastructure vulnerabilities as well as the development, review and refinement of adaption and mitigation measures. |
| EO4MULTIHAZARDS- Earth Observation for high-impact multi-hazards | EO4MULTIHAZARDS aims to use state-of-the-art satellite Earth Observation to improve the understanding of high-impact cascading and compounding multi-hazard events, revealing their underlying drivers and dynamics, and enhancing our ability to [...] | GMV AEROSPACE AND DEFENCE, SA (ES) | Enterprise | disaster risk, natural hazards and disaster risk | EO4MULTIHAZARDS aims to use state-of-the-art satellite Earth Observation to improve the understanding of high-impact cascading and compounding multi-hazard events, revealing their underlying drivers and dynamics, and enhancing our ability to assess their societal and ecological impacts. This project is dedicated to advancing scientific understanding and modeling of multi-hazard events through collaboration with both local and international scientific initiatives. The project main objective is to identify and address scientific needs concerning multi-hazard challenges by extending existing studies and engaging with a diverse scientific community to explore the potential role of Earth Observation in enhancing disaster risk assessment. Four science cases will be designed to develop a deeper understanding of multi-hazard events, including compound events and their various interactions. The goal is to enhance the capability to evaluate exposure, risks, and vulnerabilities practically through the development of scientific knowledge in the defined science cases and demonstrating the impact of scientific progress in high-risk areas. These science cases serve as foundations for the corresponding demonstration cases which will foster collaborations with end-users and practitioners to support timely actions in early warning systems. Collaboration with stakeholders and first responders is pivotal in endorsing early warning systems and facilitating timely responses to hazards. A critical aspect of this initiative is the establishment of an Open Multi-Hazard Events Database adhering to Open Science standards. This platform will ensure reliable data for the scientific community and promote comprehensive research efforts on multi-hazard events. Ultimately, EO4MULTIHAZARDS seeks to actively engage with and contribute to the European research community on multi-hazards by fostering collaboration among team members and stakeholders, and creating a community roadmap. The outcomes of the project will be disseminated through scientific peer-reviewed publications and public engagement materials accessible to a diverse audience. |
| EO4NUTRI: Earth Observation for estimating and predicting crop nutrients | Background: Timely and large-area information on nutrient concentrations in staple crops is lacking which limits our understanding of how nutrients vary across various geographic areas. In the absence of this information, we cannot efficiently [...] | UNIVERSITY OF TWENTE (NL) | Science | agriculture, agriculture science cluster, crop, science | Background: Timely and large-area information on nutrient concentrations in staple crops is lacking which limits our understanding of how nutrients vary across various geographic areas. In the absence of this information, we cannot efficiently guide research activities dedicated to alleviating potential nutrient deficiencies through genetic biofortification or agronomic biofortification by applying fertilizers. Overall goal: EO4Nutri will develop innovative scientific solutions that bring together the capabilities of various Earth Observation (EO) data to estimate and predict the nutrient content of the soil, crop canopy, and harvested crops for several global staple grains. Target crops: maize, rice, sorghum, teff and wheat. Target nutrients: Calcium (Ca), Iron (Fe), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Potassium (K), Selenium (Se), Sulphur (S), and Zinc (Zn) The project will focus on two scientific cases: (1) advancing our understanding of the lifecycle of nutrients from the soil to crop canopy and further to crop grains with innovative analytical techniques and EO data, and (2) deepening our understanding of Nitrogen uptake from soil to crop canopy to crop grains and its relationship to grain protein content using Radiative Transfer Models (RTMs) and machine learning methods. The EO4Nutri team will focus on transferring the developed products and datasets into actionable information that can enhance management and decision support systems dedicated to crop nutrient monitoring. Generated scientific results will be integrated into operational activities and a Digital Twin Earth. |
| EO4PAC – Earth Observation for Permafrost dominated Arctic Coasts | EO4PAC project aims at the development of a roadmap for the next generation of the Arctic Coastal Dynamics database. The focus is on complementation of in situ records with satellite data across the entire Arctic. | b.geos GmbH (AT) | Science | Arctic, coastal zone, permafrost challenge, polar science cluster | EO4PAC project aims at the development of a roadmap for the next generation of the Arctic Coastal Dynamics database. The focus is on complementation of in situ records with satellite data across the entire Arctic. |
| EO4SD – Agriculture and Rural Development | EO4SD - Agriculture and Rural Development project - aims at demonstrating the benefits of EO-based geo-information products and services to support agricultural monitoring and management tasks, in particular projects and programmes of the [...] | ELEAF B.V. (NL) | Sustainable Development | agriculture, sustainable development | EO4SD – Agriculture and Rural Development project – aims at demonstrating the benefits of EO-based geo-information products and services to support agricultural monitoring and management tasks, in particular projects and programmes of the Mulatilateral Development Banks (MDBs) such as World Bank, Inter-American Development Bank, IFAD and Asian Development Bank which deal with land degradation, soil erosion, food security and irrigation systems management. The main objective of this Agriculture Cluster project is to demonstrate that the effectiveness of the MDB’s technical assistance interventions and financial investments in agriculture sector can be measurably enhanced by using EO-derived information to support large-scale crop area and type estimates (i.e. crop cover mapping and status assessment), irrigation and irrigation systems management (i.e. energy balance, water productivity and water stress), agriculture productivity assessment (i.e. yield estimation, ground water, precipitation monitoring), rural infrastructure investments planning and monitoring (i.e. households and transport networks mapping), Land Degradation Assessment (i.e. land use, rainfall, soil moisture, precipitation, fAPAR, NDVI indicators), and Environmental Impact Assessment (i.e. landscape level classification and change mapping including fragmentation, and agriculture commodities production impact on deforestation). |
| EO4SD – Climate Resilience | The ESA EO4SD Climate Resilience project encapsulates heterogeneous and multi-disciplinary knowledge to provide answer about the real potential of Earth Observation in supporting climate resilience decision making at regional and national scale, [...] | GMV AEROSPACE AND DEFENCE, SA (ES) | Sustainable Development | climate, sustainable development | The ESA EO4SD Climate Resilience project encapsulates heterogeneous and multi-disciplinary knowledge to provide answer about the real potential of Earth Observation in supporting climate resilience decision making at regional and national scale, and in collaboration with key Multilateral Development Banks (or MDBs). The project aims at developing an EO-based climate screening and risk management tools. The project will demonstrate the value of EO solutions with a series of use cases developed in partnership with the stakeholders (e.g. International Financing Institutions (IFIs), national hydromet agencies (NMHSs)) and innovators (e.g. citizen, entrepreneurs) to derive high-level data products supporting the monitoring of and management of climate vulnerabilities. Activities will be implemented to support selected flagship initiatives and projects implemented in Central America and Caribbean, East Africa, Central Asia and South Asia and led by the key actors in climate financing (ie. World Bank, Asian Development Bank, Interamerican Development Bank, etc.), which are interested in robust and up to date climate resilience indicators. |
| EO4SD – DISASTER RISK REDUCTION | The ESA EO4SD Disaster Risk Reduction project aims to promote the adoption of Earth Observation-based products and services mainstreamed into the working processes of IFIs funded projects that seek to prevent or mitigate the adverse impacts of [...] | INDRA SISTEMAS (ES) | Sustainable Development | disaster risk, sustainable development | The ESA EO4SD Disaster Risk Reduction project aims to promote the adoption of Earth Observation-based products and services mainstreamed into the working processes of IFIs funded projects that seek to prevent or mitigate the adverse impacts of natural disasters in developing countries. Earth Observation applied to disasters is evolving quickly and has proven to be effective in all phases of the disaster risk management cycle such as prevention/ preparedness, early warning, post event recovery and reconstruction activities. The project pursues the following objectives: Carrying out demonstrations of the benefit and utility of Earth Observation (EO)-based information in support of international development projects and activities in the thematic domain of Disaster Risk Reduction (prevention, preparedness, recovery and reconstruction phases); Supporting directly programs / projects, monitoring & evaluation methodologies and policy & planning of the IFIs and their respective Client States not only in the sector of disaster management but also in transportation, habitat, energy, water and sanitation; Mainstreaming and transferring EO-based information into operational working processes of the individual countries and development organizations. |
| EO4SD – Eastern Partnership | EO4EP – Earth Observation for Eastern Partnership is an ESA initiative which aims to achieve a step increase in the uptake of satellite-based environmental information in the development programs implemented by the World Bank and the European [...] | Space Research Centre, Polish Academy of Sciences (CBK-PAN) (PL) | Sustainable Development | sustainable development | EO4EP – Earth Observation for Eastern Partnership is an ESA initiative which aims to achieve a step increase in the uptake of satellite-based environmental information in the development programs implemented by the World Bank and the European Investment Bank in the Eastern European Region, in particular in order to support the technical collaboration and knowledge exchange among Eastern Partnership countries. The objective is to enhance the provision of the specialized remote sensing information services, analytic tools and geospatial information systems and to leverage new data sources such as Sentinel satellites to support planning, implementation, and monitoring of development projects as well as to provide remote sensing capacity building in three thematic areas: Agriculture, Land Management, and Water Resources Management. The project also aims to develop a portfolio of demonstration services which involve crop cultivation mapping and monitoring, assessment of water availability for crops, benchmarking against long-term data, delineation of areas currently undergoing water stress, predicting yields, providing information on land use as well as flood monitoring. |
| EO4SD – Marine and Coastal Resources Management | The objective of this contract is to develop and demonstrate a portfolio of EO based information services that can be embedded into a critical mass of investment projects funded by International Development Banks which address marine and coastal [...] | NATURAL ENVIRONMENT RESEARCH COUNCIL (GB) | Sustainable Development | coastal zone, marine environment, sustainable development | The objective of this contract is to develop and demonstrate a portfolio of EO based information services that can be embedded into a critical mass of investment projects funded by International Development Banks which address marine and coastal issues. The main focus will be information services addressing coastal dynamics (bathymetry, coastal erosion, sedimentation), coastal environment status (benthic and coastal habitats, coastal water quality), maritime and coastal surveillance (IUU fisheries control, pollution detection, resource extraction monitoring) and supporting the development of coastal economies (aquaculture, tourism, transport, energy). The priority geographic regions of interest are West Africa, East Africa, the Caribbean, the Northern Indian Ocean and Pacific Island States. |
| EO4SD – Support to States affected by Fragility, Conflict and Violence | The objective of this contract is to develop and demonstrate a set of EO based information services to support the activities of International Development Banks in areas affected by fragility, conflict and violence. This includes activities [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Sustainable Development | security, sustainable development | The objective of this contract is to develop and demonstrate a set of EO based information services to support the activities of International Development Banks in areas affected by fragility, conflict and violence. This includes activities addressing the causes and consequences of fragility, conflict and violence as part of an economic and social development strategy as well as support to more standard development activities which are being executed in the higher risk environment of proximity to fragility, conflict or violence. EO based information services being developed include support to natural resources management (e.g. countering illicit extraction and trafficking of minerals, fish, timber and wildlife or wildlife products), support to strengthening the application of justice and rule of law (e.g. election support, detection of crimes against humanity, onset of violence and internal displacement of persons and detection of illegal activities), support to the planning and implementation of post conflict reconstruction and support to environmental security (characterization of disease reservoirs, pollution/contamination events and the status of critical habitats and ecosystems). |
| EO4SD – Water Resources Management | EO4SD – Earth Observation for Sustainable Development – is a new ESA initiative which aims to achieve a step increase in the uptake of satellite-based environmental information in the IFIs regional and global programs. It will follow a [...] | DHI GRAS A/S (DK) | Sustainable Development | sustainable development, water resources | EO4SD – Earth Observation for Sustainable Development – is a new ESA initiative which aims to achieve a step increase in the uptake of satellite-based environmental information in the IFIs regional and global programs. It will follow a systematic, userdriven approach in order to meet longer-term, strategic geospatial information needs in the individual developing countries, as well as international and regional development organizations. Specifically, for water resource management the EO4SD will seek to demonstrate the benefits and utility of EO services in response to stakeholder requirements for water resources monitoring and management at local to basin scales. |
| EO4SD LAB: A COMMUNITY INITIATIVE FOR DEVELOPMENT AID | The goal of the EO4SD-Lab project is to facilitate and promote increased use of Earth Observation (EO)-derived information by a range of users within the sustainable development community. This will be achieved by the creation and deployment of [...] | CGI IT UK LIMITED (GB) | Sustainable Development | sustainable development | The goal of the EO4SD-Lab project is to facilitate and promote increased use of Earth Observation (EO)-derived information by a range of users within the sustainable development community. This will be achieved by the creation and deployment of an EO- processing and e-collaboration environment dedicated to Development Assistance (or Development Cooperation or Development Aid). This portal will provide users with various capabilities, ranging from searching for existing relevant factsheets and publications, undertaking analysis on various datasets, using data processing services to create new products to building and deploying their own bespoke services. Such capabilities will enable users with a varying level of EO and Geospatial knowledge to find the most relevant information. |
| EO4SD-Urban | The EO4SD-Urban project aims at demonstrating the benefits of satellite Earth Observation-based geoinformation products to support urban planning tasks, in the context of projects and programmes of Mulatilateral Development Banks (MDBs) such as [...] | GAF AG (DE) | Sustainable Development | sustainable development, urban | The EO4SD-Urban project aims at demonstrating the benefits of satellite Earth Observation-based geoinformation products to support urban planning tasks, in the context of projects and programmes of Mulatilateral Development Banks (MDBs) such as the World Bank Group, Asian Development Bank, Inter-American Development Bank, etc., and stakeholders in their Client States, as well as major global development initiatives. Its major goal is to provide convincing demonstrations of the benefit and utility of user-driven EO-based information in the urban framework, based on case studies in approximately 40 cities, thereby enhancing measurably the MDB’s technical assistance interventions and financial investments in the urban sector. To progress towards the longer-term goal of estabishing EO-based information as part of the working practices of MDBs and their Client States, an important element of the project is to provide knowledge transfer via capacity building exercises on how to derive and use EO-based product in various urban development-related scenarios. |
| EO4URBAN, Multi-Temporal Sentinel-1 SAR and Sentinel-2 MSI Data for Global Urban Services (DUE Innovator III Series) | More than half of the people on the planet live in cities and the situatiuon will further worsen with another 2.5 billion people expected to move into cities by 2050. The information decision makers need for their urban planning activities are [...] | KTH ROYAL INSTITUTE OF TECHNOLOGY IN STOCKHOLM (SE) | Applications | applications, urban | More than half of the people on the planet live in cities and the situatiuon will further worsen with another 2.5 billion people expected to move into cities by 2050. The information decision makers need for their urban planning activities are either non-existent, outdated or collected through time-consuming field surveys or visual interpretation of areal images. Timely, reliable and consistent information on urban land cover and its changing patterns from satellite data is of critical importance to support sustainable urban development. Despite the growing importance of urban land mapping, it remains difficult to map globally and systematically urban areas, due to the heterogeneous mix of land cover types in urban environments, and to the cost of commercial airborne and satellite data. With the recent launches of Sentinel-1 and Sentinel-2, high resolution SAR and optical data with global coverage and free and open data policies are now available, which allow an operational and reliable global urban land mapping to become achievable. EO4URBAN developed some novel and innovative approaches for global urban services around Sentinel 1 C-SAR and Sentinel 2 MSI in support to sustainable urban development. The fusion of SAR and optical data has been proven advantageous due to the complementary nature of the data. Both SAR and optical data have their own merits and limitations, thus the fusion of SAR and optical data can overcome the deficiencies associated with single sensor approaches. The projects evaluated the added value of a joint use of Sentinel 1 and Sentinel 2 in urban land cover and urban extent mapping. Pilot products were developed for 10 cities around the world that represents different urban realities. |
| EO4WR – EARTH OBSERVATION FOR WATER RESOURCE EXTRACTION IN INDONESIA | The project is exploiting new AI techniques using EO data to support water extraction. The service provide generated a precise terrain motion map using Sentinel-1 data with InSAR and this was combined with global and local geosptial data such as [...] | Planetek Italia (IT) | Enterprise | permanently open call, Sentinel-1, water resources | The project is exploiting new AI techniques using EO data to support water extraction. The service provide generated a precise terrain motion map using Sentinel-1 data with InSAR and this was combined with global and local geosptial data such as a database concerning water extraction activities including a map of wells in the area of Jakarta. Seismic risk assessment, subsidence and water resources management in indonesia Support to Water and Food Security Planning and Investments in Indonesia |
| EOCONTEXT- Contextualisation of EO data for River Environmental Changes | Over the next decade, numerous transnational enterprises are planning to build over 3,000 hydropower plants (HPP) on rivers flowing throughout South East Europe. Many of these rivers are part of Natura 2000 protected areas and are well-known for [...] | ZRC SAZU – Research Centre of the Slovenian Academy of Sciences and Arts (SI) | Applications | applications, infrastructure, land cover, rivers, water cycle and hydrology | Over the next decade, numerous transnational enterprises are planning to build over 3,000 hydropower plants (HPP) on rivers flowing throughout South East Europe. Many of these rivers are part of Natura 2000 protected areas and are well-known for their rich ecosystems. One of these rivers, Vjosa in Albania, has not been affected by hydropower dams so far, except in its upper catchment that flows through Greece. Vjosa is considered to be among the last ‘free-flowing rivers’, having one of the broadest gravel bars in Europe. The river flows free for 270km, untamed and undammed, through spectacular valleys and canyons. Similarly, the river Mura in its middle and lower course in Slovenia has not been impacted by the construction of hydropower plants so far, but is, in contrast to Vjosa, heavily dammed in its upper catchment in Austria. In total, 31 hydropower stations were built on the Mura river, of which 26 are still operating. The dense hydropower infrastructure network in the upper catchment has caused some significant transformations of the riverine morphology, its biodiversity, and landscapes. The objective of the project is to compare the environmental changes in two different river catchments (Mura river in Slovenia and Vjosa river in Albania) and assess the impact of hydro-electric infrastructures by studying the streamflow alterations (on land cover and gravel deposits) on the river regimes and comparing these changes to the perception of changes from local population. |
| EOCYTES: Evaluation of the effect of Ozone on Crop Yields and the TErrestrial carbon pool using Satellite data | Living Planet Fellowship research project carried out by Jasdeep Singh Anand. Terrestrial ecosystems are a major carbon pool, and so act to mitigate anthropogenic climate change. However, vegetation in these carbon pools are damaged by [...] | UNIVERSITY OF LEICESTER (GB) | Science | atmosphere, biosphere, carbon cycle, carbon science cluster, land, living planet fellowship, science | Living Planet Fellowship research project carried out by Jasdeep Singh Anand. Terrestrial ecosystems are a major carbon pool, and so act to mitigate anthropogenic climate change. However, vegetation in these carbon pools are damaged by tropospheric O3, which is formed from anthropogenic NOx and aerosol emissions. Damaged vegetation cannot sequester as much carbon, so this will lead to a degradation of carbon pools, and a worsening of climate change. In addition, O3 exposure also decreases crop yields, and therefore poses a threat to global food security. Previous investigations into O3 exposure on vegetation have relied on long-term in-situ studies using eddy covariance methods. Such investigations are costly and extremely geographically limited, and do not cover most of the tropics and emerging economies. Additionally, poorly constrained factors such as CO2 fertilisation also increase the uncertainty of derived estimates of O3-related damage. Satellite datasets from ESA and third-party missions provide long-term global monitoring of atmospheric composition and plant productivity, and could be combined with existing models of land-atmosphere processes to better constrain the rate of degradation of the terrestrial carbon pool, and to provide more useful metrics on crop losses stemming from O3 exposure. This project will analyse satellite datasets of O3, and vegetation indices as well as use the JULES land surface model to assess the extent short-term and long-term O3 exposure decreases the terrestrial carbon sink and decreases crop yields, particularly near megacities where emissions of O3 precursors are most concentrated. These results will be validated against existing in-situ datasets, such as the SoyFACE experiments, along with historical crop yield data. |
| EOFIN – BEST PRACTICE FINANCIAL MANAGEMENT SUPPORT | EO-FIN is one of the ESA best practice series of projects with a focus on the financial management sector. The main aim of the EO-FIN project is to understand the Financial Management sector's requirements for geospatial information and what the [...] | GMV NSL LTD (GB) | Enterprise | climate, risk, security | EO-FIN is one of the ESA best practice series of projects with a focus on the financial management sector. The main aim of the EO-FIN project is to understand the Financial Management sector’s requirements for geospatial information and what the current (including near future), capabilities of EO are to support the Financial Management sector’s needs on Geospatial services. EO-FIN seeks to identify the best practices allowing the EO industry to respond to these requirements through high-quality, standardised, EO products and services and, finally, define a roadmap for the implantation of these EO best practices. For the purposes of this activity, the FM sector will be represented by stakeholders operating in the following four FM markets: Investment Management, Risk management, Insurance Management and Green Finances. Investment Management: services including asset allocation, stock allocation, monitoring of existing investments, and portfolio strategy and implementation. Risk Analysis: the process of identifying, assessing, and managing financial, legal, strategic, and security risks to an organisation’s capital, operations, and earnings. Insurance Management: services including the provision of insurance contracts, underwriting, ongoing and post-event asset evaluation, and claims against policies. Green Finance: financial activities that mitigate negative impacts that arise from environmental pollution and climate change, and support the development of a greener future. |
| EOMall | The Objective of this activity is to develop an on-line Marketplace for the EO Service sector. Known as EOMall, the platform will enable the interactive promotion of downstream EO-based products & services focused on the needs of a global [...] | EVERSIS SP. Z O.O. (PL) | Enterprise | enterprise | The Objective of this activity is to develop an on-line Marketplace for the EO Service sector. Known as EOMall, the platform will enable the interactive promotion of downstream EO-based products & services focused on the needs of a global user-base. |
| EOplumes | The detection of trace gas plumes allows us to improve attribution of pollutant emissions and photochemical processing in the global troposphere. Data collected by the ESA TROPOspheric Monitoring Instrument (TROPOMI) has resulted in a growing [...] | UNIVERSITY OF EDINBURGH (GB) | Science | air quality, atmosphere, atmosphere science cluster, atmospheric chemistry, environmental impacts, science | The detection of trace gas plumes allows us to improve attribution of pollutant emissions and photochemical processing in the global troposphere. Data collected by the ESA TROPOspheric Monitoring Instrument (TROPOMI) has resulted in a growing number of case studies that have used ad hoc methods to detect plumes for science applications. Developing a more comprehensive understanding of TROPOMI data will help to identify new research avenues and support the development of new applications. However, this is difficult because of the associated data volumes, a challenge that will only grow with time. We address this challenge by using artificial intelligence methods, underpinned by domain-level expertise, to develop plume reference datasets for TROPOMI. Sulphur dioxide hotspots We will develop our plume identification algorithm to study the entire TROPOMI SO2 record and build an up-to-date database of the time and location of each plume we identify. We anticipate, based on recent work, we will find the location of volcanoes, powerplants, smelting facilities, and shipping routes. These facilities can mostly be evaluated using existing inventories, although we expect that some new coal-fired power plants will be missing from the inventories due to a lag between national emission reports and inventory compilation. We will also use our new SO2 plume reference dataset to examine the spatial and temporal variations in the SO2 columns. Photo-chemical processing Elevated surface ozone levels are detrimental to human health and to the growth of a range of agricultural crops. Understanding the sensitivity of surface ozone to changes in emissions of nitrogen oxides (=NO+NO2) and volatile organic compounds (VOCs) is therefore an important scientific and policy-relevant quantity to understand. We will use collocated plumes of formaldehyde (HCHO), a high-yield product of VOC oxidation, and nitrogen dioxide (NO2) from our TROPOMI plume reference datasets to examine spatial and temporal variations in photo-chemical environments. The resulting HCHO:NO2 ratio plume reference data will help us to study changes in the photo-chemical environment in urban areas across the world. |
| EOSAT 4 SUSTAINABLE AMAZON | EOSAT 4 Sustainable Amazon demonstrates near real time monitoring of forest disturbances in the Colombian Amazon to support the country in reaching its sustainable development goals. | SARVISION BV (NL) | Applications | applications, forestry, permanently open call, sustainable development | EOSAT 4 Sustainable Amazon demonstrates near real time monitoring of forest disturbances in the Colombian Amazon to support the country in reaching its sustainable development goals. |
| EOStat-Poland | The EOStat project is co financed by EOEP5 and a Polish Industry Incentive Scheme Program (PLIIS) and aiming to facilitate the growth of strategic space applications sectors in Poland where new EO-methods methods and services integrated with [...] | Institute of Geodesy and Cartography (IGiK) (PL) | Enterprise | agriculture, enterprise | The EOStat project is co financed by EOEP5 and a Polish Industry Incentive Scheme Program (PLIIS) and aiming to facilitate the growth of strategic space applications sectors in Poland where new EO-methods methods and services integrated with advanced ground segment capabilities can be developed and applied for operational use. EOStat-Agriculture Poland addresses specifically the needs of the Central Statistical Office of Poland (CSO) which is the only official national source of agricultural statistical information transmitted to the European Commission (Eurostat). In this context the objectives of this ESA-financed project is to enhance the quality and affordability of agriculture data collection and to support CSO to adopt a wide-scale use of satellite-derived information in view of the upcoming reform of the EU Common Agricultural Policy (CAP2020). |
| EOvideo product Exploitation Platform (VANTAGE) | Capturing video from Earth Observation (EO) is one of the most exciting innovations to hit the remote sensing world in recent times. High-resolution, full-colour EO video is enabling fundamental and disruptive changes for the Geospatial [...] | Earth-i Ltd (GB) | Digital Platform Services | generic platform service, platforms | Capturing video from Earth Observation (EO) is one of the most exciting innovations to hit the remote sensing world in recent times. High-resolution, full-colour EO video is enabling fundamental and disruptive changes for the Geospatial Intelligence and Earth Observation industries. EO Video provides several advantages over still imagery, for example: it enables faster and more accurate object recognition using AI and machine learning; It enables 3D models to be created to much higher precision than from a single stereo pair; It provides more contextual information to analysts and researchers, by capturing movement; It allows for more accurate change detection including detection of 3D changes over time; It provides the ability to mitigate patchy cloud and haze in a scene to derive a clear image. VANTAGE is a new, online, cloud-based platform for analysis and exploitation of video from space. The VANTAGE platform includes a repository of high-definition videos captured from Earth orbiting satellites – including data from the Earth-i Vivid-X2 satellite that was launched in 2018. Alongside this data is a suite of sophisticated analytical tools, enabling a user to extract value and insight from the videos such as derivation of 3D models, tracking of moving objects in the videos, extraction of movement vectors and building up cloud-free composite images. The VANTAGE platform also connects to complementary external data sources and enables development of commercial, scientific and public sector applications. VANTAGE enables a user to bring their own EO data as well as their own user-defined workflows and processing algorithms to be deployed and used alongside the predefined list of services and functions. VANTAGE is being developed by Earth-i and CGI under a two-year contract with the European Space Agency, which kicked off in March 2020. The project launched the first version of the platform in November 2020 and will deploy incremental releases of functionality every four months focusing on pre-defined use cases such as earthworks monitoring, deforestation and seaport analytics. The existing VANTAGE services include: Vessel Detection – an AI algorithm to detect and count vessels in satellite video. Motion Tracking – an AI algorithm to track velocity and direction of moving objects, such as aircraft and shipping vessels. Cloud-Free Compositing – an AI algorithm to composite multiple video frames segment the clouds and then removes them to create a cloud-free satellite image. Video Stabilisation – an AI algorithm to stabilise video by aligning each video frame. Frame Extraction – an algorithm to break the video down into individual images for 2D image processing. Video Generation – an algorithm to take multiple 2D images and build it back up into a video, as well as transcoding videos into different formats (e.g. H.264, H.265, MPEG and Motion JPEG). 3D Model Creation – The VANTAGE platform computes a 3D model of the satellite scene and outputs it as a Mesh, DSM and Point Cloud. 3D Volumetric Change Detection Reporting – The VANTAGE platform undertakes change detection between two pre-processed 3D models to map cut and fill regions and report on the volumetric changes detected. Additional features and algorithms will be added to the platform in future releases. |
| ESADEMICS | It has become abundantly clear during the COVID-19 pandemic that environmental factors can be important in the emergence, spread, health impact, social political response, and socioeconomic recovery plan from Sars-Cov-2/COVID-19. Having tools [...] | Science [&] Technology Netherlands (NL) | Enterprise | air quality, covid19, health, permanently open call, public health, water quality | It has become abundantly clear during the COVID-19 pandemic that environmental factors can be important in the emergence, spread, health impact, social political response, and socioeconomic recovery plan from Sars-Cov-2/COVID-19. Having tools available to study the impact of the environment for this pandemic and future pandemics is important to increase preparedness and curtail future societal and economic costs. However, despite the fact that many useful data sources are existing, it remains a tremendous challenge for scientists to combine all these data for their research. The various satellite missions of the European Space Agency (ESA) have led to a plethora of data assets. These assets are publicly available and are used in many scientific projects. The relation between well-being and changes in our habitat require data about our living environment. These data can be reliably and effectively collected using earth observation instruments such as satellites. These satellite data are available from data stores that have been developed by ESA or their operational organisations. For many of the data stores a historical archive is available as well. Even though the data from the various missions are reliable and timely stored in these data stores, their usability for research on the relation between our well-being and our living environment is somehow limited. This is caused by a number of factors. First of all data is not easily accessible to epidemiologists, since they lack specific knowledge on data stores, file formatting standards, etc. In addition, epidemiological research often requires derived data rather than the data stored. And finally, the data stores from ESA and other providers have not been designed with the idea that data can be combined; linking atmospheric data to land cover maps is not a simple query. ESADEMICS aims at making a number of air quality, water quality and mismanaged waste data sources available that are relevant for epidemiological use cases. The focus of this project is to combine a set of relevant data sources from (amongst others) ESA and develop methods to link these different data sources related to air quality, water quality, and mismanaged waste on geolocation and time period. These methods hide the complexity from the epidemiologists to deal with different spatial and time scales of the different data sources. The resulting data set can be retrieved and combined with other data sources (population health data) in their statistical environment. |
| Eu-Mon | Sustainable Development Goals (SDGs) are meant to assist countries to manage and monitor progress on the three key interconnected components of sustainable development: economic growth, social inclusion, and environmental sustainability. This [...] | CGI ITALIA S.R.L. (IT) | Applications | coastal processes, coastal zone, sustainable development | Sustainable Development Goals (SDGs) are meant to assist countries to manage and monitor progress on the three key interconnected components of sustainable development: economic growth, social inclusion, and environmental sustainability. This must therefore be integrated into the national policies and processes. EO is potentially a great source of information for mapping and monitoring SDGs either directly, through the usage of existing data and analytics, or by integrating existing local, regional, and global services, such as Copernicus Core services and similar initiatives. Nevertheless, the adoption of EO in mainstream processes for local authorities is still limited, due to a number of challenges, related to a lack of technical expertise, the capability of integrating different data sources, need to create robust yet widely applicable algorithms and methods. All the above challenges can only be addressed by creating a consortium of EO and data integration experts working in close liaison with the beneficiaries of the EO-related products. The goal of the SDG Eutrophication Monitoring (Eu-Mon) project is to create a pre-operational implementation of EO-processing chains tailored for the national monitoring of SDGs. Such innovative EO-based methods will be deployed on existing EO platforms which are used to funnel the information into the national systems and processes on SDGs, also with the aim to showcase the adequacy of EO for SDG monitoring. In particular, this project addresses the SDG 14.1.1a Monitoring Index of Coastal Eutrophication. The project has engaged with the following end-users organisations: Regional Environmental Centre (REC) Albania, which is directly connected with the national statistical office National Bureau of Statistics, Tanzania In addition, the project will benefit from the in-kind contribution of ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), the Italian entity which has large expertise in using EO and other geospatial data for environmental monitoring. The project has a strong user-centric approach, with EAs and experts always involved in all project activities. This will be strengthened by the execution of three Living Labs, which, benefitting modern communication tools and a combination of virtual and in-person meetings, will ensure proper co-creation, co-design, PoC results, analyses, and validation of the project activities. The core development phases of the project will be carried out by means of an Agile approach, where the EAs will act as Product Owners, with the support of the project consortium. |
| Euro Data Cube Facility | The Euro Data Cube Facility (EDC) service is providing a unique service to access to a considerable amount of EO related information from instrument data up to environmental variables, including Copernicus Services. Capitalizing on EO data [...] | SINERGISE LTD. (SI) | Digital Platform Services | platforms | The Euro Data Cube Facility (EDC) service is providing a unique service to access to a considerable amount of EO related information from instrument data up to environmental variables, including Copernicus Services. Capitalizing on EO data offer from the cloud (e.g. DIAS), EDC avoids at maximum data replication. It offers to EO value-adders the possibility to apply their own algorithm and data transformations in a one-stop-shop Information Factory. The EDC marketplace gives also the opportunity to expose value added data and services from Third parties. Thanks to its data and processing capabilities offer in the cloud, EDC establishes a “bridge from Space to Applications”. The project also contributes to the interoperability activities in the related domain to maximize the service capabilities and foster federation of similar initiatives worldwide. |
| European Ecostress Hub | The European Ecostress Hub is focusing on the development and implementation of the European Ecostress Hub (EEH) in support of the Copernicus High Priority Candidate Land Surface Temperature Monitoring mission (LSTM). ECOSTRESS data acquired [...] | LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY (LU) | Applications | applications, land surface, platforms | The European Ecostress Hub is focusing on the development and implementation of the European Ecostress Hub (EEH) in support of the Copernicus High Priority Candidate Land Surface Temperature Monitoring mission (LSTM). ECOSTRESS data acquired over Europe and Africa together with user interfaces and application programming interfaces, e.g. scene and area selection, selection of different retrieval methods, different parametrisation and auxiliary information, etc.) shall be made available on a suitable cloud environment. In addition, the hub shall provide a dedicated interface for ingesting campaign data (e.g HyTES campaign data). The study also comprises a detailed analysis of the retrieval performances under consideration of different scene settings (different cover types, different stages in the growing cycle, different climate zones (tropical, dry, mild mid-latitude, cold mid-latitude) over a full growing cycle. |
| EW-EXPLORE: SENTINEL-1 EW-MODE ARCHIVE EXPLOITATION FOR POLAR RESEARCH | EW-Explore is a pilot project to investigate interferometric (InSAR) applications of Sentinel-1 (S1) Extra Wide mode (EW) beyond the ocean- and sea ice applications where this mode was designed for. | NORCE Norwegian Research Centre AS (NO) | Science | applications, permanently open call, polar flagship, Sentinel-1 | EW-Explore is a pilot project to investigate interferometric (InSAR) applications of Sentinel-1 (S1) Extra Wide mode (EW) beyond the ocean- and sea ice applications where this mode was designed for. |
| Examining GReenland’s Ice Marginal Lakes under a changing climate (GRIML) | Living Planet Fellowship research project carried out by Penelope How. Sea level is predicted to rise drastically by 2100, with significant contribution from the melting of the Greenland Ice Sheet. In these predictions, melt runoff is assumed [...] | GEOLOGICAL SURVEY OF DENMARK AND GREENLAND (DK) | Science | climate, cryosphere, Glaciers and Ice Sheets, lakes, living planet fellowship, optical, SAR, sea surface topography | Living Planet Fellowship research project carried out by Penelope How. Sea level is predicted to rise drastically by 2100, with significant contribution from the melting of the Greenland Ice Sheet. In these predictions, melt runoff is assumed to contribute directly to sea level change, with little consideration for meltwater storage at the terrestrial margin of the ice sheet. In 2017, 3347 ice marginal lakes were identified in Greenland along the ice margin. Globally, these ice marginal lakes hold up to 0.43 mm of sea level equivalent, which could have a marked impact on future predictions. Therefore, they need to be monitored to understand how changes in ice marginal lake water storage affect melt contribution, and how their dynamics evolve under a changing climate. Currently, there are large challenges in using remote sensing techniques to classify and monitor ice marginal lakes over large regions. Reliance on a single sensor/product (e.g. SAR imagery, optical imagery, DEM products) or detection method (e.g. backscatter classification, spectral indices classification, sink detection) has proven to reduce the accuracy of lake classification, leading to underestimations and false trends. This emphasises the importance of using compound approaches, which is now achievable with the ever-growing use of online cloud processing. GrIML proposes to examine ice marginal lake changes across Greenland using a multi-sensor and multi-method remote sensing approach to better address their influence on sea level contribution forecasting. Firstly, Greenland-wide inventories of ice marginal lakes will be generated for selected years during the satellite era, building upon established classification methods in a unified cloud processing workflow. Secondly, detailed time-series analysis will be conducted on chosen ice marginal lakes to assess changes in their flooding dynamics; focusing on lakes with societal and scientific importance. The findings from this work will be validated against in-situ observations – namely discharge peaks from downstream outlets, surface turbidity measurements, and terrestrial time-lapse images – to evaluate whether the remote sensing workflow adequately captures ice marginal lake dynamics. |
| EXPAND DEMAND – OIL & GAS AND DISASTER RISK FINANCING & TRANSFER | In recent years the need for real-time incident satellite imagery has grown within the oil and gas industry. Following the Gulf of Mexico (Deep water Horizon) oil spill, it became clear that access to real-time satellite data, tasked within [...] | CGI IT UK LIMITED (GB) | Enterprise | natural hazards and disaster risk, platforms | In recent years the need for real-time incident satellite imagery has grown within the oil and gas industry. Following the Gulf of Mexico (Deep water Horizon) oil spill, it became clear that access to real-time satellite data, tasked within hours of an incident and used to inform critical decision-making, could have far-reaching impacts for oil & gas operators in their response to oil spill incidents. However, effective use of satellite imagery to help drive response decisions faces a unique challenge in the time it takes from collecting the first image of an area of interest, to a revisit pass of the same area of interest (16 days in the case of Landsat). This is exacerbated in locations that are closer to the equator than to the poles. The solution is therefore more access to satellites, resulting in non-reliance on a single provider to meet standard needs. This demand for better access to mission-critical Earth Observation (EO) data has led to the ‘Expand Demand Oil and Gas’ project, created and funded by the European Space Agency (ESA). This project has been running within ESA since 2018, and has two key high-level requirements: To meet a specific operational requirement of the oil and gas industry. To establish generic EO capabilities within the oil and gas industry and showcase the capabilities of the Sentinel mission and the European EO service industry. The benefit of this project to its end-users would be a service delivering relevant near-real-time EO data. This would be provided by a dedicated portal, where information relating to a specific spill incident is gathered and presented in a clear and systematic way. The information provided would cover: A timeline of available products from a range of providers. Predictions of future availability of products. Actual products wherever possible Derived services such as oil spill extent mapping. To meet this challenge, the Oil and Gas Industry Earth Observation Response Portal (OGEO – ReP) has been developed. This platform will assist oil spill responses by gathering, processing and displaying a wide range of relevant EO data, including: Satellite data products from a wide range of sources (free and commercial). Predicted acquisitions relevant to the incident. Derived products, e.g. Oil spill extent mapping, processed as a hosted service. Contextual background information, such as asset locations. The scalability of the platform allows it to process large amounts of data in a spill event, allowing for the inclusion of swath prediction (to identify potential acquisitions of interest),the mapping of a spill event, and running of oil spill drift models to forecast the behaviour of the spill. This is all presented via an intuitive graphical user interface (G |
| eXperimental jOint inveRsioN | The Earth crust represents less than 1% of the volume of our planet but is exceptionally important as it preserves the signs of the geological events that shaped the Earth. This thin layer is the place where the natural resources we need can be [...] | GEOMATICS RESEARCH AND DEVELOPMENT (IT) | Science | gravity and gravitational fields, ionosphere and magnetosphere, Mediterranean, permanently open call, solid earth | The Earth crust represents less than 1% of the volume of our planet but is exceptionally important as it preserves the signs of the geological events that shaped the Earth. This thin layer is the place where the natural resources we need can be accessed (e.g. minerals, critical raw materials, geothermal energy, fresh water, hydrocarbons). For these reasons, a thorough understanding of its structure is crucial for both scientific and industrial future activities. In recent years, thanks to the increasing availability of seismic/seismological data and to satellite missions, the Earth crust has been thoroughly investigated and modelled at global and continental scales. However, despite this progress, the crust remains poorly understood in many regions as global models are often too coarse to provide detailed information about the regional and local dynamics. Potential field methods, which exploit gravity and magnetic data, are a powerful tool to recover information on the Earth’s crust structure. A wide variety of gravity and magnetic data in fact have been nowadays collected at near surface altitudes in most regions of the world. These measurements, if properly combined with global satellite data can be used to refine at regional/local scale the modelling of crustal structures, depicting the boundaries between geological units and stratification of the crust. To fully exploit these satellite-derived and terrestrial data ad-hoc physics integrated approaches, to reconcile all the measurements, are required. A promising solution to this issue is represented by the joint processing of both gravity and magnetic fields observations, possibly incorporating the available geological knowledge and constrains coming from seismic acquisitions. In the XORN project an innovative, fully integrated approach will be developed to perform a complete 3D joint inversion of gravity and magnetic fields data, constrained by seismic and geological a-priori information. The developed algorithm will be used within the project to recover a 3D regional model of the Earth crust in the Mediterranean Area in terms of density and magnetic susceptibility distribution and in terms of depths of the main geological horizons. |
| Explainable AI: application to trustworthy super-resolution (OpenSR) | The project aims to bring robust, accountable, and scalable multi-spectral super-resolution techniques to the Earth Observation (EO) community for the ubiquitous L2 and L3 pre-processing of the Sentinel-2 (S2) revisits archive. Super-resolution [...] | UNIVERSITY OF OXFORD (GB) | AI4EO | AI4EO, AI4Science | The project aims to bring robust, accountable, and scalable multi-spectral super-resolution techniques to the Earth Observation (EO) community for the ubiquitous L2 and L3 pre-processing of the Sentinel-2 (S2) revisits archive. Super-resolution (SR) is a nascent technology and the roadmap to maturity will require insights from many disciplines. Super-resolution is not just about image generation, but also degradation: how much is lost in pixelation. To shift the public perception on the safety of SR-S2 products, the project will provide uncertainty and quality metrics along with the SR products; establish and disseminate best practices through new methods and tools that will be open to everyone. The project will push the boundaries of excellence science and technological development of SR in remote sensing, by creating a set of tools, platform, and guidelines: Tools of state-of-the-art SR, Explainable AI (xAI), saliency and information metrics. An open WebGIS platform that goes beyond standard solutions by working directly on Analysis Ready Data stored in a datacube. The platform will bring SR S2 data at the fingertips of users, allow for interactive data exploration, analysis and combination of SR S2 and other data, and even on-the-fly execution of xAI models on S2 data. It will provide access to the data from a number of use cases illustrating different real-world problems and showcasing how applications benefit from the combined action of SR and xAI, and their limits. A set of guidelines and best practices that summarize an accountable and reproducible SR pipeline for successful applications. |
| extrAIM | extrAIM (AI-enhanced uncertainty quantification of satellite-derived hydroclimatic extremes) is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, [...] | National Technical University of Athens (GR) | AI4EO | AI4EO, AI4Science, Ecosystems, Mediterranean, platforms, science | extrAIM (AI-enhanced uncertainty quantification of satellite-derived hydroclimatic extremes) is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, and contributes to the ESA Extremes and Natural Disasters Science Cluster. The AI4SCIENCE ITT had 2 main objectives: Advancing Earth System Science: advancing our capacity to combine EO and AI to address a major scientific challenge: The observation, understanding and characterisation of multi-hazards, compound and cascade events and its impacts on society and ecosystems. Advancing Artificial Intelligence for EO: unlocking the full potential of Artificial Intelligence for Earth System Science with focus on two main AI challenges: physics-driven Artificial Intelligence and explainable AI. extrAIM will develop a first-of-its-kind, satellite-based, low-latency, uncertainty-aware precipitation dataset for the Mediterranean region, adjusted to account for the extremes’ probabilistic behavior. extrAIM will combine statistical learning and Bayesian modelling methods (for uncertainty quantification) with an AI (Artificial Intelligence)-enhanced dataset integration approach, suitable for combining multiple precipitation products (e.g., satellite-data, estimates based on soil moisture), with an eye on model’s explainability. Finally, and with improving understanding and awareness in mind, extrAIM will develop a user-friendly data-management and visualization platform able to provide easy access to the UA Mediterranean dataset, as well as communicate risks arising from individual and compound extreme events. In more detail, extrAIM project’s specific objectives are: 1. The development of an AI-enhanced, yet explainable and operational approach capable of optimally combining multiple SPPs into a single, and improved integrated SPP. 2. The development of a general probabilistic framework for the uncertainty modelling and quantification of the quantitative precipitation estimates obtained by SPPs (with a focus on extremes). 3. The creation of a first-of-its-kind UA satellite-based precipitation dataset for the Mediterranean region. 4. The development of a user-friendly data analysis and visualization platform, which will enable easy data retrieval and visualization, aiming to increase understanding and awareness against hydroclimatic risks arising from individual and compound extreme events. The project results and publications will be made available at the project website: https://extraim.eu/en/ |
| F-BURST – mapping of Field -aligned currents in the ionosphere and BURSTYbulk flows in the magnetotail. | FBURST aims at better understanding the ionosphere-magnetosphere coupling based on multi-spacecraft observations that can monitor the status of the high latitude ionospheric field aligned current system (FAC) and the conditions in the [...] | SWEDISH INSTITUTE OF SPACE PHYSICS (SE) | Science | ionosphere and magnetosphere, solid earth, swarm | FBURST aims at better understanding the ionosphere-magnetosphere coupling based on multi-spacecraft observations that can monitor the status of the high latitude ionospheric field aligned current system (FAC) and the conditions in the geomagnetic tail. In particular, this project focusses on the fast plasma jets detected at more than 60000 km from the Earth in the geomagnetic tail, called Bursty Bulk Flows (or BBFs). These BBFs are easily recognisable in in-situ data from ESA’s Cluster mission and NASAs MMS (Magnetospheric Multi-Scale) since they are characterised by velocities exceeding 300 km/s and highly structured magnetic field perturbations, consisting typically of a dipolar variation of the magnetic field component perpendicular to the current sheet (Bz). It has been established that BBFs are responsible for most of the plasma transport from the magnetotail to the inner magnetosphere, playing a pivotal role in the global magnetospheric energy budget. Therefore, advancing our understanding of how BBFs couple to the ionosphere is of critical importance to obtaining a complete understanding of ionosphere-magnetosphere coupling. The FACs, which are the oldest known manifestation ionosphere-magnetosphere coupling, connect the F2 ionospheric layer (150 – 200 km altitude) with the outer magnetosphere, including also the geomagnetic tail. The main distribution of FACs consists of two concentric rings in the high-latitude ionosphere in proximity of the auroral oval, which is the region where visible polar aurorae are observed. FAC intensity and location are directly connected with the level of geomagnetic activity since they strongly intensified and expands to lower latitudes during geomagnetic substorms. The current knowledge of BBFs-ionosphere link comes from a number of single-case studies reported in scientific literature, with simultaneous observations of BBFs and FAC in the nightside Region1. FBURST project envisages instead a statistical approach combining together the long-term Swarm observations to monitor FAC in synergy with long-term data from Cluster and MMS to detect BBFs in the geomagnetic tail. This approach, which is currently missing in literature, would allow to: 1- establish a measurable statistical link between BBFs and perturbations in FACs; 2- identify the physical mechanism that connects the BBFs with planarity and spatial scale of FAC filaments. In order to link Swarm and magnetospheric observations and therefore map the BBFs into the ionosphere, FBURST would rely on Tsyganenko field-line model. The project also envisages a statistical connection between MMS/Cluster magnetotail observations and Swarm ionospheric observations, not relying on one-to-one MMS-Cluster-Swarm mapping, that will maximise the use of both statistical datasets. This will provide a deeper insight into the behaviour of FACs in terms of the variations in current density, the distortion of their structure, and also quantification of the spatial scales. This will simultaneously contribute to a better characterisation of FACs but also shed significant light on a key magnetosphere-Ionosphere coupling mechanism (BBFs), which is not completely understood. |
| FAST-EO (Fostering Advancements in Foundation Models via Unsupervised and Self-Supervised Learning for Downstream Tasks in Earth Observation) | Fostering Advancements in Foundation Models via Unsupervised and Self-Supervised Learning for Downstream Tasks in Earth ObservationThe objectives will be achieved through the validation of the proposed FMs (Multimodal Foundation Models) on [...] | DLR – GERMAN AEROSPACE CENTER (DE) | AI4EO | AI4EO, Biomass, climate, land, natural hazards and disaster risk, Sentinel-1, Sentinel-2 | Fostering Advancements in Foundation Models via Unsupervised and Self-Supervised Learning for Downstream Tasks in Earth ObservationThe objectives will be achieved through the validation of the proposed FMs (Multimodal Foundation Models) on suitable downstream applications that address global societal challenges. More specifically, the validation of the proposed FM architectures will be conducted on six main use cases (UCs), which are as follows: UC1: Weather & Climate Disaster Analysis UC2: Detection of Methane Leaks UC3: Observation of Changes in Forest Above-Ground Biomass UC4: Estimation of Soil Properties UC5: Detection of Semantic Land Cover Changes UC6: Monitoring Expansion of Mining Fields into Farmlands The resulting FMs tailored to Earth observation (EO), as Geospatial Foundation Models (Geo-FMs), accompanying downstream applications for UCs, and the corresponding dataset and code repositories will be made freely available to the AI4EO community. This FAST-EO project primarily addresses the needs of the public and private sectors involved in Earth Observation (EO) and environmental analysis. Customers in these sectors are seeking advanced, AI-powered toolkits that can be easily adapted to different use cases, requiring minimal expert knowledge or effort for accurate monitoring and analysis of various environmental and geographical phenomena. In this regard, the project is not only in line with the customer needs but also aligns with the high-level business objectives of each partner The FAST-EO project is designed to cater to a global customer base, with a particular focus on countries and regions facing significant environmental challenges and those with strong commitments to environmental sustainability. It targets both developed nations with advanced Earth Observation capabilities and developing countries seeking to enhance their environmental monitoring infrastructure. The project’s advanced, AI-powered toolkits are also ideally suited for international organizations and NGOs dedicated to climate change mitigation, environmental protection, and disaster management. This wide-ranging appeal is due to the project’s potential capacity to provide accurate, efficient, and adaptable solutions for monitoring and analyzing diverse environmental and geographical phenomena, making it a valuable asset for countries and entities at various stages of EO and environmental analysis development The objective of the FAUST-EO project is to enhance the accessibility and democratization of FMs within the EO community. This includes: Tailoring to Data Domains: Adapting FMs specifically for synthetic aperture radar (SAR), multispectral, and hyperspectral sensor characteristics, and considering the multi-temporal nature of EO data, with a focus on prioritizing existing European missions such as Sentinels, while also aligning with upcoming initiatives such as the Copernicus Hyperspectral Imaging Mission of ESA (CHIME). Enhanced Multimodality: Incorporating text-based, semantic masking-based or geometrical prompts to enhance multimodality beyond just sensor data. Overcoming Computational Barriers: Addressing computational limitations to facilitate the optimal reconfiguration and refinement of FMs for various EO tasks, thereby encouraging their widespread adoption in practical applications. Affordable Fine-Tuning: Design and train FM’s on world-wide samples, with the objective to reduce the number of labelled data for novel down-stream tasks, which can be deployed at a global scale. Operational and Accessible Implementation: Devising strategies for effectively scaling up and moving towards the operationalization of these FMs. Additionally, ensuring their accessibility for non-technical audiences, facilitated by both our project consortium members (IBM, FZJ, DLR, and KP Labs) and our project endorsers/stakeholders. Since each use case will be examined under various modality, sensor, and temporality conditions, it can be said that some UCs have multiple sub-UCs to examine the provided Geo-FMs from different perspectives The FAST-EO project will release the model weights, configuration for reproducibility, and datasets as open-source, following a free-of-charge and permissive licensing (Apache-2). These resources will be accessible through the SpatioTemporal Asset Catalog (STAC) or via the OpenEO API for efficient geospatial data retrieval in cloud-based systems. Additionally, the source code will be hosted on GitHub, and pretrained Geo-FMs will be available via HuggingFace, ensuring complete transparency, accessibility, and a “plug-and-play” mindset for easy investigation, similar to what we achieved with the Prithvi Model.Within the FAUST-EO project, we will enhance this software stack to provide a more versatile solution that encompasses both language and vision modalities, while also accommodating additional temporal and sensor variations. This expanded software stack will be made available under a free-of-charge and permissive licensing |
| Federated Identity Management Pathfinders | Several different activities to explore the notion of having Federated Identities for EO Exploitation, allowing a user to access services using its home organisation account, e.g. university account being used to access a DLR service or an ATOS [...] | CGI IT UK LIMITED (GB) | Digital Platform Services | platforms | Several different activities to explore the notion of having Federated Identities for EO Exploitation, allowing a user to access services using its home organisation account, e.g. university account being used to access a DLR service or an ATOS Commercial service. |
| FEOSID – Further Expansion of EO Uptake Supporting International Development Bank Projects / Support for IADB | The objective of this activity is to demonstrate the improved capabilities of EO data for four specific activities of the Inter-American Development Bank (IADB). These are 1) Effects of land titling in Peru; 2) Sustainable agriculture [...] | TERRASIGNA (RO) | Sustainable Development | agriculture, land cover, sustainable development, urban, water resources | The objective of this activity is to demonstrate the improved capabilities of EO data for four specific activities of the Inter-American Development Bank (IADB). These are 1) Effects of land titling in Peru; 2) Sustainable agriculture development in Guyana; 3) Monitoring of the water supply and irrigation programs in Bolivia and 4) Geospatial analysis as a tool for urban resilience in Vitória, Brazil. The project will have particular focus on the enhancements made possible by Copernicus data, an aspect that has not been addressed in the previous demonstration projects the team carried out for IADB (EOSID and EODAT projects), and which was specifically highlighted in the feedback received at the completion of those projects. |
| FFSAR – Coastal Fully Focused SAR Altimetry and Innovative River Level Gauges for Coastal Monitoring | Fully Focused (FF) SAR Coastal [FFSAR-Coastal] is a project funded by ESA to apply the Fully Focused SAR altimetry processor on Sentinel-3 data and evaluate its potential to make a significant new contribution to coastal and estuarine monitoring [...] | SATELLITE OCEANOGRAPHIC CONSULTANTS LTD. (GB) | Science | altimeter, coastal zone, ocean science cluster, oceans, rivers, science, Sentinel-3, Sentinel-6, surface water | Fully Focused (FF) SAR Coastal [FFSAR-Coastal] is a project funded by ESA to apply the Fully Focused SAR altimetry processor on Sentinel-3 data and evaluate its potential to make a significant new contribution to coastal and estuarine monitoring systems, when coupled with innovative water level gauges for validation. Two different environments have been considered: The Severn Estuary and river: A highly dynamic mixed tidal estuary environment, the confluence between a river and its estuary experiencing large tidal range and strong tidal currents The lower Rhône Delta and Camargue: A low lying, flat river delta and wetland environment, susceptible to inundation and water level rise. Innovative in-situ water level gauges were used to validate the satellite data. Time series were provided by autonomous Vortex.io gauges (“microstations”) placed at fixed locations, gauges mounted on drones were used to provide water level profiles between the fixed locations and satellite tracks. FFSAR-Coastal investigated the potential applicability and benefits offered by FF SAR altimeter data in these two different environments. Analysis focused on the benefits offered by the very high along-track resolution in water level and backscatter that can be provided through Fully Focused SAR processing. User agencies and groups from the two regions were consulted to identify gaps and priorities for monitoring requirements. The Fully Focused SAR altimeter data, Vortex.io microstation data, and drone campaign data, are all available through a special page on the UK Coastal Monitoring Website. Further information and all project reports are available through the project website. |
| Flexible ONBoard Data Analysis | The amount of data coming from imaging sensors increases steadily and a modern imaging sensor creates frames of several megapixels at a high frame acquisition rate. These imaging sensors with their large data output are mounted on spaceborne [...] | Science [&] Technology Norway (NO) | Enterprise | permanently open call, platforms | The amount of data coming from imaging sensors increases steadily and a modern imaging sensor creates frames of several megapixels at a high frame acquisition rate. These imaging sensors with their large data output are mounted on spaceborne platforms, but the downlink capability of these spaceborne platforms, especially for small platforms, has not been increasing at the same rate as the data generation of the imaging sensors. This has resulted in a ‘big data problem’ on board these spaceborne platforms. An industry trend towards smaller satellites – with smaller antennas, less power and worse pointing accuracy- leads to an expectation that the downlink capability will remain well below the data generation capability for such imaging satellites. In order to use more acquisitions and have a high ‘usability’ of the satellite, the on-board processing of payload data is a solution. In this project, S&T will determine and test the technology platform that is best suited for onboard intelligent processing of imaging payload data. This will include testing techniques such as development of low volume data products instead of raw image files for downlink, verifying using concrete algorithms and implementation choices how performant such processing can be, exploring the implications of moving certain parts of the processing functionality to FPGA and conducting tests using HyperSpectral imagery on a cubesat. |
| FLOCKEO: A Multi-Scale System of Mappable Indicators to Describe Tourism and Environment Integration at Regional, Local and Business Level | This activity assesses environmental pressures in the tourism sector, by extracting key information from EO data to quantify two major elements: the pressure on water resources and the pressure due to population. The information will be [...] | Murmuration (FR) | Enterprise | This activity assesses environmental pressures in the tourism sector, by extracting key information from EO data to quantify two major elements: the pressure on water resources and the pressure due to population. The information will be integrated with tourism sector indicators and made easily accessible to various stakeholders. Two case studies are defined: the Mediterranean region on the regional scale and Malta on the focussed scale. These regions are highly representative of tourism impact issues issues such as the hydrological balance and water stress, conservation of areas with high ecological/agricultural potential, and anthropogenic pressure. Based on the requirements, a thorough investigation and benchmarking of existing global EO and non-EO data was carried out, with special focus on tourism statistics and urban sprawl. High-priority such datasets have been post-processed and aggregated in a dashboard-style web mapping interface. For the regional scale, a set of thematic indicators was created to diagnose the state of the environment regarding tourism challenges. These were then normalised and combined into a synthetic index called “ecotourism score”. The indicators (partly based on EO) relate to overall water risk, protection of the ecosystems, urbanisation level, air quality and hotel density. For the local (Maltese) scale, additional indicators are made available on imperviousness, green infrastructure and drought anomalies. The project also formulates a unique indicator, TSDI (Tourism Sustainable Development Indicator) that aggregates the ensemble of data extracted from EO and non-EO sources. The goal for TSDI is to increase the readability of the project output to non-expert users and ultimately become the standard to measure the “compatibility of tourism and environment” at any given location. The indicator is inspired by the World Bank’s Human Development Index (HDI) and the Sustainable Development economic indicator (University of London). For the further validation of TSDI, the team is in touch with expert economists from the Toulouse School of Economics. The project website tourism-SDI.org is now online showing a first version of TSDI, which is based on the urbanisation and water stress datasets. | |
| FluViSat | FluViSat is a proof-of-concept study that demonstrates the potential of satellite-collected video imagery to provide accurate and timely quantification of water movements and river flows for the benefit of water management globally. The [...] | UK Centre for Ecology & Hydrology (GB) | AI4EO | AI4EO | FluViSat is a proof-of-concept study that demonstrates the potential of satellite-collected video imagery to provide accurate and timely quantification of water movements and river flows for the benefit of water management globally. The study is being led by the UK Centre for Ecology and Hydrology, in partnership with the Luxembourg-based company, RSS-Hydro, and the Queensland Government, Australia. According to the OECD, floods affect 250 million people and cause 40 billion USD in losses on an annual basis. In addition, the demand for water for people, industry and agriculture is continually growing, placing severe stress on water availability. Freshwater management requires quantitative observations of how much water is flowing through and is being stored within river catchments, and yet across much of the world, water monitoring capabilities fall short of requirements. Previous efforts to determine river discharge from Earth Observation (EO) data have largely been based on the determination of water surface height and extent alone, and lacked the critical parameter of flow speed. Two recent advances are leveraged by the FluViSat project to bring a step change to satellite based river flow observation capabilities. The first is the availability of large satellite networks, such as the SkySat constellation operated by Planet Labs that combine very high-resolution imagery with frequent revisit times. The second is the development of digital video-based ‘surface velocimetry’ methods for streamflow determination. Surface-velocimetry techniques work by tracking the movement of visible features on the water’s surface through the frame of digital video files, in order to quantify the movement of flowing water. By combining these surface-velocimetry techniques with very high resolution video from the SkySat satellites, the FluViSat project has demonstrated that the speed of flow of water on the Earth’s surface can be accurately determined for a range of river sizes, types and locations. This in turn greatly improves the accuracy of remote observations of river discharge and flood peaks. By comparing surface velocities and river discharges from data collected simultaneously from satellite video, low altitude drone video and boat-mounted Acoustic Doppler Current Profilers (ADCP) during high flow events in rivers and tidal locations in the UK, Austria, Australia and Japan, the international project team has demonstrated: The potential of satellite-based surface velocimetry methods in hydrometry, and The potential of innovative new EO techniques for water resource and flood risk management globally Above: The FluViSat validation concept. Satellite video results compared to aerial drone and ADCP derived results (Credit: Nick Everard, UKCEH) The primary customers for this innovation are water resource managers, environmental regulators, and those involved risk and disaster mitigation and management. However, the successful proof of concept can also be beneficial to the re-insurance community, hydro-meteorological systems modellers, as well the EO data service providers. The project can greatly improve global hydrological understanding by enabling flow velocity and discharge data collection from previously ungauged locations, and locations that may be hard to reach. The new method also has the potential to significantly improve the observation of the hugely damaging and disruptive overland flows that accompany many major flood events. The method can benefit and complement existing risk reduction and emergency management systems, improving preparedness and reducing flood impacts. Finally, the cost effectiveness and safety of river flow measurements can be improved significantly compared to mobilising monitoring teams to visit remote locations. Above: Water velocities derived from satellite video. River Indus, Pakistan, September 2022 (Background image courtesy of Planet Labs PBC). Water flow velocity and discharge estimates are also essential to the management of diffuse pollutant fluxes, general water quality monitoring, and water-use for irrigation and recreation, as well as in the modelling and prediction of river morpho-dynamics. As such, the method derived from this project can benefit environmental regulators and water quality management.Through the success of the feasibility study, this project provides vital insights into the needs and values of possible future Sentinel video missions, but more importantly, it can demonstrate the potential value of satellite video imagery for scientific, societal, and commercial activities. *** Following the successful demonstration of the FluViSat satellite velocimetry innovation, an extension was granted to expand the proof-of-concept to explore the validity of using high framerate still imagery from space to estimate surface flow rates. The team is also leveraging the existing ESA Earthnet project PP0087756 titled “Measuring global streamflow and drought impacts with Planet SkySat ultra-high resolution satellite imagery” to explore the potential of still frame imagery from Planet Labs, who will also be providing video imagery to help validate results from the still frame images. The extension period is being used to refine the FluViSat video method, in particular the pre-processing of imagery (both video and still frame) to expand the range of locations and conditions in which the methods can be used, and to increase the accuracy of velocimetry results. Finally, the project is trying to develop a framework to enable responsive satellite-based observations when extreme hydrometeorological events occur. |
| Food Security Thematic Exploitation Platform | The project successfully developed a Thematic Exploitation Platform (TEP) dedicated to Food Security in order to support sustainable agriculture, aquaculture and fisheries by providing access to data, processing tools and computing resources in [...] | VISTA GEOWISSENSCHAFTLICHE FERNERKUNDUNG GMBH (DE) | Digital Platform Services | platforms | The project successfully developed a Thematic Exploitation Platform (TEP) dedicated to Food Security in order to support sustainable agriculture, aquaculture and fisheries by providing access to data, processing tools and computing resources in a cloud environment. It facilitates collaborative research and benchmarking of methods, development of innovative Apps and services, as well as uptake of EO data in processes of end-users in the above-mentioned sectors. |
| ForEarth | The objective of the ForEarth project is to provide a mobile-oriented environmental alert service dedicated to public institutions, scientists and citizens to keep a close watch on their surrounding environment based on freely-available [...] | GEOMATYS (FR) | Sustainable Development | permanently open call, sustainable development | The objective of the ForEarth project is to provide a mobile-oriented environmental alert service dedicated to public institutions, scientists and citizens to keep a close watch on their surrounding environment based on freely-available satellite Earth Observation data. A microservices infrastructure, customised for hosting EO data will be developed and deployed. The infrastructure will be accessed by an EO-specific social networking smartphone app, SnapPlanet, which empowers users of any skill level to trigger web processing of selected EO products and view or download the results. The service will address questions about local environmental variables, through simple and robust remote sensing techniques: change detection over forest, surface water in reservoir dams, irrigated surface area detection. The targeted audience are non-experts: local businesses or simply curious citizens, NGOs, consulting or insurance companies that would not be capable to get this information from elsewhere and in a near real time. More advanced users could use the enquiries collected from users as a feedback to learn what environmental issues are common in the place where the users are querying the app. |
| Forecasting Water Quality from Space (FC-WQ) | Despite their global coverage and public availability, measurements of water quality parameters retrieved by remote sensing have not been used for local short-term forecasting of water quality yet. In fact, forecasting based on remote sensing [...] | BROCKMANN CONSULT GMBH (DE) | Applications | coastal zone, oceans, water quality | Despite their global coverage and public availability, measurements of water quality parameters retrieved by remote sensing have not been used for local short-term forecasting of water quality yet. In fact, forecasting based on remote sensing water quality products with on-ground resolution from, say, 30 m (Sentinel-2 MSI, Landsat-8/9 OLI) to 300 m (Sentinel-3A/B OLCI) or 500 m (GOCI) constitutes a potential breakthrough since the availability of in situ measurements of water quality is often limited. For a given location, availability of remote sensing water quality products is mainly determined by satellite revisit frequencies (3-5 days for Sentinel-2A/B, 1-3 days for Sentinel-3A/B, and 30 minutes for GOCI) and constrained by cloud coverage. The Forecasting Water Quality from Space (FC-WQ) project aims to develop and validate a method for local short-term forecasting of water quality based on EO data in coastal and inland waters. This method will be based on time series of remotely sensed water quality parameters, combined with past, present, and forecast data of physical parameters (i.e., meteorological, hydrological, and specific environmental parameters). The proposed method exploits the capability of Machine Learning (ML) to learn and model the complex relationships in aquatic ecosystems. Specific objectives of this undertaking comprise: Forecasting of turbidity and chlorophyll-a concentration and associated uncertainties up to five days ahead of time Providing the probability of occurrence of a harmful algal bloom (HAB) within seven days ahead of time Development of the methodology based on selected coastal and inland water test sites while aiming at applicability to coastal and inland waters in general Validating the methodology for selected coastal and inland water test sites for certain hindcast periods not considered and during model training Demonstrating the forecasting capability at selected coastal and inland water sites for a certain forecast period Testing transferability of the methodology to other sites Developing a roadmap for further scientific studies as well as product and service applications |
| Forest Carbon Monitoring | Information on forest biomass and carbon is in high demand by forestry stakeholders. This project will develop remote sensing based user-centric approaches for forest carbon monitoring, helping to shift economies towards carbon neutral [...] | VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD (FI) | Applications | applications, carbon cycle, forestry, generic platform service, platforms | Information on forest biomass and carbon is in high demand by forestry stakeholders. This project will develop remote sensing based user-centric approaches for forest carbon monitoring, helping to shift economies towards carbon neutral futures.We aim to develop and implement a prototype of a remote sensing based monitoring and accounting platform with consistent results on carbon stock. The platform aims to act as a prototype of an operational system for standardized forest biomass and carbon monitoring, offering: A selection of statistically robust monitoring methods designed for accurate large-scale and small-scale carbon accounting. This removes barriers that prevent fact-based decision making regarding forest carbon stocks. Cloud processing capabilities to unleash the potential of the increased volumes of high resolution satellite data and other large datasets. Forest Carbon Monitoring flyer |
| Forestry Thematic Exploitation Platform | The Forestry Thematic Exploitation Platform (Forestry TEP) enables commercial, governmental and research users in the forestry sector globally to efficiently access satellite data based processing services and tools for generating value-added [...] | VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD (FI) | Digital Platform Services | applications, forestry, platforms | The Forestry Thematic Exploitation Platform (Forestry TEP) enables commercial, governmental and research users in the forestry sector globally to efficiently access satellite data based processing services and tools for generating value-added forest information products. Via the platform, the users can also create and share their own processing services, tools and generated products. |
| FORESTSCAN | ESA’s upcoming Biomass mission will deliver valuable P-band SAR data aimed at forest aboveground biomass (AGB) estimation across the humid tropics. Additionally, the current NASA GEDI mission on the International Space Station (LiDAR), the [...] | UCL CONSULTANTS LTD (GB) | Science | Biomass, carbon science cluster, forestry, SAR, science | ESA’s upcoming Biomass mission will deliver valuable P-band SAR data aimed at forest aboveground biomass (AGB) estimation across the humid tropics. Additionally, the current NASA GEDI mission on the International Space Station (LiDAR), the NASA NISAR and JAXA ALOS-4 (L-band SAR) will widen our possibilities to estimate AGB from space. However, all these missions rely on calibration and validation data derived from field-plots. Which needs to be scalable across the typically hectare-scale satellite sensor footprints. The ForestScan project will investigate novel technologies such as Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle-based Laser Scanning (UAV-LS) to complement manual plot based measurements of AGB by collecting and analysing such data for three tropical sites in French Guiana (Paracou), Gabon (Lopé) and Malayisa (Sepilok). In addition at each of these sites airborne laser scanning data is available. The specific objectives of the study are (i) the development of a protocol for acquiring such measurements in tropical forests; (ii) analysing scaling properties of forest structure in tropical forests and (iii) high precision limited area measurement (plot census, TLS and UAV-LS) with wide area airborne laser scanning. Ultimately this effort will support the systematic collection and understanding of reference data for biomass product validation as required for the CEOS Good Practices Guideline (Duncanson et al., 2021, DOI:10.5067/doc/ceoswgcv/lpv/agb.001). |
| FOUNDATION MODELS FOR CLIMATE AND SOCIETY (FM4CS) | SummaryThe project "Foundation Models for Climate and Society" (FM4CS) seeks to leverage the breakthrough of Foundation Models (FMs) in shaping the future of Earth observation. During the last year, FMs have revolutionized the [...] | NORWEGIAN COMPUTING CENTER NORSK REGNESENTRAL (NO) | AI4EO | AI4EO, climate, generic platform service, Sentinel-1, Sentinel-2, Sentinel-3 | Summary The project “Foundation Models for Climate and Society” (FM4CS) seeks to leverage the breakthrough of Foundation Models (FMs) in shaping the future of Earth observation. During the last year, FMs have revolutionized the understanding and processing of data, in particular language data, paving the way for significant advancements in various fields. FM4CS aims to establish a multimodal FMs for Earth observation (EO), with a focus on data from the Sentinel 1-3 satellites, using the latest advancements in self-supervised learning. The FM4CS project aims to demonstrate the capabilities of FM in a range of climate and society downstream tasks: snow monitoring, flood zone mapping, sea ice mapping, iceberg detection and monitoring, and draught mapping and monitoring. Project Objectives The main objective of the FM4CS project is to unleash the potential of self-supervised learning and large-scale multimodal Foundation Models for EO use cases related to climate science and society applications and services. In particular, we aim to: Define and develop an EO-specific FM using large-scale EO archives. Develop AI4EO downstream tasks using the developed FM for the EO use-cases: snow mapping, flood zone mapping, sea ice mapping, iceberg detection and draught monitoring. Develop a roadmap for the use of FM in EO, with emphasis on scaling up, preparation for operationalization, and adoption of this technology in EO. Engage and disseminate project results with the players and potential users of AI FMs within the EO community. Downstream climate and society applications Downstream climate and society applications User-case Responsible partner Preferred Platforms Flood zone mapping Norwegian Water Resources and Energy Directorate Sentinel-1 & 2 Drought monitoring and mapping Romanian National Meteorological Administration Sentinel 1-3 Sea ice mapping The Danish Meteorological Institute Sentinel 1 & 3, AMSR2 Iceberg detection and monitoring Polar view Sentinel 1 & 2 Snow monitoring Norwegian Computing Center Sentinel 1 & 3 TBD Norwegian Computing Center Sentinel 1 & 2 |
| Frontier Development Lab (FDL) Europe | FDL Europe is a research collaboration between the ESA’s ɸ-Lab, ESA Esrin and Trillium Technologies and the University of Oxford, in partnership with private industry players such as Google Cloud, Nvidia - Scan, D-Orbit and Planet, in which the [...] | Trillium Technologies Ltd (GB) | AI4EO | AI4EO, virtual labs | FDL Europe is a research collaboration between the ESA’s ɸ-Lab, ESA Esrin and Trillium Technologies and the University of Oxford, in partnership with private industry players such as Google Cloud, Nvidia – Scan, D-Orbit and Planet, in which the latest tools and techniques in Artificial Intelligence (AI) and Machine Learning (ML) are applied to research priorities in support of ESA science and exploration. The primary vision of FDL is to advance the application of machine learning, data science, and high performance computing to problems of material concern to humankind. As such, the work of FDL is conducted in the spirit of collaboration for mutual and universal benefit, with the full intention of being published and open sourced according to academic best practice FDL Europe has consistently developed state-of-the-art in AI4EO applications with a close-eye on the needs of beneficiaries, such as UNICEF, the World Food Program and UNOSAT. FDL’s work has informed the development of Digital Twin for Earth (DTE) initiatives as well as extending the capabilities of mission operations. FDL’s work has also supported climate science research and disaster response. Illustrative successes include ‘WORLDFLOODS’ – a Machine Learning pipeline and globally labelled dataset able to provide a vector segmentation of flooding, land and clouds from orbit and rapidly return the results to Earth. The dataset has been downloaded by researchers around the world. In mid-2021, WorldFloods flew as a ML payload on D-Orbit’s Wildride mission, running Unibap’s SpaceCloud hardware. WorldFloods was able to provide a vector segmentation of a Sentinel 2 flood image for the first time. The pipeline was also retained for an RGB camera on D-Orbit’s Ion spacecraft and the model successfully re-uploaded, demonstrating for the first time the potential for both image vector compression and the porting of ML between instruments in orbit. FDL’s work Earth Digital Twinning and Cloud Classification have also shown the potential of ML to efficiently emulate high-performance-computing (HPC) to better understand, predict and improve the resolution of complex planetary processes – the latter winning ‘best paper’ at the prestigious ClimatechangeAI workshop at NeurIPS, where both projects were showcased. Both research projects produced benchmark datasets (‘RAINBENCH’ and ‘CUMULO’) available for the community. FDL is a year-long research initiative that produces published research in peer-reviewed journals, however the ML pipelines are developed during an intensive nine week sprint hosted at ESA and Oxford University during the summer – the best time to broker interdisciplinary teams of Phd-level researchers from around Europe. What makes FDL different is the emphasis on high-risk / high-reward applied AI research that takes bold concepts from low TRL (Tech Readiness Levels) through to published research and, in some cases, deployed ML pipelines, while in the process developing enhanced data products and shareable tools for the research community to build and improve on, such as ‘SatExtractor’ an open source, cloud native public satellite data extractor, allowing the rapid development of diverse analysis ready data. |
| GAME.EO | Recent years have brought tremendous advancements in the area of automated information extraction from Earth Observation (EO) imagery, but problems still remain since even state-of-the-art algorithms based on imagery alone do not provide a [...] | GISAT S.R.O. (CZ) | AI4EO | permanently open call, platforms, sustainable development | Recent years have brought tremendous advancements in the area of automated information extraction from Earth Observation (EO) imagery, but problems still remain since even state-of-the-art algorithms based on imagery alone do not provide a satisfactory solution. In these situations, it is possible to exploit the crowdsourcing of human intelligence, which is a recent promising area for EO. This is of particular interest with respect to providing information on devleoping countries to International Finance Institutions such as the World Bank.In this project an integrated (hybrid) crowdsourced and EO data-based information extraction framework is being developed. Mobile-based tools for supporting crowdsourcing campaigns and gaming approaches will be developed, and then used to mobilize and train volunteers to provide data via dedicated EO-based workflows to extract the required information in a more timely and accurate manner, with lower costs than would be incurred using professional datacollection services. The approach will be demonstrated using specific service cases for EO-based monitoring of Informal Settlements/Slum Areas (SDG11), with the aim to enhance current machine-learning algorithms for the identification, delineation and further characterization of these areas. The developed framework and tools will be tested in cooperation with World Bank users and stakeholders (GWASP/GSURRP) in an ongoing internal project1 for Dhaka, Bangladesh, to demonstrate the potential and the added value of the synergies of crowdsourcing- and EO-based information to support the World Bank’s research and operational activities. |
| GammaCloud: Feasiblity of using S1 Terrain Flattened Gamma_0 backscatter across EO platforms | The project prototyped a prototype of a processing workflow for improved Sentinel-1 backscatter data, providing a temporal stack of analysis ready data (ARD) that can be integrated into a data cube system allowing to access the data in a spatial [...] | EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT) | Digital Platform Services | permanently open call, platforms, Sentinel-1 | The project prototyped a prototype of a processing workflow for improved Sentinel-1 backscatter data, providing a temporal stack of analysis ready data (ARD) that can be integrated into a data cube system allowing to access the data in a spatial and temporal domain. |
| GENESIS | Farmers and field owners need information about the soil parameters to optimize the fertilization process. This may ultimately lead to selecting a better mix of fertilizers, and to reducing the overall amount of them. The current approach toward [...] | KP Labs Sp. z o.o. (PL) | AI4EO | AI4EO, hyperspectral | Farmers and field owners need information about the soil parameters to optimize the fertilization process. This may ultimately lead to selecting a better mix of fertilizers, and to reducing the overall amount of them. The current approach toward quantifying the soil parameters (e.g., macroelements) is very user-dependent, laborious, time-consuming, vastly manual – we have to gather and mix soil samples in the field and pass them to the lab for further chemical analysis. Also, this process does not allow us to accurately capture the information concerning the macroelements, and the number of sampling points in the field is commonly limited. KP Labs and QZ Solutions intend to use the Intuition-1 satellite to remotely detect soil parameters (specifically: potassium – K2O, phosphate – P2O5, magnesium – Mg and pH) using on-board machine learning techniques employed to analyze the acquired hyperspectral data. Hyperspectral data captures very detailed information about the observed area; however, its volume makes the data acquisition and transfer back to Earth very costly and time expensive (due to the data transmission constraints). Hence, the whole process of detecting the soil parameters will be automated on-board the Intuition-1 satellite. To make the process efficient for large-scale imaging, additional optimizations in the on-board pre-processing chain are foreseen, including filtering of too cloudy scenes based on L0 data, so heavy processing to L1 data will be avoided. Another important pre-processing step assumes determination of the bare soil area, so the soil analysis algorithms can be used only in the right context focusing on the regions of interest. Selected algorithms which will be used for pre-processing and estimating the soil parameters, will be deployed on the data processing unit called Leopard, verified during the on-ground testing and benchmarking campaign. As an output, an image with the soil parameters should be returned (see the example rendered in Figure below) – it will allow us to dramatically reduce the volume of the data that is to be transferred back to Earth, as we would be sending just the parameter maps. Moreover, the project will focus on the incremental/continuous learning which directly corresponds to the real-world scenario, where the new data may be captured (and manually or semi-automatically analysed in order to obtain the ground truth) while a machine learning model is deployed on-board spacecraft. Here, gathering new data may help us improve the models in time following the lifelong learning paradigm, but, at the same time, may easily lead to the catastrophic forgetting and interference, as the newly acquired data may be of different characteristics. Soil parameters maps Website: https://platform.ai4eo.eu/seeing-beyond-the-visible |
| Geohazards Thematic Exploitation Platform | The Geohazards Exploitation Platform or GEP supports the exploitation of satellite EO for geohazards. In particular it is a contribution to the CEOS WG Disasters to support its Seismic Hazards Pilot and terrain deformation applications of its [...] | TERRADUE SRL (IT) | Digital Platform Services | platforms | The Geohazards Exploitation Platform or GEP supports the exploitation of satellite EO for geohazards. In particular it is a contribution to the CEOS WG Disasters to support its Seismic Hazards Pilot and terrain deformation applications of its Volcano Pilot. The geohazards platform is sourced with elements – data, tools, and processing including INSAR – relevant to the Geohazards theme and related exploitation scenarios. |
| Geopedia Pay-Per-Use Demonstration on Optical High-Resolution Cloud Platform | The project enabled the Sentinel-Hub functions for MERIS, ESA Landsat, validating procurement mechanisms for a cloud-based resource tier sharing also Sentinel data. | Centre of Excellence for Space Sciences and Technologies (SPACE-SI) (SI) | Digital Platform Services | platforms | The project enabled the Sentinel-Hub functions for MERIS, ESA Landsat, validating procurement mechanisms for a cloud-based resource tier sharing also Sentinel data. |
| Geophysical Reference Data For Machine Learning (GRD4ML) | The GRD4ML project aims to create an Enhanced Environment to generate Reference Data for the Retrieval of Geophysical Parameters by Machine Learning.Scientist and application developers will have the opportunity to create, enhance, utilise and [...] | CGI ITALIA S.R.L. (IT) | AI4EO | AI4EO | The GRD4ML project aims to create an Enhanced Environment to generate Reference Data for the Retrieval of Geophysical Parameters by Machine Learning. Scientist and application developers will have the opportunity to create, enhance, utilise and manage their own datasets for training neural networks in a integrated environment based on free licensed tools and cloud computing resources, overcoming the complexity of the present practices to made up machine learning analysis. |
| GEORICE (DUE Innovator III Series) | The GEORICE innovator addresses research priorities within the Group of Earth Observation Global Agricultural Monitoring (GEOGLAM) initiative related to SAR techniques for rice monitoring. The project developed and demonstrated EO products for [...] | UNIVERSITE TOULOUSE III – PAUL SABATIER (FR) | Applications | agriculture, applications | The GEORICE innovator addresses research priorities within the Group of Earth Observation Global Agricultural Monitoring (GEOGLAM) initiative related to SAR techniques for rice monitoring. The project developed and demonstrated EO products for crop rice stage monitoring based on the high temporal frequency of Sentinel-1 over the Mekong delta to derive statistics of rice planted area and their phenological stages. GEORICE algorithms have been implemented on a cloud platform and demonstrated to national users in Vietnam up to national scale. |
| GLACIERS MASS BALANCE INTERCOMPARISON EXERCISE (GLAMBIE) | GlaMBIE project builds on nascent efforts within the IACS working group on Regional Assessments of Glacier Mass Change (RAGMAC, https://cryosphericsciences.org/activities/wg-ragmac/) to setup and coordinate an intercomparison exercise of [...] | UNIVERSITY OF ZURICH (CH) | Science | Glaciers and Ice Sheets, polar science cluster, science | GlaMBIE project builds on nascent efforts within the IACS working group on Regional Assessments of Glacier Mass Change (RAGMAC, https://cryosphericsciences.org/activities/wg-ragmac/) to setup and coordinate an intercomparison exercise of regional glacier mass changes from glaciological in-situ measurements and various remote sensing sources, including geodetic DEM differencing, altimetry, and gravimetry. Under the guidance of Scientific Advisory Committee (staffed with the RAGMAC co-chairs), an assessment framework, algorithm, and environment will be developed to compile and analyse the regional glacier mass-change results from the active research groups to come up with new consensus estimates of regional and global glacier mass changes and related uncertainties. |
| GLANCE | Prompted by the novel satellite data of glyoxal (CHOCHO) and formaldehyde (HCHO) retrieved by the high resolution spectra of the TROPOMI sounder, GLANCE aims to assess the global budget of their precursors using the MAGRITTEv1.1 global [...] | BELGIAN INSTITUTE OF SPACE AERONOMY (BIRA-IASB) (BE) | Science | air quality, atmosphere science cluster, atmospheric chemistry, environmental impacts, health, public health | Prompted by the novel satellite data of glyoxal (CHOCHO) and formaldehyde (HCHO) retrieved by the high resolution spectra of the TROPOMI sounder, GLANCE aims to assess the global budget of their precursors using the MAGRITTEv1.1 global atmospheric chemistry-transport model (CTM) and an inverse adjoint-based framework. Both compounds are formed in the oxidation of non-methane volatile organic compounds (NMVOCs), with isoprene being the most important in terms of global emissions, and they are also emitted directly, in particular, from biomass burning. CHOCHO is produced at high yields from the oxidation of specific anthropogenic compounds, namely acetylene and aromatic NMVOCs. However, the atmospheric budget of glyoxal is, to this day, still poorly understood. Whereas past studies have shown that models can reasonably well reproduce the satellite observations of HCHO, a severe underprediction of CHOCHO from spaceborne observations has been identified, pointing to a large continental CHOCHO source unaccounted for in models. GLANCE will contribute to fill in the current gap in our understanding of the CHOCHO sources worldwide and to improve the current VOC emission inventories. This is particularly important since the currently available inventories bear large uncertainties. Within GLANCE, we will first update the model to consider the updated recommendations for the reactive uptake coefficients for CHOCHO to aerosol particles and cloud droplets, the recent detailed chemical oxidation mechanism for aromatic hydrocarbons based on the latest laboratory and theoretical results, and a state-of-the-art chemical mechanism for isoprene oxidation. A joint (two-compound) inversion scheme will be designed to handle the simultaneous use of HCHO and CHOCHO columns as top-down constraints. The emissions to be optimized include biogenic isoprene, biomass burning NMVOCs, two classes of anthropogenic NMVOCs (glyoxal precursors and other compounds), and an additional biogenic precursor meant to account for the missing glyoxal source suggested in previous studies. The emissions will be derived on monthly basis from 2018 to 2020. The inversion results will be evaluated against a wide array of in situ observations, as well as FTIR and MAX-DOAS data. Furthermore, the outcomes of GLANCE will be compared against 3 aircraft campaigns performed by NOAA: the first airborne CHOCHO measurements from the SENEX 2013 research flights over the southeast U.S., the recent FIREX-AQ 2019 aircraft campaign focusing on wildfires in the western U.S., and the AEROMMA mission planned in summer 2023 over U.S. megacities.The main innovative aspects of GLANCE are: the use of the improved high resolution retrievals of HCHO and CHOCHO from TROPOMI in a two-compound inversion framework; the first top-down estimation of the emissions of anthropogenic CHOCHO precursors from space; the strength and distribution of the missing CHOCHO source, its uncertainty, and the identification of potential candidates explaining it; the extensive evaluation of the optimization against in situ, ground-based and aircraft data. |
| GlobDiversity: Development of High-Resolution RS-Enabled EBVs on the Structure and Function of Terrestrial Ecosystems | A global knowledge of the state of and changes to biological diversity can only be based on a combination of in-situ and remotely sensed observations integrated into a comprehensive biodiversity knowledge system. The needs to integrate satellite [...] | UNIVERSITY OF ZURICH (CH) | Applications | applications, ecosystems/vegetation | A global knowledge of the state of and changes to biological diversity can only be based on a combination of in-situ and remotely sensed observations integrated into a comprehensive biodiversity knowledge system. The needs to integrate satellite observations in a unified and global biodiversity monitoring strategy has been recognised by the Convention on Biological Diversity (CBD) and the intergovernmental Science-Policy Platform on Biodiversity (IPBES). A framework for such a global and integrated biodiversity monitoring system is developed by the Group on Earth Observation Biodiversity Observation Network (GEO BON) under the general concept of Essential Biodiversity Variables (EBV). GlobDiversity is the first large-scale project explicitly designed to develop and engineer Remotely Sensed enabled Essential Biodiversity Variables (RS-enabled EBVs). The objective of the project is to develop, validate, showcase and scale up a number of High Resolution RS-enabled EBVs on the structure (characterisation of the ecosystem components such as ecosystem extent, distribution and fragmentation) and function (characterisation of the ecosystem processes such as vegetation phenology or primary productivity) of terrestrial ecosystems, in support to the collaborative efforts of CBD, IPBES and GEO BON to build a global knowledge system on the biodiversity of ecosystems. The project produces reference documentation for the development of RS-enabled EBVs, supported by pilot demonstrations of 3 RS-enabled EBVs (Land Surface Phenology, Canopy Chlorophyll Content and Ecosystem Fragmentation) on 10 pilot sites selected in key terrestrial biomes. In addition, Vegetation Height is also investigated as potential future RS-enabled EBV. GlobDiversity contributes to the the collaborative efforts of the biodieversity communtity to prioritize and specify the EBVs retrievable from remote sensing. |
| GlobWetland Africa: Development of EO Tools for the Conservation, Wise-Use and Effective Management of Wetlands in Africa | GlobWetland Africa aims at facilitating the exploitation of satellite observations for the conservation, wise-use and effective management of wetlands in Africa, by providing African stakeholders with EO methods and tools to fulfil their Ramsar [...] | DHI GRAS A/S (DK) | Applications | applications, water resources | GlobWetland Africa aims at facilitating the exploitation of satellite observations for the conservation, wise-use and effective management of wetlands in Africa, by providing African stakeholders with EO methods and tools to fulfil their Ramsar obligations and monitor the extent, integrity and conditions of their wetlands. The main project output is a free-of-charge and open-source toolbox for the end-to-end processing of a large portfolio of EO products (wetland inventory, wetland habitat mapping, wetland inundation regimes, water quality, mangrove inventory and characterisation, river basin hydrology) and the subsequent derivation of spatial and temporal indicators on wetland status and trends, from local to basin scales. The project is executed in close cooperation with the Africa team of the Ramsar convention on wetlands and a number of African stakeholders representing different user profiles (Ramsar African regional initiatives, Ramsar National Focal Points, River Basin Authorities, International Conservation Organisations). GlobWetland Africa helps African authorities to make the best use of satellite-based information on wetland extent and condition for better measuring the ecological state of wetlands and hence their capacity to support biodiversity and provide ecosystem services. As an ultimate objective GlobWetland Africa aims to enhance the capacity of the African stakeholders to develop their own national and regional wetland observatories. |
| GOCE gravity gradients for time-variable applications (GOCE4TV-APPs) | The gravity gradients of the highly successful ESA Earth Explorer mission GOCE (Gravity field and steady-state ocean circulation explorer), which have been reprocessed by applying enhanced calibration strategies in the frame of the ESA project [...] | TECHNICAL UNIVERSITY OF MUNICH (DE) | Science | permanently open call, science, solid earth, water cycle and hydrology | The gravity gradients of the highly successful ESA Earth Explorer mission GOCE (Gravity field and steady-state ocean circulation explorer), which have been reprocessed by applying enhanced calibration strategies in the frame of the ESA project GOCE High-level Processing Facility (HPF), have reached a very high quality level, especially in the long-wavelength spectral range where the main time-variable gravity field signals occur. In the frame of this project, it shall be investigated if time-variable gravity field signals can be extracted from these newly processed gravity gradient data. Due to their direct relation to mass and mass change, temporal variations reflect mass transport processes in the Earth system, which by themselves are subtle indicators of climate change. Therefore, the GOCE gradients shall be analysed for and used in dedicated time-variable geophysical applications, such as the detection of earthquakes reflecting pre-, co-, and post-seismic mass movement, land hydrology reflecting changes in the total water storage of large hydrological catchments, and ice mass balance trends such as ice mass melting in Greenland and Antarctica. For this purpose, existing processing strategies based on spherical harmonic modelling of the gravity field, as well as promising contemporary processing and parameterization strategies, among them a so-called Mascon approach, shall be applied. The latter is routinely used in temporal gravity modelling based on data of the inter-satellite ranging mission GRACE (Gravity Recovery And Climate Experiment), but has never been applied to GOCE data yet, and will be developed and adapted for GOCE data assimilation and data exploitation. The main outcome will be gradiometry-only regional and global data sets of identified gravity changes, giving information about the amplitude, seasonal/periodic and drift behavior of the changes. The results will be validated against GRACE temporal gravity models. Especially, it will be evaluated if by means of GOCE gradients the spatial resolution of recoverable time-variable gravity signals can be increased. The data sets shall be provided in common and easy to use data formats in order to be used within relevant related fields of applications. |
| GOCE+ ANTARCTICA | The overarching objective of this activity is to explore the potential of GOCE to improve lithospheric modelling over Antarctica, to reduce uncertainties in bedrock topography and to study the implication on GIA modelling based on the derived [...] | UNIVERSITY OF KIEL (DE) | Science | Antarctica, GOCE, polar science cluster, science | The overarching objective of this activity is to explore the potential of GOCE to improve lithospheric modelling over Antarctica, to reduce uncertainties in bedrock topography and to study the implication on GIA modelling based on the derived information. This ismotivated by recent scientific developments, applications and new products that have emerged from ESA’s GOCE mission. In particular,a new data set, provided through the GOCE+ Theme 2 activity (Bouman et al 2014), should enable geophysical application and modelling over Antarctica with the goal to better understand and model the Earth’s interior and its dynamic processes, contributing to new insights into the geodynamics associated with the lithosphere, mantle composition and rheology. This activity shall investigate the potential to determine bedrock topography of the grounded part of the ice sheet with high spatial resolution and accuracy. Furthermore, the activity shall determine – with additional geophysical data and information – the thermal structure or composition of the upper mantle, and hereby to link crust and upper mantle. This will in turn allow to study Earth’s rebound (glacial isostatic adjustment, GIA) over Antarctica from the several kilometre thick ice sheets that covered Antarctica. |
| GOCE++Dynamic Topography at the Coast and Tide Gauge Unification (DYCOT) | The objective of this activity is a consolidated and improved understanding and modelling of coastal processes and physics responsible for sea level changes on various temporal/spatial scales. In practice, this study shall combine several [...] | Technical University of Denmark (DK) | Science | oceans, science | The objective of this activity is a consolidated and improved understanding and modelling of coastal processes and physics responsible for sea level changes on various temporal/spatial scales. In practice, this study shall combine several elements: Propose and develop an approach to estimate a consistent DT at tide gauges, coastal areas, and open ocean Validate the approach in well-surveyed areas where DT can be determined at tide gauges Determine a consistent MDT using GOCE with consistent error covariance fields Connect measurements of a global set of tide gauges and investigate trends Develop and outlook how the approach could be further improved using improved coastal altimetry. |
| GODAE OCEAN OBSERVING SYSTEM EVALUATION OF SATELLITE SEA SURFACE SALINITY AND EL NINO 2015 (SMOS-NINO15) | SMOS Sea Surface Salinity (SSS) is not yet widely used by the ocean modelling community. In part this is due to the technical challenges of assimilating satellite SSS and assessing the impact of the assimilation using objective tools and [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Science | oceans, science, SMOS | SMOS Sea Surface Salinity (SSS) is not yet widely used by the ocean modelling community. In part this is due to the technical challenges of assimilating satellite SSS and assessing the impact of the assimilation using objective tools and reporting. The Global Ocean Data Assimilation Experiment (GODAE) Ocean View Science Team (GOV-ST) group Observing System Evaluation Task Team (OSEVal-TT, see https://www.godae-oceanview.org/science/task-teams/observing-system-evaluation-tt-oseval-tt/) was convened by GOV-ST to evaluate the impact of different measurement systems by running specific observing system experiments and producing an Observation Impact Statement Report. This allows GOV-ST to formulate specific requirements for ocean observations on the basis of improved understanding of data utility.This activity is focussed on the design, implementation and reporting of an Observing System Evaluation of satellite SSS during the strong El Nino 2015/16 event. Strong SSS signals are present in SMOS data prior and during to the El Nino event. Inaddition to SMOS, full use of the NASA SMAP mission data will be encouraged. The output will be a GOV-ST Observation Impact Statement Report focussed on satellite SSS, journal publications and a workshop dedicated to the findings and approach taken by the study team. |
| Grassland cutting detection for agriculture | The main objective is to provide an operational methodologies and software components that combines the data from remote sensing satellites (in particular Sentinel‐1 and Sentinel‐2) that will allow to detect and monitor the grassland cutting and [...] | KAPPAZETA LTD (EE) | Enterprise | agriculture, regional initiatives, Sentinel-1, Sentinel-2 | The main objective is to provide an operational methodologies and software components that combines the data from remote sensing satellites (in particular Sentinel‐1 and Sentinel‐2) that will allow to detect and monitor the grassland cutting and grazing. This tool is intended to be deployed by the National Paying Agencies (NPAs) which have the role to control the owners of permanent and agricultural land to insure they adhere to certain management policies of the EU Common Agriculture Policy resulting in 90% accuracy of grassland cutting detection rates, fewer in situ inspections, and decrease wrongly allocated funds due to fraudulent farmers. The system was demonstrated to the Paying Agencies of Estonia, Denmark and Sweden and further extended to develop the service trial in Poland – Agency for Restructuring and Modernisation of Agriculture (ARMA). |
| Gravitational Seismology | This project analyses the extent to which tectonic processes at plate boundaries give rise to changes that can be detected as variations in gravitational acceleration. The requirements for sensitivity are now being fed into preparatory studies [...] | UNIVERSITA DEGLI STUDI DI MILANO (IT) | Science | permanently open call, science | This project analyses the extent to which tectonic processes at plate boundaries give rise to changes that can be detected as variations in gravitational acceleration. The requirements for sensitivity are now being fed into preparatory studies for future gravity measurement missions. |
| Grazing detection from Copernicus data for agricultural subsidy checks | The project will develop methodology for grazing detection based on Sentinel 1 and 2 data. address grazing intensity, set out benchmarks for detection units (LU/ha) and test the methodology with selected paying agencies in Europe (Czech, [...] | KAPPAZETA LTD (EE) | Enterprise | agriculture, permanently open call, Sentinel-1, Sentinel-2 | The project will develop methodology for grazing detection based on Sentinel 1 and 2 data. address grazing intensity, set out benchmarks for detection units (LU/ha) and test the methodology with selected paying agencies in Europe (Czech, Spanish, Estonian, Swedish). |
| Ground Deformation from Meteorological, Seismic and Anthropogenic Changes Analysed by Remote Sensing, Geomatic Experiments and Extended Reality – GERMANE | Living Planet Fellowship research project carried out by Romy Schlögel. Within this project we intend to analyse ground deformation hazards induced by meteorological changes and seismotectonic conditions in eastern Belgium, western Germany [...] | UNIVERSITY OF LIEGE (BE) | Science | living planet fellowship, SAR, science, solid earth | Living Planet Fellowship research project carried out by Romy Schlögel. Within this project we intend to analyse ground deformation hazards induced by meteorological changes and seismotectonic conditions in eastern Belgium, western Germany and the south-eastern Netherlands. Thus, its outcomes should also be of interest for the ongoing Interreg project Einstein Telescope EMR Site & Technology (E-TEST). Focus is on the differentiation of weather-induced and seismotectonically influenced Earth surface processes in the E-Test area where human-induced groundwater level changes are also observed. The regional aspect of ground deformation in the E-Test area would be approached by Synthetic Aperture Radar Interferometry (InSAR) processing. Detailed analyses will be performed along the numerous faults crossing the E-Test area. Differential ground deformation across fault structures should, however, be quite small, probably of the amount of a few millimetres. Such small displacements require extremely precise surveying, using InSAR studies supported by the installation of fixed corner reflectors. Also, repeated very high resolution (VHR) image and digital elevation model (DEM) will be collected using Unmanned Aerial Vehicles covering the whole potentially subsiding area is necessary (supported by ground-based measurements). In parallel, geodetic monitoring using Global Navigation Satellite System (GNSS) measurements on benchmarks as well as Essential Climate Variables (ECVs) monitoring to determine the meteorological conditions when increase of ground deformation observed. The project also aims to develop a permanent monitoring system which would last after the duration of the project. Finally, we will develop models allowing us to manage and visualise (also in Extended Reality environments) the slow ground movements measured by remote sensing. |
| Ground Reference Observations Underlying Novel Decametric Vegetation Data Products from Earth Observation – GROUNDED EO | Ground Reference Observations Underlying Novel Decametric Vegetation Data Products from Earth Observation (GROUNDED EO) aims to exploit cutting-edge machine learning approaches, ground data collection capabilities, and data fusion methods to [...] | University of Salford (GB) | Science | agriculture, crops and yields, ecosystems/vegetation, living planet fellowship, Sentinel-2 | Ground Reference Observations Underlying Novel Decametric Vegetation Data Products from Earth Observation (GROUNDED EO) aims to exploit cutting-edge machine learning approaches, ground data collection capabilities, and data fusion methods to develop improved decametric vegetation biophysical products from Sentinel-2 and -3, ultimately facilitating better environmental decision making. The objectives of the project are to: Develop a harmonised global ground reference database for vegetation biophysical variables with observations throughout the growing season, capitalising on routine data collection by recently established environmental monitoring networks, advances in novel automated field instrumentation, and developments in automated data processing and uncertainty evaluation. Exploit the harmonised ground reference database to develop and benchmark an improved biophysical processor, free from biases due to radiative transfer model assumptions (achieved by training cutting-edge machine learning algorithms, which have previously been restricted by ground reference data availability and consistency); Leverage synergetic potential with Sentinel-3 to derive synthetic Sentinel-2 data, upon which the improved biophysical processor will be applied, filling gaps in the original Sentinel-2 time series (e.g. due to cloud cover). Biophysical variable retrievals from the synthetic data will be validated using ground reference observations that didn’t match the original Sentinel-2 observations. Vegetation covers approximately 70% of the terrestrial surface, influencing biogeochemical processes through controls on the exchange of water, carbon, and energy with the atmosphere. Accurate estimates of biophysical variables describing vegetation condition and dynamics are required as inputs to models of crop yield, carbon exchange, and the weather and climate systems, which are fundamental to developing successful environmental policy, and play a crucial role in informing effective climate change mitigation strategy. Accounting for approximately 30% of the land surface and approximately 50% of its gross primary productivity (GPP), the world’s forests are crucial in terms of carbon storage, but also provide a range of important ecosystem services, acting as a source of fibre, fuel and timber. Meanwhile, agricultural crops, which account for approximately 13% of the land surface, represent the main source of the world’s food, whose security needs to be ensured in the context of an increasing global population. High quality EO-derived estimates of vegetation biophysical variables are essential for monitoring and managing these resources. Whilst current retrieval algorithms including the Sentinel-2 Level-2 Prototype Processor (SL2P) can now provide routine decametric (10 m to 100 m) estimates of biophysical variables including leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR), they are subject to known biases due to assumptions embedded within the radiative transfer models used in their training. Meanwhile, their temporal frequency (≥ 5 days) cannot resolve rapid changes in vegetation status (e.g. due to stress, pests, and disease), particularly in cloud-prone environments. GROUNDED EO will provide a fundamental advancement upon these algorithms. By taking advantage of cutting-edge machine learning approaches and ground data collection capabilities, retrieval algorithms will be trained on real EO data and contemporaneous ground reference observations, enabling biases due to radiative transfer model assumptions to be avoided. Spatiotemporal data fusion will then enable improved temporal coverage to be attained. In achieving these objectives, GROUNDED EO will also deliver a step change in the provision of ground reference observations, which have been limited in quantity, typically being obtained through one-off field campaigns restricted to the peak of the growing season, and which have also suffered from inconsistencies and the presence of unquantified measurement uncertainties. By collecting and harmonising observations from novel automated field instrumentation and recent environmental monitoring networks using a standardised processing chain, and by adopting traceable uncertainty quantification methods developed under the Fiducial Reference Measurements (FRM) programme, these limitations will be addressed. Overall, by increasing the accuracy and spatiotemporal coverage of decametric LAI and FAPAR products, GROUNDED EO has potential to reduce uncertainties in downstream applications, providing improved estimates of variables such as crop yield and GPP, and ultimately resulting in better environmental decision making. |
| Harmonised Landsat-8 and Sentinel-2 Analysis-Ready Products | The project developed a prototype service providing analysis-ready harmonized Landsat-8 and Sentinel-2 data/products to the user for easy exploitation. The service will be embedded as a SNAP “plug in”, aiming to be available in the Copernicus [...] | TELESPAZIO VEGA UK LIMITED (GB) | Digital Platform Services | permanently open call, platforms | The project developed a prototype service providing analysis-ready harmonized Landsat-8 and Sentinel-2 data/products to the user for easy exploitation. The service will be embedded as a SNAP “plug in”, aiming to be available in the Copernicus Data and Information Access System (DIAS). |
| Harmonizing and advancing retrieval approaches for present and future polarimetric space-borne atmospheric missions (HARPOL) | Atmospheric aerosol particles strongly influence climate by scattering and absorbing light (direct forcing) and by changing cloud properties (indirect forcing). The corresponding radiative forcing represents one of the most uncertain radiative [...] | Netherlands Institute for Space Research (NWO-I) (NL) | Science | Aerosols, Altitude, atmosphere, atmosphere science cluster, permanently open call | Atmospheric aerosol particles strongly influence climate by scattering and absorbing light (direct forcing) and by changing cloud properties (indirect forcing). The corresponding radiative forcing represents one of the most uncertain radiative forcing terms as reported by the Intergovernmental Panel on Climate Change (IPCC). To improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, optical properties like Aerosol Optical Thickness (AOT) and Single Scattering Albedo (SSA), as well as the aerosol height profile are of crucial importance. It has been demonstrated by studies on synthetics measurements, airborne measurements, and space-borne measurements that Multi-Angle Polarimetric (MAP) measurements are needed to provide information about detailed aerosol properties like size distribution, refractive index, SSA, in addition to the AOT. The only MAP instrument that has provided a multi-year data set (2005-2013) in the past has been the French POLDER-3 instrument on the PARASOL mission. Now space agencies realize the large potential of MAP instrumentation, in the 2020s several of such instruments will be launched, e.g. 3MI on METOP-SG (ESA-2023), SPEXone and HARP-2 on PACE (NASA-2023), and a MAP on the CO2-Monitoring mission (ESA-2025) and A-CCP (NASA-2028). To cope with the increased information content on aerosols of MAP instrumentation and to assess the climatic effect of aerosols, new tools for retrieval need to be (further) developed. So far, this development has lagged behind the instrument development, which is the reason for the under-exploitation of the existing POLDER-3/PARASOL data sets. Currently, there are two algorithms that have demonstrated capability at a global scale to exploit the rich information content of MAP measurements: the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm, developed at the Laboratory of Atmospheric Optics (LOA) of the University of Lille and the GRASP-sas company, and the Remote Sensing of Trace gases and Aerosol Properties (RemoTAP) algorithm developed at SRON – Netherlands Institute for Space Research. Both algorithms show good performance against ground based AERONET measurements and already important scientific advancement has been made using the corresponding data products. Nevertheless, when looking at global maps, significant differences are apparent between the two algorithms. In order to improve retrieval products from PARASOL and the upcoming missions containing MAP instrumentation (3MI/METOP-SG, SPEXone/PACE, HARP2/PACE, MAP/CO2M) it is essential to understand the reasons for the differences between the GRASP and RemoTAP algorithms. Therefore, in this project we propose to perform an extensive and systematic comparison between the two algorithms. We expect this will lead to optimized algorithm choices for both algorithms leading to better aerosol products and error characterization. The project will results in improved global data sets of aerosol properties from both algorithms. |
| HeatAdapt: Heat stress monitoring supporting Austrian climate change adaptation strategies | Most of the largest cities experience profound changes due to urbanization and hence, city administrations are facing challenges in order to safeguard high quality urban growth despite increasingly tight spatial resources. Modifications in the [...] | GeoVille (AT) | Enterprise | Alps, Ecosystems, generic platform service, regional initiatives, Sentinel-2 | Most of the largest cities experience profound changes due to urbanization and hence, city administrations are facing challenges in order to safeguard high quality urban growth despite increasingly tight spatial resources. Modifications in the built up environment increase the temperature of cities compared to their surroundings and are more prone to excess heat. Moreover, climate change in general and the increasing temperatures in particular pose a particular risk for mountainous areas affecting alpine communities and their economy. In July 2023, Europe experienced record breaking air temperatures, making it the hottest in the ERA5 data record, which goes back to 1940 (source: Copernicus Climate Change Service). This increase in temperature has far reaching consequences , with issues related to i.e.: Health Heat induces stress on the human body, particularly dangerous for infants and elders Urban planning : Urban heat island effect, Heat related health issues; energy systems strain (e.g. more air conditioning) Infrastructure : increased cost & environmental burden , street and pavement lifetime (cracks, softening, etc.) etc.), maintenance and repair Agriculture : Irrigation crop health issues ,act. Taking action in terms of adaptation is not only the focus of larger cities but also of any growing built up or settlement area as well as mountain region. Understanding how land use and climate trends lead to changes to the local climate is essential for decision makers to find optimally cost effective, evidence based, and consistent solutions for sustainable cities but also for communities in rural or mountainous areas. The project HeatAdapt combines Land use and Land Cover (LULC) and climate data to demonstrate the effect of urbanization or other LULC changes on ambient temperatures and supports the location of other heat related hotspot areas in rural and mountainous regions at high spatial resolution. Making use of regional clim ate model (RCM) based scenario data will further allow to assess future expected areas for which adaptation actions will be required (e.g., greening activities) allowing city administrations and municipalities to plan ahead (e.g., demonstrate effect of additional soil sealing). HeatAdapt uses artificial intelligence (AI) and multi sensor data fusion methodologies to develop a prototype algorithm for monitoring land surface temperature (LST). Further, climate scenarios are fused with the model, enabling AOI based scenario analysis factoring in LULC changes. HeadAdapt will provide statistical outputs of proposed indicators per administrative unit (province, district, municipalities, census units) and will allow for a statistical evaluation of relation between LULC composition and temperature indicators and potential demonstration of effects changing LULC composition . The project is part of the GTIF demonstrator (Green Transition Information Factory), focusing on Austria to explore Green Transition pathways. For further information, please contact sammer@geoville.com |
| HI-FIVE: High-Resolution Forest Coverage with InSAR & Deforestation Surveillance | Living Planet Fellowship research project carried out by Francescopaolo Sica. Forests are of paramount importance for the Earth’s ecosystem, since they play a key-role in reducing the concentration of carbon dioxide in the atmosphere and in [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | biosphere, living planet fellowship, science | Living Planet Fellowship research project carried out by Francescopaolo Sica. Forests are of paramount importance for the Earth’s ecosystem, since they play a key-role in reducing the concentration of carbon dioxide in the atmosphere and in controlling climate changes. The study of deforestation and development of global forest coverage and biomass is fundamental for assessing forests’ impact on the ecosystem. Remote sensing represents a powerful tool for a constant monitoring at a global scale of vegetated areas. In particular, given the daylight independence and the capability to penetrate clouds, space-borne synthetic aperture radar (SAR) systems represent a unique solution for the mapping and monitoring of forests. Sentinel-1, with its large coverage and short revisit-time, is a breakthrough technology, ideal for the generation of a constantly updated forest coverage map product and for the rapid monitoring of large-scale areas, aiming at detecting ongoing deforestation activities and forest disturbance. The main objective of the proposed research project is to develop and implement advanced image-processing methods and strategies for the generation of high-resolution maps of forest coverage and deforestation from Sentinel-1 interferometric SAR data. Even though the detected SAR backscatter already provides useful information on forest coverage and structure, the use of SAR interferometry adds valuable and reliable information to the classification method. In particular, the temporal dynamic of the interferometric coherence, with a sampling period of 6 or 12 days, is investigated and modeled for different types of land cover. The accurate estimation of InSAR parameters is of fundamental importance for approaching this analysis. The proposed methodology exploits nonlocal estimation methods to retrieve reliable information about InSAR parameters of the full-resolution SAR image. Different classification approaches are compared, from classical pixel/region-based classifier, to more recent machine learning approaches, such as Deep Convolutional Neural Networks. Furthermore, since both temporal and volume decorrelation phenomena affect the coherence measurement in repeat-pass systems, such as Sentinel-1, I further propose the use of TanDEM-X bistatic data (simultaneous acquisitions) as high-resolution reference to support the modeling of Sentinel-1 backscatter information and its InSAR coherence temporal dynamic. Indeed, the combined use of single- and repeat-pass data allows for the isolation of volume and temporal decorrelation and for a more suitable use of the coherence at the aim of land classification. Eventually, Landsat, Sentinel-2, TanDEM-X, and possibly laser data, together with ground truth references, will be used for training and validation. |
| High information content ozone profile algorithm for ground-based passive remote sensing instruments (OPA) | LuftBlick Earth Observation Technologies (LuftBlick) and the Royal Belgian Institute for Space Aeronomy (BIRA) propose to develop a novel algorithm to derive ozone profiles from measurements of ground-based passive remote sensing instruments. [...] | LUFTBLICK OG (AT) | Science | Altitude, atmosphere, atmosphere science cluster, atmospheric chemistry, permanently open call | LuftBlick Earth Observation Technologies (LuftBlick) and the Royal Belgian Institute for Space Aeronomy (BIRA) propose to develop a novel algorithm to derive ozone profiles from measurements of ground-based passive remote sensing instruments. These are the highlights of our proposed activity: The novel algorithm distinguishes itself in several ways from existing approaches: It uses MAX-DOAS sky observations combined with direct sun measurements; It relies on absolute slant columns instead of relative ones; It combines results from UV and VIS spectral regions (Huggins and Chappuis ozone bands respectively) to make use of their different path lengths; It adds the retrieved effective ozone temperature to the input; It analyses entire days as a whole instead of single measurement sequences; It includes temperature profiles from re-analysis to be used in combination with the retrieve effective ozone temperatures. Once validated and made operational, the novel algorithm can be applied to new and existing datasets such as from the Pandonia Global Network (PGN). By this it would be an extremely valuable contribution to our knowledge of tropospheric ozone with direct impact to air quality, tropospheric chemistry and satellite validation. Having a working operational technique to derive TropO3 information from ground-based passive remote sensing measurements would increase our knowledge about TropO3 substantially at hardly any additional cost. Pandoras (or other MAX-DOAS instruments) are distributed in existing networks, e.g. the Pandona Global Network (PGN) with >100 locations around the world and are most often already performing the types of measurements which we plan to use for the algorithm we propose to develop. Hence a working ozone profile algorithm can be applied to these observations as well as on additional worldwide data sets which extend several years into the past. |
| HIGH-LATITUDE POYNTING FLUX INTO AND OUT OF THE ATMOSPHERE: SWARM, SUPERDARN AND AMPERE OBSERVATIONS (HLPF-SSA) | The Earth’s upper polar atmospheric region is constantly bombarded with energy input from the interaction between the magnetosphere and the solar wind. This controls immediately visible phenomena like the aurora borealis and australis, but also [...] | UNIVERSITY OF SASKATCHEWAN (CA) | Science | atmosphere, ionosphere and magnetosphere, living planet fellowship, swarm | The Earth’s upper polar atmospheric region is constantly bombarded with energy input from the interaction between the magnetosphere and the solar wind. This controls immediately visible phenomena like the aurora borealis and australis, but also results in changes to the composition and dynamics of the atmosphere itself. The total rate of electromagnetic energy per unit area that travels between the magnetosphere and ionosphere, i.e. between the Earth’s space environment and upper atmosphere, is called the Poynting flux. The Poynting flux can be measured by each satellite in the ESA Swarm constellation. The Poynting flux is one of the most important quantities for space weather studies to accurately determine due to its potential wide-reaching impact on the function of low earth orbiting satellites. This project will include four studies that examine the nature of how Poynting flux is deposited into the ionosphere-thermosphere system, the variability of small-scale Poynting fluxes within larger scale features, and the behaviour of the ionosphere spatially and temporally during uncommon events of upward Poynting flux. It is thought that enhancements of the neutral mass density in the thermospheric cusp region are due to small-scale (<1km) and high-magnitude (several tens of mW/m2) Poynting fluxes in the same region. Previous studies have been unable to fully confirm this, as many instruments lack the ability to measure Poynting fluxes on scales less than a kilometre. The electric field instruments on board the Swarm satellites however have this capability, and so the first study of this proposal will examine statistically the prevalence of sub-kilometre Poynting fluxes, mainly around the dayside cusp region. Whilst Swarm can offer high-resolution measurements of the Poynting flux, it is limited to ionospheric regions overlapping with Swarm orbits. Poynting flux can also be calculated using a combination of data from the Super Dual Auroral Radar Network (SuperDARN) and the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). Although the SuperDARN/AMPERE estimation would be global in scale rather than along the track of an orbit, the spatial resolution of both instruments means Poynting flux variability present within larger scale features (like field-aligned and substorm current regions) would be missed. The second study is therefore a multi-instrument study to investigate the small-scale features (measured by Swarm) embedded within large scale ionospheric features (measured by SuperDARN and AMPERE). Finally, both the duration and spatial extent of upward Poynting fluxes will be investigated in studies 3 and 4. When Poynting flux is upward, instead of downward into the atmosphere, it means an ionospheric electric field is driving the magnetosphere rather than the other way around. Upward Poynting flux can be due to the neutral wind flywheel effect, when residual momentum in thermospheric neutrals (from previous geomagnetically active conditions) maintains an ionospheric electric field even though the previous driver (convection of the magnetosphere) stops. This is a seldom studied subject, but the combination of Swarm Poynting flux measurements with the “always-on” global coverage of SuperDARN will offer new insight into how the thermosphere can feedback energy to the magnetosphere. |
| High-resolution methane mapping with hyper and multispectral data (HiResCH4) | The detection and repair of methane leaks from fossil fuel production activities have been identified as a key climate change mitigation strategy. In the last years, a number of optical satellite missions with a spatial resolution of 30-m or [...] | UNIVERSITAT POLITÈCNICA DE VALÈNCIA (ES) | Science | atmosphere, atmosphere science cluster, permanently open call, science, Sentinel-2 | The detection and repair of methane leaks from fossil fuel production activities have been identified as a key climate change mitigation strategy. In the last years, a number of optical satellite missions with a spatial resolution of 30-m or better have shown potential for the detection of strong methane plumes emitted by point sources, which is key to guide emission reduction efforts. Those high resolution missions include two types of optical imagers, namely hyperspectral (e.g. PRISMA) and multispectral (e.g. Sentinel-2). The number of studies using either of those classes of spaceborne instruments to map methane point emissions is rapidly increasing. The overarching objective of this project is to assess the potential and limitations of spaceborne hyperspectral and multispectral missions for high-resolution methane mapping. Critical tasks to achieve this goal are the implementation of a realistic end-to-end simulator, the development of advanced methane retrieval methods, and the evaluation of methane emissions at different sites using real data from those missions. Methane emissions from fossil fuel extraction and transport Methane (CH4) emissions from fossil fuel production activities have been found to account for 35% (range 30%–42%) of total global anthropogenic emissions. Emissions mostly originate from oil and gas production infrastructure, such as wells, gathering stations, compressor stations, storage tanks, pipelines, processing plants, and flares, and also coal mines can be strong methane emitters. These industrial methane emissions typically happen as so-called “point emissions”, namely plumes emitted from small surface elements and containing a relatively large amount of gas. The detection and elimination of unintended methane emissions from fossil fuel production activities have been identified as a key means to reduce the concentration of greenhouse gases in the atmosphere. Detecting methane point emissions from space The Sentinel-5P/TROPOMI mission, launched in 2017, is leading a revolution in this field, but its 7-km pixel size does not generally allow for sampling of individual point sources. Fortunately, very recent scientific developments are showing that high-resolution (30 m or better) methane retrievals are possible using land-oriented satellite missions with optical imagers sampling the 2300-nm methane absorption. On the one hand, hyperspectral missions have a relatively high sensitivity to methane due to their dense spectral sampling of the strong methane absorption at 2300 nm, but only provide sporadic acquisitions over pre-selected sites. On the other hand, multispectral missions offer a continuous global coverage within some days, but with a lower sensitivity to methane than hyperspectral missions. Better understanding the potential and limitations of these new data sets, and the synergies between them and with TROPOMI, are key for future satellite-based methane emission mitigation efforts. |
| HR-AlbedoMap: Generation of high-resolution spectral and broadband surface albedo products based on Sentinel-2 MSI measurements | The project aims at improving a current surface albedo generation system by adapting and integrating a deep learning system for cloud detection, an advanced atmospheric correction model which considers the surface BRDF effects, and a new [...] | UCL CONSULTANTS LTD (GB) | Science | carbon science cluster, permanently open call, science, Sentinel-2, Surface Radiative Properties | The project aims at improving a current surface albedo generation system by adapting and integrating a deep learning system for cloud detection, an advanced atmospheric correction model which considers the surface BRDF effects, and a new technology allowing to retrieve high-resolution albedo from high-resolution reflectance by combining with downscaled MODIS BRDF climatology |
| HydroCoastal: coastal ocean and inland water altimetry | HYDROCOASTAL was a project aimed at maximising the exploitation of SAR and SARIn altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process data from CryoSat-2 and Sentinel-3. Optical [...] | SATELLITE OCEANOGRAPHIC CONSULTANTS LTD. (GB) | Science | altimeter, bathymetry and seafloor topography, coastal zone, CryoSat, ocean science cluster, oceans, OLCI, rivers, science, Sentinel-2, Sentinel-3, SLSTR, surface water, tides, water cycle and hydrology | HYDROCOASTAL was a project aimed at maximising the exploitation of SAR and SARIn altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process data from CryoSat-2 and Sentinel-3. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products. New SAR and SARIn processing algorithms for the coastal zone and inland waters were developed, implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme was implemented to generate global coastal zone and river discharge data sets. Case studies assessed these products in terms of their scientific impacts. All the produced data sets are available on request to external researchers, and full descriptions of the processing algorithms will be provided. What are the specific science and technical focuses? The scientific objectives of HYDROCOASTAL were to enhance our understanding of interactions between inland water and coastal zone, between coastal zone and open ocean, and small-scale processes that govern these interactions. Also the project aimed to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea level changes. The technical objectives were to develop and evaluate new SAR and SARIn altimetry processing techniques in support of the scientific objectives, including stack processing, filtering and retracking. Also an improved Wet Troposphere Correction was developed and evaluated. Associated user needs, applications, and issues The potential benefits of global data sets were investigated through a series of impact assessment case studies in the second year of the project. Case studies considered different estuaries and coastal regions including the Bristol Channel (UK), the German Bight and South-Western Baltic Sea, the Northern Adriatic, and the Ebro River and Delta. They each exhibit specific features, but common across the locations are flooding and erosion, sedimentation, the importance of accurate high resolution local modelling, the vulnerability of coastal habitats, the connection between river discharge and coastal sea levels. Inland Water Case Studies considered selected river systems in China to investigate the potential to develop operational hydrological forecasting, lakes and rivers in Ireland to investigate the impacts of lake size and riverbank configuration on the accuracy of water level retrievals, the river Po in Italy to validate water level time series and discharge estimates, and also the River Rhine and Lake Constance to validate water level time series. Who are the End Users that have been or will be engaged? The project team includes key experts in the use of satellite data in coastal zone and inland water studies. External end-users are encouraged to access the data products to evaluate and implement them in their own applications. Solutions, outputs and products Publicly available outputs and products include: Detailed technical descriptions of the algorithms and processing schemes applied. Initial validation coastal zone and inland water Test Data Sets for selected regions, An improved Wet Troposphere Correction for the coastal zone and inland waters A final global coastal zone product, and a river discharge product for large and medium sized rivers. An impacts assessment report on the applications and benefits of these global products Educational and outreach material A final scientific roadmap provides recommendations for further development of processing algorithms, for further SAR and SARin altimeter missions, and priorities for further scientific research in the coastal zone and inland waters. Dependencies As well as altimeter data from Sentinel-3A and -3B, and from CryoSat, HYDROCOASTAL has used data from Sentinel-1 (river mask, coastline), Sentinel-2 (MSI) and Sentinel-3 (OLCI, SLSTR). What and where are the gaps in existing capability? Previous projects and initiatives, most recently the ESA SCOOP (http://www.satoc.eu/projects/SCOOP) and SHAPE projects (http://projects.alongtrack.com/shape) have worked separately to develop and implement improved processing schemes for inland water and coastal domains, but HYDROCOASTAL is the first project aiming to consider them together in synergy. The junction between the Coastal Zone and Inland Water provides a challenge to researchers as it represents a boundary between different science domains (hydrology and oceanography), and different satellite measurement regimes. It is also a region of high variability in small spatial and temporal scales, pushing to the limit the ability of satellite data in terms of sampling and providing accurate measurements. Tools, Services, Software, or Portals needed Websites and tools that will be used by HYDROCOASTAL include: Data and satellite information resources ESA Sentinels online: http://sentinel.esa.int Copernicus: http://www.copernicus.eu Cryosat Missions and Products: https://earth.esa.int/web/guest/missions/esa-operational-eo-missions/cryosat Inland Water data and information sites ESA River and Lake website: http://earth.esa.int/riverandlake/ HYDROWEB: http://www.legos.obs-mip.fr/fr/soa/hydrologie/hydroweb/ USDA Lake DB web site: http://www.pecad.fas.usda.gov/cropexplorer/global_reservoir/ TUM Database for Hydrological Time Series of Inland Waters (DAHITI): http://dahiti.dgfi.tum.de/en/ Related Project Websites SAMOSA: http://www.satoc.eu/projects/samosa/ CP4O: http://www.satoc.eu/projects/CP4O/ SCOOP: http://www.satoc.eu/projects/SCOOP/ CRUCIAL: http://research.ncl.ac.uk/crucial/ SHAPE: http://projects.alongtrack.com/shape/ RIDESAT: http://hydrology.irpi.cnr.it/projects/ridesat/ Other resources: ESA online SAR and SARIn altimetry Processing (registration needed): https://gpod.eo.esa.int Coastal Altimetry web site (for papers and presentations): http://www.coastalaltimetry.org OSTST web site (for papers and presentations): https://meetings.aviso.altimetry.fr What specific technical Tasks need to be done? There are four tasks to the project:- Scientific Review and Requirements Consolidation: Review the current state of the art in SAR and SARin altimeter data processing as applied to the coastal zone and to inland waters. Implementation and Validation: New processing algorithms were designed and implemented to generate Test Data Sets, which were then validated against models, in situ data and other satellite data sets. Selected algorithms were then used to generate global coastal zone and river discharge data sets. Impacts Assessment: The impact of these global products was assessed in a series of Case Studies. Outreach and Roadmap: Outreach material have been prepared and distributed to engage with the wider scientific community and provide recommendations for development of future missions and future research. Data sets Three data sets are available: HYDROCOASTAL Final Product: L2 along-track re-tracked product L3 inland water level time series L4 river discharge time series. HYDROCOASTAL Test Data Set: L2 along-track re-tracked product. HYDROCOASTAL CCN2 isardSAT coastal product. A readme file provides a more detailed description of these products, and a Product Specification Document describes the product contents and format |
| Hydrology Thematic Exploitation Platform | The Hydrology TEP offers:- a Community Platform: an open, collaborative and inclusive community where users can SHARE information, knowledge, algorithms, methods, tools, results, products, services.- a Service Platform: a portal providing LARGE [...] | ISARDSAT S.L. (ES) | Digital Platform Services | applications, platforms, water resources | The Hydrology TEP offers: – a Community Platform: an open, collaborative and inclusive community where users can SHARE information, knowledge, algorithms, methods, tools, results, products, services. – a Service Platform: a portal providing LARGE SCALE EO SERVICES and PRODUCTS customised for hydrology applications. Flood monitoring and small Water bodies mapping, Water quality and level, Hydrological models. – an Enhancing Platform: a workspace based on the Cloud where users can discover, access, PROCESS, UPLOAD, visualise, manipulate and compare data. |
| HyNutri: Sensing “Hidden Hunger” with Sentinel-2 and Hyperspectral | The project will perform an experimental campaign to investigate the potential of Sentinel-2 and PRISMA data to estimate and predict the concentration of different nutrients (K, P, Ca, Fe, Mg, Zn, N and S) in the final agricultural production. | UNIVERSITY OF TWENTE (NL) | Science | agriculture, permanently open call, science, Sentinel-2 | The project will perform an experimental campaign to investigate the potential of Sentinel-2 and PRISMA data to estimate and predict the concentration of different nutrients (K, P, Ca, Fe, Mg, Zn, N and S) in the final agricultural production. |
| HYPER-CROP – HYPER-RESOLUTION CROP YIELD ESTIMATES AND EXTREME EVENTS CROPS SHOCKS MONITORING BY INTEGRATING MULTIPLE SATELLITE DATA AND MONITORING | The project will develop an EO-service for Hyper-resolution crop yield estimates and extreme events crops shocks monitoring by integrating multiple SATellite data and modeling, able to support farmers precision agriculture.This will be based on [...] | UNIV PADOVA (IT) | Enterprise | agriculture, climate, enterprise, generic platform service, land surface, Sentinel-2 | The project will develop an EO-service for Hyper-resolution crop yield estimates and extreme events crops shocks monitoring by integrating multiple SATellite data and modeling, able to support farmers precision agriculture.This will be based on a dynamic calibration/validation system which takes advantage of the high spatial resolution (5-8m) of combined harvesters’ crop yield information. The system procedures will be substantially all based on available data from EO information and web-based available ground database, plus some specific ground data for models validation. EO data in the different bands from different sensors will be used in order to retrieve leaf area index (LAI) and land surface temperature (LST) information from Sentinel 2 at 10 m of spatial resolution and also from the Third-party missions LANDSAT data at 30 to 60-100 m. The procedure will use the high-resolution remote sensing data for driving different water-energy-crop models based on two hypotheses: parameters-saving vs complex physical representation both for crop dynamic and evapotranspiration modeling. Data assimilation procedures of EO data will be routinely implemented along the crop season with the objective of detecting and monitoring crop exposure to shocks due extreme events non-reproducible by the model alone which alter the canopy morphology and physiology, such as weather disasters (e.g. extreme heat or cold, water logging etc.), saline stress, plant diseases and insect pests. Leaf area index (LAI) and land surface temperature (LST) from multiple remote sensing data will be assimilated to improve both the crop evapotranspiration and growth dynamics. At the end of the crop season the modeled crop yield estimates will be calibrated / validated against ground yields maps from georeferenced combine harvesters, allowing producing hyper-resolution crop yield estimates and soil – vegetation parameters (5-8 m). The procedure will be integrated in a loop allowing to have hyper-resolution yields estimates between the different seasons. The proposed methodology will be applied in irrigated and not irrigated fields in the North of Italy over maize and winter wheat fields where combine harvester fleets have been operating for several years. Yield and quality data will be used for a dynamic calibrating procedure. Expected innovative products will respond to the call activity line “EO for a Resilient Society”, impacting directly on agricultural farmers and their associations in the case studies, but it will be immediately exportable to any area of the world where combine harvesters equipped with yield sensors and eventually quality sensors are used. Of course, the scientific community will gain new knowledge on the retrieval of hyper-resolution crop yields. In this way, the project will deliver: protocol for retrieving and using data collected by fleets of combine harvesters; i) a protocol for retrieving and using data collected by fleets of combine harvesters; ii) a tool for driving variable rate applications of water and fertilizers; iii) a tool for estimating the damages caused by shock events and the potential impact of climate change. Identified end-users: Veneto Agricoltura, the extension service of Veneto Regional Governament. Interreg Italy-Croatia project “SeCure” Representatives of Confagricoltura Veneto Representative of Claas Italia User representative can be contacted via the TO or project manager. |
| HyperBOOST | In situ bio-optical datasets are essential for the assessment of the uncertainties of satellite ocean colour measurements and derived products. This is especially critical in coastal waters (between 200m and 5km distance from the coastline), [...] | Plymouth Marine Laboratory (GB) | Science | biodiversity flagship, biodiversity science cluster, coastal processes, coastal zone, Ecosystems, marine environment, ocean health flagship, ocean science cluster, oceans, science | In situ bio-optical datasets are essential for the assessment of the uncertainties of satellite ocean colour measurements and derived products. This is especially critical in coastal waters (between 200m and 5km distance from the coastline), where land adjacency effects, complex atmospheric aerosol mixtures, high loads of optically active components in particular high concentration of chromophoric dissolved organic matter, and bottom reflectance effects contaminate the signal that reaches the satellite. Yet, extensive campaigns with unified sample collection and analysis protocols covering a wide range of optical and environmental conditions are rare in the literature. The Tara expedition (https://fondationtaraocean.org/en/home/) within the frame of the Traversing European Coastlines project (https://www.embl.org/about/info/trec/expedition/), offers in 2023-2024 the unique opportunity of an oceanographic survey from a unique platform, using the same set of protocols, instruments, and sample analysis, collocated with a rich biological dataset describing the microbiologic diversity in detail. This integrated profiling across environmental and man-made gradients of micro- and macroscopic life will enable the collection of a first of the kind, pan-European census of European coastal ecosystems. The Hyperspectral Bio-Optical Observations Sailing on Tara (HyperBOOST) project aims to extend the variables collected during the TREC integrated sampling by including bio-optical measurements relevant to present and future satellite ocean colour missions. The aims of this project are to: Provide validation data (in-situ hyperspectral radiometry, bio-optical, optically active components biogeochemical and biodiversity relevant data) in optically complex waters for several missions/products: S2, S3, Landsat8/9, PRISMA, ENMAP, PACE (stations during 2024) Provide a hyperspectral bio-optical characterization of European regional seas with a consistent set of instruments/measurement protocols Validate satellite products from different sources Preparation activities for ESA CHIME in coastal waters |
| HyperSpectral pre-operational data injection into Copernicus | The aim of this project is to develop and validate novel EO-based hyperspectral data generated by an unprecedented miniaturized hyperspectral sensor (HyperScout-2) employed in the ESA EO directorate small sat mission PhiSat-1. The processed data [...] | cosine Remote Sensing BV (NL) | AI4EO | AI4EO, hyperspectral, permanently open call | The aim of this project is to develop and validate novel EO-based hyperspectral data generated by an unprecedented miniaturized hyperspectral sensor (HyperScout-2) employed in the ESA EO directorate small sat mission PhiSat-1. The processed data output of this project will advance existing EO capabilities. The processing and the distribution of the data to the community will enable original advancements in open science practices. It will boost up leading-edge short term studies advancing key areas of Earth system science and maximizing the scientific impact of European EO assets. The data processed in this project will serve as primary applications the ones foreseen in FSSCAT and PhiSat-1 missions. Following the distribution, many other applications will be possible by users, e.g. flooding, fire prediction, detection and monitoring, Urban Heat Islands, vegetation and crop status, water quality, change detection, soil moisture. The overall goal of this project is to pre-process HyperScout 2 data from level 0 to level 1C, thus making them available for different non-space applications. The main objectives derived from this goal are listed below: OBJ-01: Define the L-1C product scheme. The L-1C product will be a georeferenced hyperspectral cube of TOA reflectances along with associated meta-data such as processing related information, mapping specifications, viewing angles, etc. Here, which specific metadata to be included will be decided along with the file format (e.g. HDF5) and organization of the final product. OBJ-02: Select and fine tune the most suitable processing chain. A processing chain will be selected among the ones currently employed at cosine for different projects, and will be fine tuned to the specific needs of the project. The data processing chain begins with a L-0 product and outputs a L-1C product which match the specifications defined from OBJ-01. OBJ-03: Develop methods to validate the quality of the product. A validation environment will be developed which quantifies the quality of the hyperspectral cubes geometrically, radiometrically and spectrally. The accuracy of the meta-data will also be assessed in the environment. OBJ-04: Process the selected L0 VNIR dataset and assess the quality of the final product. Using the environment developed for OBJ-04, the quality of the L-1C product will be assessed. OBJ-05: collect lessons learned and identify improvements for the data processing algorithms. |
| ICE SHEET MASS BALANCE INTERCOMPARISON EXERCISE PHASE III (IMBIE-3) | The Ice sheet Mass Balance Inter-comparison Exercise (IMBIE) was established in 2011 as a community effort to reconcile satellite measurements of ice sheet mass balance. The purpose of IMBIE is to reduce uncertainties in ice sheet mass balance [...] | UNIVERSITY OF LEEDS, SCHOOL OF EARTH AND ENVIRONMENT (GB) | climate, Glaciers and Ice Sheets, polar science cluster, science, sea surface topography | The Ice sheet Mass Balance Inter-comparison Exercise (IMBIE) was established in 2011 as a community effort to reconcile satellite measurements of ice sheet mass balance. The purpose of IMBIE is to reduce uncertainties in ice sheet mass balance estimation through community efforts, in order to reconcile different satellite-based measurements of ice sheet mass balance and help constrain future projections of sea level rise. IMBIE is an international collaboration between scientists, supported by European Space Agency (ESA) and the National Aeronautics and Space Administration (NASA), primarily as a contribution to the Intergovernmental Panel on Climate Change (IPCC), but also to provide critical information on global sea levels for a wide range of stakeholders. IMBIE has led to improved confidence in the measurement of ice sheet mass balance and the associated global sea-level contribution. The improvements were achieved through combination of ice sheet imbalance estimates developed from the independent satellite techniques of altimetry, gravimetry and the input-output method. Going forwards, IMBIE provides a framework for assessing ice sheet mass balance, and has an explicit aim to widen participation to enable the entire scientific community to become involved. The previous two phases led to a reduction in ice sheet mass balance uncertainties and showed a 6-fold increase in the rate of mass loss during the satellite era. In addition to continuing this exercise, the new phase of IMBIE includes new objectives designed to provide more robust and regular estimates of ice sheet mass balance and their contribution to global mean sea level rise. These new objectives are to: • Include data from new satellite missions including GRACE-FO and ICESAT-2 • Provide annual assessments of ice sheet mass balance • Partition changes into dynamics and surface mass balance processes • Produce regional assessments • Examine the remaining biases between the three geodetic techniques | |
| ICEFLOW: Short-term movements in the Cryosphere | UNIVERSITY OF OSLO (NO) | Science | cryosphere, living planet fellowship, polar science cluster, science | ||
| ICEYE SAR VIDEO | An activity to explore the potential of SAR Video for the Iceye x-band SAR constellation | ICEYE OY (FI) | Enterprise | SAR | An activity to explore the potential of SAR Video for the Iceye x-band SAR constellation |
| IMAGE COMPRESSION FOR REMOTE SENSING USING VECTOR-QUANTIZED AUTOENCODERS (CORSA) | Development of novel AI based clustering methods to support enhanced compression performance (time and information loss). The use of AI based methods to support the optimization of the compression and decompression process as well as enabling [...] | VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK VITO (BE) | Enterprise | permanently open call | Development of novel AI based clustering methods to support enhanced compression performance (time and information loss). The use of AI based methods to support the optimization of the compression and decompression process as well as enabling optimized feature extraction based on the lower volume compressed datasets. |
| IMITATE – Introducing Machine-learning Into Targeted Analysis for Terrestrial Ecosystems | The proposed IMITATE project aims to address the following questions:How well can machine learning methods emulate physical process-based land surface models, focused over Europe?Can explainable AI techniques provide new insights into process [...] | UNIVERSITY OF LEICESTER (GB) | Science | AI4EO, carbon cycle, carbon science cluster, Ecosystems, land surface, science | The proposed IMITATE project aims to address the following questions: How well can machine learning methods emulate physical process-based land surface models, focused over Europe? Can explainable AI techniques provide new insights into process understanding when combining land surface models and Earth Observation data Are the learnt relationships between the modeled inputs and outputs consistent with those from Earth Observation data? To do this the project will: produce land surface model simulations from the JULES ESM (Earth System Model) over Europe focusing on the carbon cycle develop, train and evaluate machine learning models (emulators) against the simulated land surface parameters use these emulators to investigate the complex emergent relationships and feedback to gain an increased understanding of the underlying Earth System processes and to test whether data from satellite-based essential climate variables (e.g. ESA-CCI) are consistent with the relationships learnt from the land surface models. produce an Emulated-GPP (gross primary productivity) data product based on EO data, using the relationships learnt from the land surface model. |
| Impact of COVID-19 on harvest of row crop | The project aims at determining changes in agricultural management patterns, particularly in crop harvest dates, as accurately as possible using Sentinel-1 radar data, and assessing whether linked to Covid-19. | VISTA GEOWISSENSCHAFTLICHE FERNERKUNDUNG GMBH (DE) | Science | agriculture, covid19, permanently open call, science, Sentinel-1 | The project aims at determining changes in agricultural management patterns, particularly in crop harvest dates, as accurately as possible using Sentinel-1 radar data, and assessing whether linked to Covid-19. |
| Impact of 3D Cloud Structures on the Atmospheric Trace Gas Products From UV-Vis Sounders (3DCATS) | In current atmospheric trace gas retrieval schemes exploiting UV-vis sounder data, clouds are treated in a simplistic way ignoring 3D structures and cloud shadows. In this activity, the impact of such cloud effects on trace gas products is [...] | NILU – NORWEGIAN INSTITUTE FOR AIR RESEARCH (NO) | Science | atmosphere, science | In current atmospheric trace gas retrieval schemes exploiting UV-vis sounder data, clouds are treated in a simplistic way ignoring 3D structures and cloud shadows. In this activity, the impact of such cloud effects on trace gas products is quantified, building on statistical analyses of cloud observational data and on 3D Monte Carlo radiative transfer simulations for typical cases. Improved handling of cloudy scenes and mitigation of related biases is explored and tested on real UV-vis observational data exploiting cloud signatures in collocated imager data. |
| Impact study of COVID-19 lockdown measures on air quality and climate (ICOVAC) | The global crisis due to the pandemic spread of the coronavirus COVID-19 that the humanity is facing since early 2020 led to unprecedented measures taken by different governments worldwide in order to limit as much as possible the number of [...] | BELGIAN INSTITUTE OF SPACE AERONOMY (BIRA-IASB) (BE) | Science | air quality, atmosphere science cluster, atmospheric chemistry, covid19, environmental impacts, health, public health | The global crisis due to the pandemic spread of the coronavirus COVID-19 that the humanity is facing since early 2020 led to unprecedented measures taken by different governments worldwide in order to limit as much as possible the number of impacted persons. Those measures include social distancing, banning of people gathering and travels, encouragement for teleworking, closings of schools, universities, restaurants, pubs and non-essential product shops, border closings,… All those measures have been implemented by the individual countries at different moments, depending mostly on the virus outbreak timing in each territory. Italy has been the first European country to be significantly impacted by the virus outbreak and to take lockdown measures in early March 2020. Most of the other European countries had to take similar decisions in the following weeks, almost all countries worldwide are impacted by the COVID-19. All those measures impact significantly the anthropogenic emissions in the atmosphere as they lead to a drastic drop in road and air traffic and a strong reduction of industrial activities in non-essential sectors. On the other hand, other sectors might face increased demands, like domestic heating for example. Satellite measurements of nitrogen dioxide (NO2) tropospheric columns are a direct proxy for anthropogenic emissions. A decrease of the TROPOMI NO2 tropospheric columns in different parts of the world (e.g. China, Po Valley, US) during the respective lockdown periods has been reported in many press articles lately. Besides NO2, other atmospheric species such as CO, glyoxal, CO2,… originate, at least partly, from anthropogenic activity and might be impacted by the taken COVID-19 measures. It will be investigated during this work whether a COVID-19 footprint can be detected in available satellite and ground-based data sets for a number of pollutants. We will attempt to assess the potential impact of the lockdown measures on air quality and climate by deriving updated NOx and CO emissions but also on climate with the analysis of satellite greenhouse gas data products, such as XCO2 columns and/or via the use of the NOx emissions as a proxy to derive fossil fuel CO2 emissions. |
| Impacts of PYROgenic aerosols on PLANKTON ecosystems (PYROPLANKTON) | Living Planet Fellowship research project carried out by Joan Llort. In recent years, exceptionally large wildfires have been recorded in Australia, California, the Mediterranean region, and the Arctic. While there exists an established [...] | Barcelona Supercomputing Centre (BSC) (ES) | Science | Aerosols, Biomass, climate, living planet fellowship, natural hazards and disaster risk, oceans, wildfires | Living Planet Fellowship research project carried out by Joan Llort. In recent years, exceptionally large wildfires have been recorded in Australia, California, the Mediterranean region, and the Arctic. While there exists an established research effort on how Climate Change is leading these megafires and on how they are affecting land ecosystems, recent observations show that wildfires can also perturb marine ecosystems. Biomass burning injects massive amounts of aerosols into the atmosphere that are rich in organic matter, nutrients, and trace metals. When these aerosols fall over the ocean, they enrich surface waters with nutrients potentially triggering the accumulation of the microscopic marine algae that supports marine life, the so-called phytoplankton. The fertilisation of phytoplankton by wildfires aerosols has been directly observed during the extreme 2019-20 fire season in Australia. These observations agree with previous modelling efforts on showing that fire activity might have immediate impacts on marine productivity, which are likely to increase with the current global trends in wildfires. The type, extension and consequences of these impacts are beyond our understanding as we have not yet defined which are the affected regions or which compounds are dissolved in seawater after the deposition of wildfire aerosols. This project, called Impacts of PYROgenic aerosols on PLANKTON ecosystems (PYROPLANKTON), will analyse the problem from three different perspectives: First, the spatial and temporal variability of biomass burning aerosols deposition and its impact on surface phytoplankton will be evaluated from a synoptic perspective thanks to an original combination of ocean colour (OC-CCI), global fire products (FireCCI and GFAS) and a state-of-the-art atmospheric reanalysis (CAMS). Secondly, we will conduct ground-breaking experiments with ash from wildfires across the world to provide the mechanistic and detailed understanding on how biomass burning aerosols perturb seawater’s chemical composition and its impacts on marine microorganisms. Thirdly, we will produce the first global estimate of the current and future impact of biomass burning aerosols on marine primary production and carbon export. The outputs of PYROPLANKTON will build a solid conceptual framework to inform the climate and ocean research communities and guide them to accurately simulate the full impact of wildfires in the Earth System. The project will face several ESA’s Living Planet challenges, following SOLAS recommendations on the necessity of closer interactions between remote-sensed data, field observations and modelling. |
| IMPALA | Methane is among the most important greenhouse gases in the Earth’s atmosphere, causing rapid global warming. A recent study indicates that tropical methane emissions explain a large fraction of the global atmospheric methane growth (Feng et [...] | KNMI (NL) | Applications | africa, air quality, atmosphere, atmosphere science cluster, atmospheric chemistry, Ecosystems, environmental impacts, science | Methane is among the most important greenhouse gases in the Earth’s atmosphere, causing rapid global warming. A recent study indicates that tropical methane emissions explain a large fraction of the global atmospheric methane growth (Feng et al., 2022). The relatively short lifetime of methane of about a decade makes methane emissions an attractive target of short-term climate change mitigation strategies. The sources of methane in Africa are quite diverse (e.g. gas/oil production and transport, wetlands, landfills, geological seepage, livestock and rice paddies) and the emissions of each of those sources are often poorly quantified. The determination of methane emissions is a main focus for African countries, as was recently shown by the signing of the Global Methane Pledge (following COP26) by 24 African countries. However, methane emissions reported to the UNFCCC bear large uncertainties (Deng et al., 2022). Those reported from Africa are based on only a few in situ observations, due to the lack of infrastructure and logistical hurdles in collecting emission data. There is a clear need to improve upon the current estimates, for which satellite observations are potentially very useful. Emissions of nitrogen oxides (NOx) from soils and hydrocarbon emissions from vegetation in the Tropics (biogenic volatile organic compounds, BVOC) contribute substantially to the global budget of these species. BVOCs are key drivers of tropospheric chemistry through their impacts on ozone, aerosols and the oxidising capacity of the atmosphere. However, large uncertainties reside in BVOC and soil NO emission estimates mostly due to the complex mechanisms driving the emissions and to the paucity of local observations. Since BVOC emissions are the dominant source of formaldehyde (HCHO) over African rainforests, spaceborne HCHO columns can be used to better quantify this source. Moreover, the use of satellite NO2 data provides valuable information on the spatial distribution and magnitude of the natural sources of NOx over Africa at an unprecedented spatial resolution. Within IMPALA, we will combine Sentinel-5p satellite data with state-of-the-art models and sophisticated inversion algorithms to estimate the emissions of methane as well as biogenic hydrocarbon and natural NOx emissions over Africa. Both qualitative and quantitative constraints on biosphere/atmosphere exchanges and anthropogenic emissions will be provided. This information is relevant not only for a better scientific understanding of climate forcing and biosphere-climate-air quality interactions, but also for local stakeholders and for environmental and agricultural agencies. IMPALA capitalises the long-term expertise of the consortium in emission estimation from space observations. |
| Improved Atmospheric Spectroscopy Databases | Enable better exploitation of ESA atmospheric satellite missions by the measurement/provision of improved spectroscopic reference data sets.This project includes two main activities: one on the generation of improved spectroscopy in the SWIR [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | atmosphere, science | Enable better exploitation of ESA atmospheric satellite missions by the measurement/provision of improved spectroscopic reference data sets.This project includes two main activities: one on the generation of improved spectroscopy in the SWIR (water vapour, methane and carbon dioxide) and in the UV band (sulfur dioxide) in preparation for the Sentinel 5 Precursor mission and one on the generation of a consistent ozone spectroscopy at different (UV and InfraRed) wavelength ranges. |
| IMPROVED SOIL MOISTURE RETRIEVAL USING MACHINE LEARNING (ISML) | Terrestrial land surfaces are characterised by strong heterogeneities of, among other variables, soil texture, orography, land cover, snow, or Soil Moisture (SM). SM is of broad scientific interest due to its role in the Earth system: It impacts [...] | ESTELLUS SAS (FR) | Science | climate, land surface, living planet fellowship, SMOS | Terrestrial land surfaces are characterised by strong heterogeneities of, among other variables, soil texture, orography, land cover, snow, or Soil Moisture (SM). SM is of broad scientific interest due to its role in the Earth system: It impacts the partitioning of the incoming water and energy over land and affects then the variability of the terrestrial water and energy cycle. SM is also of capital practical value for a wide range of applications from floods forecasting to agriculture and water management. The scientific community has made significant progress in estimating SM from satellite-based Earth Observations (EO). Harmonizing the SM retrievals from active and passive MW measurements from instruments that (i) operate at different wavelengths, polarisations and incidence angles; (ii) have diverging spatial, temporal and radiometric resolutions; and (iii) are hardly ever well collocated in space and time, is a true challenge. For a decade, ESA CCI SM project has released a Climate Data Record (CDR) of daily estimates at a 0.25° resolution, that relies on: 1) a physical-based inversion scheme to retrieve SM from passive MicroWave (MW), 2) a statistical retrieval for active MW, and 3) an a posteriori merging of these two products. Several sources of improvement can however to be investigated for the retrieval techniques: the synergy of the observations in the retrieval phase and the spatial downscaling based on the data fusion with other satellite observations. These improvements should help improve and generate long-term and high-resolution SM products in particular by exploiting innovative machine learning methods. In order to close the gap between Earth system research requirements and EO data, we therefore intend to investigate two topics: Improvement of the SM retrieval algorithm based on: an a priori merging of active and passive MW observations, and a machine learning method with a Localization strategy to better take into account local conditions. Spatial downscaling based on: a SM-related index, the data-fusion with other high-resolution observations such as SAR or thermal infrared data, and a deep learning image-based retrieval approach. We are now at a crossroad of opportunities: on the one hand, AI is becoming one of the most transformative technologies of the 21st century, while on the other hand, European EO capability is delivering a totally unique and comprehensive picture of the planet. This project intends to capitalize on this new context of satellite remote sensing for soil moisture. The overarching objective of the project is to investigate the feasibility to obtain a Machine-Learning (ML) advanced, high-resolution (1 km, daily, 2010-2022), and consistent Soil Moisture (SM) estimate, over the Euro-Mediterranean region. |
| INCREASING CROP WATER USE EFFICIENCY AT MULTIPLE SCALES USING SENTINEL EVAPOTRANSPIRATION (ET4FAO) | The ET4FAO project demonstrated the suitability of Copernicus data (Sentinel-2, Sentinel-3 and ERA-5) for accurate and consistent country-wide mapping of actual evapotranspiration (ET) at spatial resolutions ranging from 20 m to 300 m. This was [...] | DHI GRAS A/S (DK) | Sustainable Development | agriculture, Sentinel-2, Sentinel-3, water cycle and hydrology, water resources | The ET4FAO project demonstrated the suitability of Copernicus data (Sentinel-2, Sentinel-3 and ERA-5) for accurate and consistent country-wide mapping of actual evapotranspiration (ET) at spatial resolutions ranging from 20 m to 300 m. This was achieved through production of ET maps covering the whole of Tunisia and Lebanon for the year 2019. Validation across 6 field sites located in irrigated and rainfed agriculture resulted in mean bias of 0.3 mm/day. Food and Agriculture Organization (FAO) were engaged throughout the project as the product aligns with their long-term goals of providing earth-observation data for monitoring of Sustainable Development Goal 6 (Clean Water and Sanitation). https://www.mdpi.com/2072-4292/12/9/1433 – Paper from ESA Sen-ET project (precursor to ET4FAO) which describes the main methodology used in ET4FAO. All the Copernicus-based ET maps produced during the project for Lebanon and Tunisia are available from the project website. Clicking the (i) icon on the right panel opens a tab with description of the project and the products. |
| Independent Component Analysis of Satellite Radar Imagery for Volcanic Processes – IMRICA extension | Satellite Interferometric Synthetic Aperture Radar (InSAR) is a powerful Earth Observation tool for the analysis of subaerial volcanic deformation – a parameter that is critical both for monitoring hazardous volcanic systems and for [...] | UNIVERSITY OF LEEDS, SCHOOL OF EARTH AND ENVIRONMENT (GB) | Science | living planet fellowship, SAR, science, Sentinel-1 | Satellite Interferometric Synthetic Aperture Radar (InSAR) is a powerful Earth Observation tool for the analysis of subaerial volcanic deformation – a parameter that is critical both for monitoring hazardous volcanic systems and for understanding magma storage in the shallow crust. The long duration and consistent acquisition strategy of ESA’s Sentinel-1 mission as part of the Copernicus initiative will increase the volume of SAR imagery suitable for analyzing volcanic deformation by an order of magnitude, and change the way that we: (1) use SAR imagery to monitor active volcanoes (2) understand the variety of mechanisms that can result in measurable surface deformation. The primary outcome of my ESA Living Planet fellowship is a demonstration of the application of Independent Component Analysis (ICA) to analyzing volcanic signals (Ebmeier, 2016). This provided a novel, robust method for distinguishing between independent and causally related deformation. My synthesis of global InSAR measurements of volcano deformation (Ebmeier et al., 2018) provides insight into the lateral extent and complexity of zones of magma storage beneath volcanoes. In the extension to my fellowship research (2018-19), myself and two PhD students use SAR imagery to (1) investigate the potential for processes internal to a magma reservoir to generate deformation signals [Eoin Reddin, PhD 2018 onwards] and (2) demonstrate the capabilities of SAR backscatter for detecting eruption dynamics [Edna Dualeh, PhD 2017 onwards]. Selected Related Publications: Ebmeier, S.K. (2016). Application of independent component analysis to multitemporal InSAR data with volcanic case studies. Journal of Geophysical Research – Solid Earth, 121, 12, 8970– 8986, doi:10.1002/2016JB013765 Ebmeier SK; Elliott JR; Nocquet JM; Biggs J; Mothes P; Jarrín P; Yépez M; Aguaiza S; Lundgren P; Samsonov SV (2016) Shallow earthquake inhibits unrest near Chiles-Cerro Negro volcanoes, Ecuador-Colombian border, Earth and Planetary Science Letters, 450, pp.283-291. doi: 10.1016/j.epsl.2016.06.046 Ebmeier, S.K., Andrews, B.J., Araya, M.C., Arnold, D.W.D., Biggs, J., Cooper, C., Cottrell, E., Furtney, M., Hickey, J., Jay, J.J.J.A.V. and Lloyd, R., 2018. Synthesis of global satellite observations of magmatic and volcanic deformation: implications for volcano monitoring & the lateral extent of magmatic domains. Journal of Applied Volcanology, 7(1), p.2. |
| Infrastructure mapping and planning (EO4Infrastructures) | Infrastructures refer to the fundamental facilities and systems serving a country, city, or other area, including the services and facilities necessary for its economy to function e.g. public and private physical assets such as roads, bridges, [...] | E-GEOS (IT) | Applications | applications, mapping/cartography | Infrastructures refer to the fundamental facilities and systems serving a country, city, or other area, including the services and facilities necessary for its economy to function e.g. public and private physical assets such as roads, bridges, railways, harbors, pipelines, airports, tunnels, etc. In order to insure their proper functioning, infrastructures together with their close neighborhood environment continuously need to be monitored for changes such as physical damages caused by e.g. aging, weathering, quakes, subsidence and flooding. In this context, Earth Observation (EO) represents an opportunity for innovative research, applications and information services not only to support the planning of new infrastructure but also to support its continued monitoring. Nowadays, we are entering into a new era for EO science and applications driven by the continuously increasing observation capacity offered by the EU Sentinel missions, the opportunities for science offered by the ESA Earth Explorer missions and the capabilities to look at the past offered by the existing long-term EO data archives. Furthermore, a variety of national and commercial EO missions with unique capabilities especially in the domain of very high-resolution deliver highly valuable information on our urban environments and infrastructures. At the same time, it is clear that for a complete exploitation of the EO Services necessary to satisfy the needs of the industry and public sector, dedicated development efforts are required. This project gives exactly the opportunity to contribute to the reduction of the existing gaps in the infrastructure management sector by demonstrating that EO data, combined with in-situ data as well as other EO derived products e.g. the ones produced by the Copernicus Land Monitoring Service (CLMS) can provide a real benefit to End Users. For this reason, the study-logic proposed in the project is fully User-Requirement driven. The study-logic can be summarized in the following phases: User needs collection and assessment, to understand the effective user needs and consolidate the requirements in a robust and shared structure to be used for the definition of the requirement baseline. Technical specifications definition, based on the consolidated requirement baseline, to provide a clear and unambiguous technical description of all the EO products and systems needed to support the user needs. Validation and Demonstration, to critically evaluate the identified solutions in real-life use cases relevant for the End Users. For this reason, End Users are key-actors not only in the “User needs collection and assessment” but also during the part of the project. |
| Innovator supporting developing countries in cloud based forest monitoring for REDD+ | A range of EO based prototype capabilities have been developed and tested in relation to the implementation of REDD+. With the launch of Sentinel-1A/B and Sentinel-2A/B, a new era of frequent coverage of the earth surface by high resolution [...] | GAF AG (DE) | Sustainable Development | forestry, permanently open call | A range of EO based prototype capabilities have been developed and tested in relation to the implementation of REDD+. With the launch of Sentinel-1A/B and Sentinel-2A/B, a new era of frequent coverage of the earth surface by high resolution (HR) satellite imagery was initiated. Together with the Landsat and other satellite missions, it is now possible to build up dense time series with sufficient spectral and geometrical resolution which allow new analysis methods for improved forest and land cover mapping. The application of dense time series of Sentinel and the HR data provides the possibility to overcome mapping inaccuracies caused by seasonal changes of forest cover (leaf fall in dry season), to compensate data gaps caused by cloud coverage, to improve the analysis of human induced changes and to make an early detection of deforestation and forest degradation events possible. However, the data volumes of dense time series data stacks from Sentinel and other satellite systems are, compared with traditional processing methods (mono- and bi-temporal analysis), tremendously increasing and therefore require a sophisticated IT infrastructure to compute wall-to-wall land cover maps. It has been proven more efficient for the European Service Providers to make use of cloud processing options instead of purchasing, maintaining and constantly upgrading existing IT infrastructure. On the other side, the handling of huge data volumes and the application of complex processing algorithms pose an enormous infrastructure and capacity challenge for developing countries. Thus, technology transfer and capacity building are major pillars of development cooperation programmes but however, the status of having up-to-date hardware and software is almost always lacking behind the requirements of a fast developing technology. Therefore, working on cloud-based processing chains will be an opportunity for improved technology transfer and capacity building to developing countries. The overall goal of the current project is to enable Stakeholders and Users from developing countries to create sophisticated applications for forest monitoring and assessment within an innovative cloud-based Front Office which unifies the Big Data functionalities of the C-DIAS back storage with already verified processing algorithms for tropical dry forest mapping. In particular the project outcomes are expected to be provision to Users from developing countries of improved access and processing methods for cloud based forest monitoring, based on Sentinel-2 data, a web based Graphical User Interface (GUI) to select, pre-process and classify Sentinel-2 data and capacity building activities related to testing, validation and training on the developed system. |
| InSAR Services for Key Hungarian Market Sectors | This activity is the continuation of an previously-completed ESA project ("PASTA: Phenomena-Aware Spatial and TemporAl Clustering"). The overall objective is to develop a software tool providing higher-level solutions for automated [...] | DATelite (HU) | Enterprise | SAR, solid earth | This activity is the continuation of an previously-completed ESA project (“PASTA: Phenomena-Aware Spatial and TemporAl Clustering”). The overall objective is to develop a software tool providing higher-level solutions for automated interferometric data analysis and interpretation, geared mainly to key Hungarian users. The precursor project had successfully performed the user consultations and defined a number of demonstration pilots, each with its own user requirements. Four pilots with their own user requirements are planned, one for each of the following end-users: 1) the Baranya County Directorate for Disaster Management (BMKV); 2) LAFARGE Cement Hungary Ltd.; 3) Nuclear Waste Management Plc. (RHK) and 4) Mining Property Utilization Ltd. (BVH). These entities show continued interest to learn about and possibly adopt SAR interferometry in their respective activities. |
| Integrated Remote Sensing for Biodiversity-Ecosystems Function – IRS4BEF | The combination of information provided by different optical and thermal spaceborne imagers can give complementary information about vegetation plant biodiversity and ecosystem functions to understand their links (BEF relationships) better. [...] | MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY (DE) | Science | biodiversity science cluster, ecosystems/vegetation, living planet fellowship | The combination of information provided by different optical and thermal spaceborne imagers can give complementary information about vegetation plant biodiversity and ecosystem functions to understand their links (BEF relationships) better. However, how integrating multi-mission information in this context remains unclear. Therefore, IRS4BEF wants to solve relevant methodological questions regarding the integration and analysis of these data. IRS4BEF seeks to: understand how multi-mission data in the optical and thermal domains can be integrated to provide enhanced estimates of plant functional diversity that are linked to ecosystem functions and their responses to the environment, considering the added value of the different missions. determining the optimal approaches to integrate remote biodiversity estimates with ecosystem function responses to the environment as measured in eddy covariance stations to assess and monitor BEF relationships. Climate change and human activities jeopardize ecosystems’ biodiversity, functions, and services. Ecological studies suggest that biodiversity plays an important role in maintaining ecosystem function and stability in response to climate variability and extreme events (BEF relationships). Thus, knowing and exploiting BEF relationships is necessary to understand better how to maintain ecosystem services under the current decline in biodiversity. However, the lack of cost-effective, synoptic, and global biodiversity monitoring systems compromises the adequate implementation of conservation programs and understanding BEF relationships. Remote sensing (RS) is advancing in studying different facets of plant biodiversity and has emerged as a potential biodiversity monitoring tool. It can capture signals linked with vegetation properties (i.e., plant traits) that govern ecosystems’ functions and responses to the environment and signals directly related to such functions (thermal radiation, photochemical reflectance index (PRI), or sun-induced chlorophyll fluorescence (SIF)). At the same time, the spatial variability of these signals relates to the variability of vegetation functional properties. However, it is unclear how to exploit this multi-source information to assess biodiversity and BEF relationships. For example, which missions should be combined? And how? IRS4BEF seeks to determine which multi-mission integration methods optimize the characterization of plant functional diversity for analyzing and monitoring BEF relationships from space. |
| Integrating AI/ML Capabilities for Geohazards and Urban Management Applications | The primary objective of this project is to augment the capabilities of Ellip-powered Exploitation platforms, specifically Geohazards Exploitation Platform (GEP) and Urban Thematic Exploitation Platform (U-TEP), by seamlessly integrating an [...] | TERRADUE SRL (IT) | Digital Platform Services | AI4EO, analytics, platforms, thematic exploitation platform | The primary objective of this project is to augment the capabilities of Ellip-powered Exploitation platforms, specifically Geohazards Exploitation Platform (GEP) and Urban Thematic Exploitation Platform (U-TEP), by seamlessly integrating an AI/ML processing framework. This comprehensive framework will encompass the entire machine learning pipeline, including data discovery, access to training data, model development and deployment. GEP and U-TEP are both platforms that are designed to support the exploitation of satellite Earth Observation (EO) data in their respective thematic areas, geohazards and urban management, catering to diverse user communities such as researchers, policymakers, and planners: GEP is designed to support the exploitation of satellite Earth Observations for geohazards, focusing on mapping hazard-prone land surfaces and monitoring terrain deformation. With more than 25 services for monitoring terrain motion and critical infrastructures, GEP has over 2950 registered users, with 350+ actively creating new content. U-TEP aims to provide end-to-end and ready-to-use solutions for a broad spectrum of users to extract unique information and indicators required for urban management and sustainability. It focuses on bridging the gap between the mass data streams and archives of various satellite missions and the information needs of users involved in urban and environmental science, planning, and policy. Both platforms offer various services, including data access, processing, analytics, and visualization, while providing tools and resources for customized applications. They leverage cloud-based infrastructure to handle large volumes of EO data efficiently and offer seamless access to their services. A critical aspect of this project will be the integration of MLOps processes into both GEP and U-TEP platforms’ service offerings. MLOps, which combines machine learning, DevOps, and data engineering practices, will facilitate seamless deployment, monitoring, and management of AI/ML models, ensuring the smooth operation of AI-driven applications on the platforms. To achieve the project’s goals, the focus will be on addressing key questions related to necessary services, interface requirements, component interactions, support for various geospatial data types, and algorithm independence. Several approaches will be considered to tackle these challenges, such as managing training data, implementing “move-the-algorithm-to-the-data” principles, emphasizing transparency and accountability, and enabling testing and deployment of ML algorithms on fully-scaled infrastructures. Upon successful completion, the project will result in the enhancement of both GEP and Urban TEP platforms and their service offerings. The addition of AI/ML capabilities will empower service providers to develop and deploy AI/ML models, ultimately improving their services and delivering added value to their customers. This enhancement will greatly benefit the GEP and Urban TEP platforms by expanding their capabilities and enabling new AI-driven applications for geohazards and urban management. |
| INTENS – Characterization of IoNospheric TurbulENce level by Swarm constellation | The purpose of the project is to investigate the turbulent nature of geomagnetic field and plasma parameters (electron density and temperature) in the ionosphere as recorded by the Swarm constellation during a period of 4 years (from 1 April [...] | ISTITUTO NAZIONALE DI GEOFISICA E VULCANOLOGIA (IT) | Science | ionosphere and magnetosphere, permanently open call, science | The purpose of the project is to investigate the turbulent nature of geomagnetic field and plasma parameters (electron density and temperature) in the ionosphere as recorded by the Swarm constellation during a period of 4 years (from 1 April 2014 to 31 March 2018). Specifically, fluctuations of these quantities, as well as their scaling features, will be thoroughly investigated during different geomagnetic disturbance conditions to shed light on the role played by the magnetohydrodynamic turbulence in creating multi-scale plasma structures and inhomogeneties in the ionospheric environment at different latitudes. Focused analyses of the parameters recorded by the Swarm constellation are expected to provide a reliable characterisation of the nature and level of the ionospheric turbulence on a local scale, which can be displayed either along a single satellite orbit or through maps over the region of interest. The same parameters can be used also to study space-climatological variations of scaling features of the geomagnetic field and ionospheric plasma according to different interplanetary magnetic field orientations. Swarm measurements will give the opportunity to get a precise characterization of the different ionospheric turbulence regimes of the medium crossed by satellites on scales from hundreds of kilometres to a few kilometres, when considering low resolution data, and from tens of kilometres to a few meters, when considering data at the highest resolution. Ground-based observations from the SuperDARN network at high latitudes and the ENIGMA array at low-middle latitudes will complement Swarm data. The obtained results will be interpreted in the light of previously theoretical, numerical and observational published works. The analysis performed at high latitudes in both hemispheres will allow, for instance, a thorough investigation of the North-South asymmetries, while the analysis at mid and low latitudes will improve our understanding about the impact of magnetospheric ring current variations on the ionospheric plasma at Swarm altitudes. The investigation proposed in the framework of the project is an example of the excellent capability of Swarm data to provide new insights on the ionosphere-magnetosphere coupling. |
| Interactive Hosted EO Processing | The project demonstrated, through a proof-of-concept, that merging the concept of hosted EO data processing with GPUs (Graphics Processing Unit) and Web technologies, a solution could be created to allows users to easily exploit data in a fast [...] | BRITISH ANTARCTIC SURVEY (GB) | Digital Platform Services | platforms | The project demonstrated, through a proof-of-concept, that merging the concept of hosted EO data processing with GPUs (Graphics Processing Unit) and Web technologies, a solution could be created to allows users to easily exploit data in a fast interactive manner via a web browser. The PoC used InSAR for demonstration with very good results, the user just having to select the AoI and the algorithm and after some seconds having a InSAR output image. |
| Introducing physics to artificial intelligence methods to improve satellite monitoring of the water cycle | The project aims to develop, train, and apply a hybrid neural network model to optimise EO data for a coherent, balanced water cycle at the global scale resulting in a new pixel-resolution datasets for the four water cycle components: [...] | ESTELLUS SAS (FR) | Science | AI4EO, hydrology science cluster, permanently open call, water cycle and hydrology | The project aims to develop, train, and apply a hybrid neural network model to optimise EO data for a coherent, balanced water cycle at the global scale resulting in a new pixel-resolution datasets for the four water cycle components: precipitation, evapotranspiration, change in water storage, and runoff (or river discharge). These data will cover the entire globe on quarter-degree grid cells and on a monthly time scale. |
| INVESTIGATING LIGHTNING GENERATED ELF WHISTLERS TO IMPROVE IONOSPHERIC MODELS (ILGEW) | Some of the strongest lightning discharges occurring at the Earth surface generate short electromagnetic signals that can propagate at very large distances both at the surface of the planet and in space. During a lightning discharge, the whole [...] | INST PHYSIQUE GLOBE (FR) | Science | atmosphere, ionosphere and magnetosphere, science | Some of the strongest lightning discharges occurring at the Earth surface generate short electromagnetic signals that can propagate at very large distances both at the surface of the planet and in space. During a lightning discharge, the whole electromagnetic spectrum is excited, from radio frequencies to the visible and beyond. The conditions of the atmosphere and the ionosphere crossed by this signal affect its propagation differently in the different electromagnetic frequency bands. More specifically, when the lightning signal crosses the boundary between the neutral atmosphere and the ionosphere, at about 90 km height, the lower frequencies are spread in time due to the interactions with the electrons and ions present in the ionosphere. This phenomenon is called dispersion. It occurs because the charged particles of the ionosphere are bound to the Earth’s magnetic field lines and this induces changes in the direction and speed of signal propagation. When the lightning signal reaches a satellite at low orbital altitude, it is recorded as a whistler, a gliding signal that can be translated into a sound resembling to a whistle. ILGEW project (May 2019 – September 2020) intends to study these whistlers and improve the scientific returns of the ESA Earth Explorer Swarm mission that measures the Earth magnetic field using a constellation of three satellites. Whistler events can be recorded by the Swarm’s Absolute Scalar Magnetometer (ASM) only when the acquisition rate of the measurements of the magnetic field intensity is raised from the nominal 1 Hz to a burst-mode at 250 Hz. This allows the investigation of part of the Extremely Low Frequency (ELF) band where whistlers can be received and studied between 20 and 125 Hz. This part of the electromagnetic spectrum has not yet been systematically studied from space and it still presents many challenges for a complete understanding of the ground-ionosphere interactions. Specific burst-mode measurement campaigns are conducted during the development of ILGEW project, taking advantage of the specific orbital characteristics of Swarm satellites drifting slowly in local time, to explore whistler characteristics under different geophysical conditions. Whistlers received by Swarm satellites can be characterised by their dispersion, a measure of the relation between the signal frequency and its propagation time inside the ionosphere. The state of the ionosphere at the time of this event is a key parameter to determine the whistler’s dispersion: day/night conditions, low/high solar activity, all contribute to the variability of the dispersion. As a general indication, the more charged particles are present along the propagation path, the higher will be the whistler’s dispersion.Scientific objectives ILGEW project has three main scientific objectives: 1. Characterize the whistler dispersion measured from Earth low orbital altitudes, in order to analyse the ionosphere below Swarm satellites, along the propagation path of the whistlers. 2. Constrain the lightning activity that lead to favourable propagation conditions for the generation of detectable ELF whistlers at Swarm altitudes. 3. Establish the benefits that can be obtained for ionospheric models such as the International Reference Ionosphere (IRI) by using the information obtained from whistler’s characteristics. |
| INVESTIGATION OF SENTINEL-1 POTENTIAL IN EFFECTIVE, SUSTAINABLE AND SAFE DEVELOPMENT AND MANAGEMENT OF GEOTHERMAL RESOURCES | Development and verification of the combination of PS and SBAS based InSAR methods to characterize land surface motion and infer sub-surface geothermal process parameters. Integration of InSAR methods and subsurface lithological characterization [...] | Geo-Sentinel Ltd (HU) | Enterprise | land surface, Sentinel-1 | Development and verification of the combination of PS and SBAS based InSAR methods to characterize land surface motion and infer sub-surface geothermal process parameters. Integration of InSAR methods and subsurface lithological characterization to improve the estimation of geothermal process parameters. |
| IRIX4US: Super-Resolution Algorithm IRIX4 Applied to Urban Settlements | The perimeter that delimits a building or vertical structure in urban areas is called a Building Footprint (BF). BFs are often produced by photointerpretation and digitalisation of remote sensing images and are often used to feed advanced [...] | COTESA – Centro de Observación y Teledetección Espacial (ES) | The perimeter that delimits a building or vertical structure in urban areas is called a Building Footprint (BF). BFs are often produced by photointerpretation and digitalisation of remote sensing images and are often used to feed advanced Artificial Intelligence models. Nowadays, BFs are automatically extracted from remotely sensed images using Deep Learning (DL) algorithms. These algorithms depend on the spatial resolution of the input image, because that the higher it is, the higher accuracy values the algorithm can reach. However, more often than not, these images are not available frequently and at regular intervals, even when provided by commercial operators. The satellites available in the Copernicus Program, especially the Sentinel-2 constellation, provide free and open images with a high temporal resolution, at a 5 day-revisit interval. This is potentially a valuable resource that allows city governments and stakeholders to study the urban dynamics. However, these images usually do not have the spatial detail needed for BF extraction. The present project aims to perform a wall-to-wall study of urban dynamics by developing a pipeline integrating three state-of-the-art technologies: Implementing a validated Deep Learning model to downscale (super-resolve) Sentinel-2 images 4 times, named “IRIX4 Super Resolution algorithm”, preserving spectral characteristics while enhancing the spatial resolution. Perform an exhaustive BF extraction from super-resolved Sentinel-2 images, based on advanced DL techniques and segmentation procedures. Automate change detection processes over selected urban areas between the years 2020 and 2023 with the use of ad-hoc models. Pilot areas and final scope of algorithms will be set according to the needs of key stakeholders at different scales and data governance. | ||
| Irrigation+ | The project aims at advancing capabilities towards a quantitative, accurate and routine estimation of irrigation information by means of multi-mission satellite EO approaches: Irrigation mapping, quantifying the irrigation amount and detecting [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | agriculture, hydrology science cluster, science, Sentinel-1 | The project aims at advancing capabilities towards a quantitative, accurate and routine estimation of irrigation information by means of multi-mission satellite EO approaches: Irrigation mapping, quantifying the irrigation amount and detecting the seasonal timing of irrigation. |
| Island2VAP: Integrating Sentinel-2 and Landsat-8 to Systematically Generate Value-Added Products at High Resolution | Quality and quantity of current high resolution optical earth observation data is unprecedented and provides an opportunity to advance remote sensing land system analyses. However, cloud coverage and a lack of gridded higher level products still [...] | HUMBOLDT UNIVERSITAT ZU BERLIN (DE) | Science | land, science | Quality and quantity of current high resolution optical earth observation data is unprecedented and provides an opportunity to advance remote sensing land system analyses. However, cloud coverage and a lack of gridded higher level products still hampers the widespread usability of the data. This research addresses these shortcomings by developing toolsets to combine data streams from Sentinel-2 and Landsat-8 and that allow for the systematic (i.e. weekly, monthly, seasonal-) generation of composited reflectance and subsequently value-added products (e.g. percent cover estimates, annual phenology metrics). This suite of generated products will be synergetically exploited in order to address higher level land-use science questions that cannot readily be answered using spectral data only. While methods are developed to be capable of working with most ecosystems, a specific focus is on improving agricultural mapping and analyses. |
| JOule heating effects on Ionosphere-thermosphere coupling and Neutral density (JOIN) | Understanding the detailed spatial and temporal dynamics of the space environment is a key task in solar-terrestrial research. This is also a fundamental requisite for providing successful space weather forecasts, such as predicting changes in [...] | UNIVERSITY OF OULU (FI) | Science | GRACE, ionosphere and magnetosphere, solid earth, swarm | Understanding the detailed spatial and temporal dynamics of the space environment is a key task in solar-terrestrial research. This is also a fundamental requisite for providing successful space weather forecasts, such as predicting changes in atmospheric drag experienced by satellites at low-Earth orbits (LEO). The high-latitude auroral ionosphere is connected by magnetic field lines to a large part of the magnetospheric volume, making it a “focus area” of magnetospheric dynamics. Consequently, space weather disturbances are also most strongly manifested at high latitudes. The ionospheric and magnetospheric current systems are coupled (MI-coupling) by field-aligned currents (FAC) flowing along the geomagnetic field. The energy needed to sustain the current systems comes from the continuous interaction of the solar wind with the Earth’s magnetic field. Large part of that energy is dissipated in the auroral ionosphere as Joule heating, which among other things leads to changes in the thermospheric wind patterns and increased satellite drag via thermal expansion of the gas. In the project, the team proposes to make a detailed investigation of the auroral Joule heating and its consequences on the ionosphere-thermosphere (IT) system at high latitudes. The main objectives or Science Cases are to: Determine the global statistical distribution and variability of the high-latitude Joule heating during geomagnetic storms. Correlate the storm-time Joule heating with observed large-scale atmospheric density variations. Study and characterize the atmospheric scale height by directly comparing simultaneous and co-planar density measurements from two different altitudes during different solar and geomagnetic conditions. Perform event studies of meso-scale density variations at auroral regions by utilizing Swarm – EISCAT conjunctions. Together, these Science Cases will reach multiple science objectives mentioned under Theme 3 in the SoW. The project will characterize the coupling between the different layers of the ionosphere and the thermosphere during different levels of geomagnetic activity and in different phases of the solar cycle. Neutral density variations due to Joule heating and energy transfers during geomagnetic storms will be investigated in detail, taking into account the different interplanetary drivers behind the storms. The unique opportunities offered by the co-planarity periods (i.e., two satellites at different altitudes in nearly the same orbital plane) between the Swarm, GRACE and GRACE-FO missions will be utilized to probe the vertical variations in the thermospheric structure and composition. Conjunctions between the Swarm spacecrafts and the EISCAT incoherent scatter radars give the spatial and temporal resolution required for investigating the ionosphere-thermosphere coupling in a multi-satellite and multi-source context. |
| KARLOS | Air pollution is one of the current major environmental issues affecting human health at the global scale, therefore monitoring air pollution in urban and suburban areas is of great societal importance. The monitoring of air quality at urban [...] | LUFTBLICK OG (AT) | Science | air quality, atmosphere, atmosphere science cluster, atmospheric chemistry, public health | Air pollution is one of the current major environmental issues affecting human health at the global scale, therefore monitoring air pollution in urban and suburban areas is of great societal importance. The monitoring of air quality at urban scales is currently based on telemetric in-situ networks, which provide continuous observations with high accuracy of a number of relevant air pollutants but have limited representativeness due to the relatively small number of measurement sites. Air quality satellite observations has resolution values good enough to resolve the spatial and temporal variability of trace gases such as NO2 over regions of the world without sources, e.g. the oceans. However they fail in capturing the variability over most landmasses, especially over urban and complex (e.g.mountainous) terrains. Ground-based imaging DOAS in downward looking mode can represent a step forward for air quality monitoring in terms of spatial and temporal resolution but is rather seldom simply for the fact that a significantly elevated platform is needed for this purpose. Such a unique situation is present in Innsbruck with the Hafelekar station located at about 1800m above the city with little horizontal distance. The KARLOS (HafeleKAR Line Of Sight AQ monitoring) project aims to develop a mountain top imaging DOAS overlooking the city of Innsbruck with the following purposes: Demonstrate the capabilities and test the performance of the prototype Monitor the air quality in and around Innsbruck at high temporal and spatial resolution Assess the options for a high resolution air quality retrieval system combining measurements and model calculations |
| L-band Observations of Soil and Trees in Freezing/Thawing Conditions – LOSTinFTC | Living Planet Fellowship research project carried out by Anna Kontu. Passive microwave observations at L-band (1.4 GHz) can detect soil freeze/thaw status based on the differences in the electrical properties of ice and liquid water. This [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | forestry, living planet fellowship, snow and ice, water cycle and hydrology | Living Planet Fellowship research project carried out by Anna Kontu. Passive microwave observations at L-band (1.4 GHz) can detect soil freeze/thaw status based on the differences in the electrical properties of ice and liquid water. This method is suitable for detecting autumn freezing, but during spring thawing the liquid water in melting snow confounds the signal from soil; however, the penetration depth of electromagnetic waves at L-band may allow limited retrieval of information from subnivean soils even in snowmelt conditions. Another source of inaccuracy in present F/T retrievals is the liquid water in trees; while the water in soil mostly freezes when the soil temperature drops below 0 °C, the water in trees can stay in liquid form down to -40 °C. The amount of liquid water and ice in trees affects the transmissivity of forests and hence the transmissivity of forests is dependent on temperature. Finnish Meteorological Institute’s Arctic Space Centre (FMI-ARC) in Sodankylä, Finland, hosts a measurement setup, including two ESA ELBARA-II L-band radiometers, which could be used to study both the transmissivity of boreal coniferous forest and detection of soil thawing when snow is melting. The existing infrastructure allows for measurements from above and below the forest, and reference measurements monitor soil, snow and vegetation properties, including snow wetness and tree dielectric permittivity, among other parameters. This project aims to develop a model for boreal forest transmissivity dependence on temperature and to study possibilities for detecting soil thawing during spring snowmelt. |
| L2A-RUT | Living Planet Fellowship research project carried out by Javier Gorroño. In the last decade, some missions started to offer operational Level-1 (L1) uncertainty estimates for top-of-atmosphere (TOA) radiance/reflectance factor. Among them, [...] | UNIVERSITAT POLITÈCNICA DE VALÈNCIA (ES) | Science | living planet fellowship, science | Living Planet Fellowship research project carried out by Javier Gorroño. In the last decade, some missions started to offer operational Level-1 (L1) uncertainty estimates for top-of-atmosphere (TOA) radiance/reflectance factor. Among them, the Sentinel-2 (S2) mission delivers uncertainty products associated to the L1C products using the Radiometric Uncertainty Tool (RUT). The delivery of uncertainty products represents an important milestone that requires consecutive efforts so that further processing levels can also offer these uncertainty estimates. Consequently, the following phase of study involves the development of uncertainty estimates associated to the S2 L2A products (i.e. surface reflectance). The uncertainty analysis involves the propagation of the L1C TOA reflectance factor through the atmosphere as well as the uncertainty over the atmospheric correction itself. The study focuses on a mathematical expression of the atmospheric correction of the operational S2 L2A products using the Sen2Cor processor. From this mathematical expression, an analytical expression of the uncertainty can be defined consisting of: a Jacobian of sensitivity coefficients, a correlation matrix and an uncertainty contribution matrix. In order to derive robust uncertainty estimates, the analytical expression of the uncertainty will be validated against a Monte-Carlo approach. Special attention will be given to the auxiliary retrievals such as Aerosol Optical Thickness (AOT) and Water Vapour (WV) in Sen2Cor processor. In parallel to the uncertainty analysis, its software implementation will be developed to improve the current RUT tool in order to deliver both S2 L1C and L2A uncertainty estimates. The implementation will explore memory/processing time optimisation approaches such as the integration of the RUT as part of Sen2Cor processor. Among other applications, the delivery of S2 L2A operational uncertainty products can be helpful to provide better quality metrics for end applications such as agricultural monitoring, a better definition of prior conditions in retrieval processes or the support of Earth Observation (EO) products conformance tests. |
| L2A+ | ESA wind mission Aeolus hosts the first space-based Doppler Wind Lidar (DWL) world-wide. Its scientific objectives are to improve Numerical Weather Predictions (NWP) and to advance the understanding of atmospheric dynamics and its interaction [...] | NATIONAL OBSERVATORY OF ATHENS (GR) | Science | Aeolus, Aeolus+ Innovation, atmosphere, atmosphere science cluster, atmospheric winds | ESA wind mission Aeolus hosts the first space-based Doppler Wind Lidar (DWL) world-wide. Its scientific objectives are to improve Numerical Weather Predictions (NWP) and to advance the understanding of atmospheric dynamics and its interaction with the atmospheric energy and water cycle. The primary data product is profiles of horizontally projected line-of-sight winds from the surface up to about 30 km, and spin-off products are profiles of cloud and aerosol optical properties. While the L2A product has a reasonable quality, its full potential for aerosol and cloud studies and for further improving NWP, has not been exploited. This is mainly because L2A is not provided separately for aerosol and cloud targets. The proposed L2A+ study aims at developing a refined Aeolus L2A aerosol product (L2A+), test its application for enhancing aerosol research and aims at assessing the impact of the new product on aerosol assimilation towards improved dust transport modelling and for further enhancing NWP. This overarching goal of L2A+ will be realised by fulfilling the following individual objectives: Develop a refined Aeolus aerosol optical product (L2A+). Examine the impact of L2A and L2A+ on aerosol assimilation and dust transport models. Assess the impact of Aeolus on NWP. Highlight the benefit of the Aeolus joint aerosol and wind assimilation for simulating dust deposition fields. Compare the monthly averaged L2A+ product with the CALIPSO L3 product, to assess the climatological value of L2A+ for aerosol databases. |
| LACUS: Development and Testing of Novel Approaches for Monitoring of Tailings Storage Facilities Based on EO and IoT | The service proposed under this project offered an improved method in monitoring mine tailings sites by amalgamating ubiquitous ground sensor data with EO. The activity developed a means of providing near-real-time views of mine tailings’ [...] | Davra Networks Ltd (IE) | Enterprise | artificial intelligence, mining | The service proposed under this project offered an improved method in monitoring mine tailings sites by amalgamating ubiquitous ground sensor data with EO. The activity developed a means of providing near-real-time views of mine tailings’ perimeter changes and fill levels in order to provide more comprehensive datasets, which can be used to forecast potential physical breaches or environmental regulation breaches by employing live monitoring and the use of artificial intelligence. As mining laws vary widely from country to country, the industry is largely self-policed from a regulatory perspective, hence the commercial scope for atrusted and uniform monitoring solution has significant commercial value. It was the goal of the project that the solution developed can be used globally in a variety of mining environments, once commercialised. The activity received consultancy support from the following entities: National University of Ireland Maynooth (expertisein in decision support systems which incorporate EO and ground truth data) and Odyssey VC Ireland (expertise in regulatory and business environment associated with the mining industry). |
| Land Cover Change Detection and Monitoring Methodologies Based on the Combined Use of Sentinel-1 and Sentinel-2 for Natural Resources and Hazard Management. | The main objective of this R&D activity is to develop and validate novel methodologies for Land EO products based on the joint exploitation of Sentinel-1A SAR data and Sentinel-2A optical imagery. The outcome of the activity is intended to [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Science | applications, forestry, land cover | The main objective of this R&D activity is to develop and validate novel methodologies for Land EO products based on the joint exploitation of Sentinel-1A SAR data and Sentinel-2A optical imagery. The outcome of the activity is intended to be the prototype implementation of a new change detection methodology for land cover and agricultural monitoring along with the supporting documentation, database and products.A framework for the semi-automatic and probabilistic mapping of land cover changes is proposed within this project. Methodologies will be tuned to track changes due to: natural hazards such as landslides and floods; changes in land cover that influence natural hazard occurrence, like snow cover changes and forest changes; and finally, changes in agriculture. The framework consists of: (i) a multi-sensor training library of change signatures trapped by the Sentinels in a set-up phase and caused by landslides, floods, snow cover, deforestation and agricultural operations, and (ii) a probabilistic classifier which combines image analysis and temporal and/or susceptibility models to recognize, identify, and map changes. The first mandatory step is to prepare a library of spectral changes (i.e. the signatures) due to events occurring between two consecutive Sentinel images of the same type (optical or/and SAR). This step involves the extraction of spectral changes over time using bi-temporal change detection methods like image differencing, spectral angle, independent or principal component analysis as well as time series analysis approaches like the Continuous Change Detection and Classification (CCDC) to map changes using Sentinel-2 data and backscattering coefficient changes for Sentinel-1 data, taking into account the Dual Pol channels and coherence maps. Together with the statistics of the main changes, contextual information will be considered such as the distribution of changes in different geo-environmental contexts. Specific changes associated with landslides, floods, snow, forests, and agriculture will be recognised, mapped and the relative signatures will be extracted. The second phase is devoted to the probabilistic semi-automatic recognition and mapping of a new change, i.e. a new landslide or forest change. The algorithm recognizes changes between a new image and the previous one, it queries the library looking for similar signatures (similar changes that occurred in the past in similar geo-environmental conditions), and if found, it will use the signature as a training area to assign the probabilistic class membership of each pixel in the new image. The probabilistic class membership can be coupled to other probabilistic susceptibility models, if available, to condition or to weigh the classification. The procedure can run separately for S1 and S2 and two distinct maps are obtained. In the case that S1 and S2 images are available simultaneously (or with a non-significant delay) for the same specific event, combined S1-S2 signatures can be adopted to solve possible ambiguities present in the single signatures in assigning the probabilistic class membership. The expected final result is a methodology for automatic recognition and mapping of changes coded in the library. The mapping is probabilistic: for each pixel inside the satellite image, a probability of change is assigned. |
| LAND SURFACE CARBON CONSTELLATION STUDY | The carbon cycle is central to the Earth system, being inextricably coupled with climate, the water cycle, nutrient cycles and the production of biomass by photosynthesis on land and in the oceans. In the natural system the balance among carbon [...] | LUND UNIVERSITY (SE) | Science | carbon cycle, carbon science cluster, science | The carbon cycle is central to the Earth system, being inextricably coupled with climate, the water cycle, nutrient cycles and the production of biomass by photosynthesis on land and in the oceans. In the natural system the balance among carbon in the atmosphere, the land and the ocean is regulated through fluxes between these three main reservoirs. In addition to these natural components, there are the flux contributions to the atmosphere from human activities, namely, fossil fuel burning, cement production, and a range of land management practices. Understanding the patterns of exchanges of carbon between the atmosphere and the land and the underlying processes associated to them such as CO2 fertilization, changes in climate, and changes to natural disturbance regimes, are critical to improving knowledge of the carbon cycle, its direct and indirect impacts on society. Identifying approaches to mitigate and adapt for the consequences of the anthropogenic disturbance of the carbon cycle is hampered by the uncertain uptake of atmospheric carbon by the terrestrial biosphere, and the response of this uptake to climate change itself. To achieve such understanding and reduce these uncertainties requires an integrated approach to the carbon cycle which exploits both observations (satellite and in situ) and modelling. The main objective of the Land surface Carbon Constellation (LCC) project is to demonstrate the synergistic exploitation of satellite observations from active and passive microwave sensors together with optical data for an improved understanding of the terrestrial carbon and water cycles. This will be achieved by: adapting a numerical land surface model for its application in a data assimilation framework, acquisition and analysis of campaign data sets at Sodankylä (Finland) and Majadas de Tietar (Spain) supporting the development of the model and the data assimilation scheme on the local scale. The LCC Study started in October 2020 and contributes to ESA’s Carbon Science Cluster, focussing on its land component. |
| Large Scale Exploitation of Satellite Data for the Assessment of Urban Surface Temperatures (EO4UTEMP) | Living Planet Fellowship research project carried out by Zina Mitraka. The rate at which global climate change is happening is arguably the most pressing environmental challenge of the century and it affects our cities. Temperature is one of [...] | FORTH (GR) | Science | biosphere, land, living planet fellowship, science, Sentinel-2, Sentinel-3 | Living Planet Fellowship research project carried out by Zina Mitraka. The rate at which global climate change is happening is arguably the most pressing environmental challenge of the century and it affects our cities. Temperature is one of the most important parameters in climate monitoring and Earth Observation (EO) systems and the advances in remote sensing science increase the opportunities for monitoring the surface temperature from space. EO4UTEMP examines the exploitation of EO data for monitoring the urban surface temperature (UST). Large variations in surface temperatures can be observed within a couple of hours, particularly when referring to urban surfaces. The geometric, radiative, thermal, and aerodynamic properties of the urban surface are unique and exert particularly strong control on the surface temperature. EO satellites provide excellent means for mapping the land surface temperature, but the particular properties of the urban surface and the unique urban geometry in combination with the trade-off between temporal and spatial resolution of the current satellite missions impose the development of new sophisticated surface temperature retrieval methods particularly designed for urban areas. EO4TEMP will develop a novel UST algorithm exploiting multi-temporal, multi-sensor, multi-resolution EO data, to be validated with in-situ measurements in urban sites and to be applied to Sentinel-3 and Sentinel-2 data. Therefore, EO4UTEMP will provide an advanced methodology for deriving frequent UST estimations at local scale (100 m), capable of resolving the diurnal variation of UST and contribute to the study of the urban energy balance. Results: Mitraka, Z. and Chrysoulakis, N.: Large Scale Exploitation of Satellite Data for the Assessment of Urban Surface Temperatures, EGU General Assembly , online, 19–30 Apr 2021 |
| LARGER-SCALE EO EXPLOITATION ACTIVITIES IN SUPPORT OF SUSTAINABLE DEVELOPMENT INITIATIVES (EO4SD) – FOREST MANAGEMENT | The European Space Agency (ESA)’s Earth Observation for Sustainable Development (EO4SD) Initiative (http://eo4sd.esa.int), linked to the ESA-WB partnership, has started in September 2020 a new thematic cluster dedicated to Forest Management [...] | GAF AG (DE) | Applications | applications, forestry, sustainable development | The European Space Agency (ESA)’s Earth Observation for Sustainable Development (EO4SD) Initiative (http://eo4sd.esa.int), linked to the ESA-WB partnership, has started in September 2020 a new thematic cluster dedicated to Forest Management which is financed by ESA through 2023. The EO4SD-Forest Management Cluster has the overall objective of demonstrating the utility and benefits of mainstreaming Satellite Earth Observation (EO)– based forest related products and services for improved Forest Management for International Financial Institution (IFI) Programmes and stakeholder in Client States (CS). The cluster complements a set of seven other thematic areas addressed under the EO4SD initiative in collaboration with the World Bank (WB) and other IFI partners. EO4SD forms the basis for the new Space in Support of International Development Assistance (Space for IDA) follow-up initiative, jointly implemented by ESA and World Bank, which aims at bringing these efforts to scale and at enlarging the long-term ESA-WB partnership. The EO4SD-Forests cluster is led by GAF AG (Germany) and a Consortium of European and Canadian expert partners (Caribou Space/UK, Hatfield/Canada, Indufor/Finland, SIRS/France, Wageningen University/Netherlands) who have well established experience in the provision of geo-spatial data and services for forest monitoring and management especially in the UNFCCC REDD+ policy segment. Following the EO4SD framework, the Consortium will embark on initial consultative discussions on stakeholder engagement with the Bank’s various groups active in the forest domain and jointly identify best cases for collaboration. In the current EO4SD component, the more specific objectives are to provide convincing demonstrations of the benefit and utility of EO-based information in the field of Forest Management. The service provisions shall be on a regional basis in specific countries in Latin America, South East Asia and Africa and will be based on a fully functional forest service portfolio with quality controlled EO products. Skills transfer via capacity building will be implemented in the different regions in order to enable CS stakeholders to both use and produce EO products. |
| LIdar Cloud REcord for Climate – LICREC | Clouds play an important role in the energy budget of our planet: optically thick clouds reflect the incoming solar radiation, leading to cooling the Earth, while thinner clouds act as “greenhouse films”, preventing escape of the Earth’s [...] | Sorbonne Université, SU (FR) | Science | Aeolus, Altitude, atmosphere, atmosphere science cluster, science | Clouds play an important role in the energy budget of our planet: optically thick clouds reflect the incoming solar radiation, leading to cooling the Earth, while thinner clouds act as “greenhouse films”, preventing escape of the Earth’s long-wave radiation to space. Cloud response to ongoing greenhouse gases climate warming is the largest source of uncertainty for model-based estimates of climate sensitivity and therefore for predicting the evolution of future climate. Understanding the Earth’s energy budget requires knowing the cloud coverage, its vertical distributions and optical properties. Predicting how the Earth climate will evolve requires understanding how these cloud variables respond to climate warming. Documenting how the cloud’s detailed vertical structure evolves on a global scale over the long-term is therefore a necessary step towards understanding and predicting the cloud’s response to climate warming. Satellite observations have been providing a continuous survey of clouds over the whole globe. Passive infrared sounders have been observing our planet since 1979. Active sounders, which measure the altitude-resolved profiles of backscattered radiation with an accuracy on the order of 1−100 meters. These instruments have been providing invaluable information on cloud’s vertical profile with the accuracy matching modern requirements for climate-related processes and feedback analysis since 2006. All active instruments share the same measuring principle – they send a short pulse of laser or radar electromagnetic radiation to the atmosphere, collect the time-resolved backscatter signal by the telescope, and then register it in one or several receiver channels. However, the wavelength, pulse energy, pulse repetition frequency, telescope diameter, orbit, detector, or optical filtering are not the same for any pair of instruments. These differences define the active instruments’ capability of detecting atmospheric aerosols and/or clouds for a given atmospheric situation and observation conditions (day, night, averaging distance). At the same time, there is an obvious need to ensure the continuity of global space-borne lidar measurements. One has to stress that a simple merging of different satellite data is not enough – our overarching goal is to build a multi-lidar record accurate enough to constrain predictions of how the clouds evolve as climate warms. The project will merge the measurements performed by the relatively young space-borne lidar ALADIN/Aeolus, which has been orbiting the Earth since August 2018 and operating at 355nm wavelength with the measurements performed since 2006 by CALIPSO lidar, which is operating at 532nm and is near the end of its lifetime. Even though the primary goal of ALADIN is wind detection, its products include profiles of atmospheric optical properties (aerosols/clouds). This makes it an excellent test bed for developing an approach for building a continuous multi-lidar cloud record. Main objectives of this activity are to: develop a cloud layer detection method for ALADIN measurements, which complies with CALIPSO cloud layer detection; compare/validate the resulting cloud ALADIN product with the well-established CALIOP/CALIPSO cloud data set; develop an algorithm for merging the CALIOP and ALADIN cloud datasets; apply the merging algorithm to CALIOP and ALADIN data and build a continuous cloud profile record; adapt this approach to future missions (e.g. ATLID/EarthCare). |
| Machine Learning Methods for SAR-derived Time Series Trend Change Detection (MATTCH) | The MATTCH project - Machine Learning methods for SAR-derived Time Series Trend Change Detection - aims to apply Machine Learning techniques to InSAR (Interferometric Synthetic Aperture Radar) derived surface deformation measurements, with the [...] | TRE ALTAMIRA s.r.l. (IT) | Science | permanently open call, SAR, science | The MATTCH project – Machine Learning methods for SAR-derived Time Series Trend Change Detection – aims to apply Machine Learning techniques to InSAR (Interferometric Synthetic Aperture Radar) derived surface deformation measurements, with the goal of identifying, among the huge number of measurement points (MP) identified by advanced InSAR algorithms, the ones exhibiting displacement time series characterized by a change in trend or, more generally, an “anomalous behavior”. This data screening step is extremely important to support the End Users Community in the exploitation of frequently updated (every few days) and highly populated (millions of MPs) information layers resulting from advanced InSAR analyses over large areas.MATTCH aims to identify whether and how a Machine Learning approach can be applied successfully to the “data screening and data mining” step (with a particular emphasis on the detection of changes in trends), relying on the experience in SAR data processing of TRE ALTAMIRA and the extensive knowledge of POLIMI (Politecnico di Milano – Dipartimento di Elettronica e Informazione e Bioingegneria) about Machine Learning algorithms and their applications.To capture the temporal dependencies in the long displacement time series, the main Deep Learning architectures proposed for the analysis are Long Short-term Memory (LSTM) and Gate Recurrent Unit (GRU).The main objectives of the project are:Making SAR-derived surface deformation products more user-friendly and effective, supporting the analysis and the exploitation of InSAR-derived data, through the generation of a reliable layer of information driving the attention of the final users on a set “hotspots deserving special attention”;Enhancing the SqueeSARTM processing chain, via the implementation of a Machine Learning approach for time series trend detection, which is expected to improve the reliability and reduce the computational cost with respect to the statistical procedure currently in use;Increasing the knowledge about Machine Learning techniques applied to Earth Observation Big Data in both TRE ALTAMIRA and POLIMI groups, strengthening an effective cooperation between industry and academia in this relatively novel research field;Increasing the knowledge of Graphic Process Units (GPU) and cloud-based services to perform high throughput data processing and flexible scale-up;Improving the exploitation of ESA Sentinel-1 data, by creating innovative solutions, spurring new services to end-users and hopefully increasing the Earth Observation market |
| MAchine Learning Tool for Calibration of Hyperspectral data (MATCH) | The project aims at the development of algorithms for cross-calibration of hyperscout with S-2 and the development of the phi-sat 1 brain for cloud detection. The team is assessing Machine Learning methodology, techniques, and a suite of [...] | COSINE RESEARCH B.V. (NL) | AI4EO | AI4EO, hyperspectral, Sentinel-2 | The project aims at the development of algorithms for cross-calibration of hyperscout with S-2 and the development of the phi-sat 1 brain for cloud detection. The team is assessing Machine Learning methodology, techniques, and a suite of applications (ranging from Radiometric calibration of a single band L2A data, Calibration of data products, e.g. NDVI or LAI and Radiometric calibration of a hyperspectral spectrum L2A data). The results from PhiSat-1 mission operations proved that is possible to detect clouds during day time using a neural network on HyperScout 2 Visible Near InfraRed spectral data. Additional activities have been identified in order to complete the cloud detection capabilities including also night time using HyperScout Thermal Infrared data. The project extension aims to: Verify whether is possible to classify clouds in-orbit during night-time using the thermal infrared channel of HyperScout 2 Developed synthetic HyperScout 2 TIR nocturnal imagery to be used for training, and asses whether the quality of that data directly affects the performance of the Network. Further develop the NightView neural network according to the HyperScout 2 needs Check whether cloud detection at night can be performed employing deep learning with thermal infrared as produced by HyperScout 2. Currently, the existing convolutional neural network is trained using the MODIS sensor on-board the Aqua and Terra satellites and the associated cloud mask. |
| Mapping and characterization of unstable slopes with Sentinel-1 multigeometry InSAR | Being a mountainous country, with long fjords and steep valley sides, Norway is particularly susceptible to large rock avalanches. In the last 100 years, over 170 people have been killed by tsunamis in fjords caused by large rock avalanches. In [...] | NORTHERN RESEARCH INSTITUTE (NORUT) (NO) | Applications | disaster risk, permanently open call, SAR, science | Being a mountainous country, with long fjords and steep valley sides, Norway is particularly susceptible to large rock avalanches. In the last 100 years, over 170 people have been killed by tsunamis in fjords caused by large rock avalanches. In each case, the rock avalanche was preceded by many years of slow movement, with acceleration prior to slope failure. With several thousand kilometres of inhabited coastline and valleys, it is a challenge to identify similar hazards in an efficient manner. Once we suspect an area to be sliding, it may take several years of measurements to confirm it, and an extensive ground instrumentation to characterize the type of motion. The Geological Survey of Norway (NGU) is responsible for hazard and risk classification of large rock slope instabilities in Norway. They also assist the Norwegian Water Resources and Energy Directorate (NVE) with long term monitoring of high risk instabilities. A very important factor in determining hazard is the determination of rates of movements. This is predominantly done using InSAR, although GNSS and in situ instrumentation (crack meters, tilt meters, borehole instrumentation, total stations etc.) are also applied at site level. In Norway, there has been a significant interest from the public stakeholders (NGU and NVE) to use InSAR, mainly for mapping of landslides. NGU launched a development project in 2016, with Norut a prime contractor, to set up a national InSAR-based deformation mapping service, based upon satellite data from Sentinel-1. The first national deformation map, produced by using Sentinel-1 Persistent Scatterer Interferometry (PSI), was publicly released in November 2018. The system, when in operational phase, will provide updated displacement maps at a national scale, and with an open data policy. It is however well know that when the true displacement direction differs from the satellite line-of-sight (LoS), the sensitivity decreases and interpretation of InSAR deformation measurements may become challenging. Relating InSAR displacement maps to ongoing surface displacement processes can be difficult. A knowledge of the LoS direction for the applied satellite geometry as well as factors controlling the direction of displacement (gradient and aspect of the terrain, orientation of controlling geological structures) is required to understand how much of the true three-dimensional (3D) displacement can be observed. Combining InSAR data from ascending and descending satellite orbits can increase sensitivity for displacement by providing information about the displacement, decomposed into the East-West and Vertical vector surface. The resulting products will contain information about both the magnitude and the direction of surface displacement. Combination is possible in areas covered by at least two spatially and temporally overlapping InSAR datasets, from ascending and descending orbit geometries. By combining InSAR information determined from different lines of sight, the understanding of the type of movement taking place is improved. For example, surface parallel, mostly vertical, toppling etc. In this project, we will develop higher-order products based on combination of different InSAR datasets in order to ease the interpretation of site-specific deformation processes. The aim of our project is to define and develop geologically meaningful InSAR products to provide meaningful information about slope processes, which could extend the use of Sentinel-1 InSAR in landslide risk management in Norway. |
| MARINE LITTER SIGNATURES IN SYNTHETIC APERTURE RADAR IMAGES (MIREIA) | This project complements on-going activities and other activities started under this call for proposals by focussing on optimising the techniques for the detection of marine litter in SAR data. This complements the use of optical data and [...] | ISARDSAT S.L. (ES) | Science | marine environment, permanently open call, SAR, science | This project complements on-going activities and other activities started under this call for proposals by focussing on optimising the techniques for the detection of marine litter in SAR data. This complements the use of optical data and modelling in order to progressively build up an integrated picture as to how marine litter (and marine plastics in particular) are entering the marine environment, how they are transporeted, how they break down and how they are impacting different ecosystems. Results: “A first approach to the automatic detection of marine litter in SAR images using artificial intelligence”, Salvatore Savastano, Ivan Cester, Marti Perpinya, Laia Romero, Proceedings of IGARSS 2021, Brussels |
| MARITIME AWARENESS PRE-OPERATIONAL DEMONSTRATIONS – EXPRO | Maritime Domain Awareness (MDA) is defined by the International Maritime Organization (IMO) as the effective understanding of anything associated with the maritime domain that could affect the security, safety, economy, or environment. In the [...] | E-GEOS (IT) | Enterprise | applications, maritime spatial planning, oceans, SAR, security, Sentinel-1, Sentinel-2 | Maritime Domain Awareness (MDA) is defined by the International Maritime Organization (IMO) as the effective understanding of anything associated with the maritime domain that could affect the security, safety, economy, or environment. In the context of MDA activities, the complete understanding of the current maritime picture, as well as a deep knowledge of the maritime patterns of life as consolidated in the monitored area, are crucial for an efficient and effective capability to monitor the maritime activities. In recent years, the need for improved capabilities for Maritime Domain Awareness has increased considerably. For instance, illegal immigration by sea represents the most visible of the problems affecting the European Union’s maritime sea borders, which also includes illegal activities of different kinds (drugs, weapons, pollution,etc.) and terroristic threats. In addition, an ever-increasing importance is given to the protection of coastal and off shore sensitive assets, for what concerns both human and natural threats. A typical scenario for these activities is the maritime scenario, where this illegal traffic is added to the legal civil and/or military maritime traffic, both along the coasts and in open water, making the monitoring and surveillance of all such activities extremely necessary to the national and international security. There is a strong need to integrate innovative technologies and solutions into the conventional maritime decision support systems, in order to increase the surveillance capabilities in the different areas of operation.The increasing number of space assets and recent advances in Information Extraction from satellite images, data fusion processing and Big Data technology provide a wide range of Maritime Analysis Tools and components that can fulfil requirements to produce actionable information in support of decision making and operations in the maritime intelligence domain.In this evolving context, the objective of this proposal is specifically the provision of a comprehensive solution to allow and complete assessment of : valued added and/or limitation related to the exploitation of ISAR/SAR Refocusing derived products contribution of the ISAR/SAR Refocusing to the improvements of data fusion processing Impact of RF data on the Maritime Domain Awareness. This will be done through three project tasks: Requirements consolidation and design of algorithms, to assess the study of the state of the art and to select most promising and effective technologies to implement the identified evolutions Prototypes Implementation, to develop, deploy and test the ISAR processing prototype as well as the enhanced data fusion model (EO, AIS and RF data) through the e-GEOS proprietary SEonSE platform Use cases Demonstration and Validation, to design multi-sensors (Sentinel-1, Sentinel-2, COSMO-SkyMed, AIS and RF data) demonstration scenarios to validate prototype performances through the application of ad-hoc key performance indicators. |
| Mass balance and ice dynamics of Antarctic Peninsula glaciers (MIT-AP) | Living Planet Fellowship research project carried out by Thorsten Seehaus. Pronounced climatic changes have been observed at the Antarctic Peninsula within the past decades and its glaciers and ice caps have been identified as a significant [...] | Friedrich-Alexander-Universität Erl (DE) | Science | Antarctica, climate, cryosphere, Glaciers and Ice Sheets, living planet fellowship, polar science cluster, SAR | Living Planet Fellowship research project carried out by Thorsten Seehaus. Pronounced climatic changes have been observed at the Antarctic Peninsula within the past decades and its glaciers and ice caps have been identified as a significant contributor to global sea level rise. Dynamic thinning and speed-up was reported for various tidewater glaciers on the western Antarctic Peninsula. On the east coast, several ice shelves disintegrated since 1995. Consequently, former tributary glaciers showed increased flow velocities due to the missing buttressing, leading to substantial ice mass loss. Various studies were carried out to quantify the ice mass loss and ice discharge to the ocean at the Antarctic Peninsula using different approaches. However, the results are still subject to substantial uncertainties, in particular for the northern section of the Antarctic Peninsula (<70°S). Thus, the aim of this project is to carry out an enhanced analysis of glacier mass balances and ice dynamics throughout the Antarctic Peninsula (<70°S) using various remote sensing data, in-situ measurements and model output. By analyzing bistatic SAR satellite acquisitions, an unprecedented spatial coverage with surface elevation change information at the study area will be achieved to compute multi-temporal geodetic glacier mass balances on regional and glacier scales. Information on ice dynamics will be derived from multi-mission SAR acquisitions using offset tracking techniques. In combination with latest ice thickness data sets the spatiotemporal variability of the ice discharge to the ocean will be evaluated. By including information from in-situ measurements and model output of atmospheric and oceanic parameters, driving factors of the obtained change patterns will be assessed to enhance the understanding of the ongoing change processes. The project results will contribute fundamental information to international initiatives and institutions like IMBIE, IPCC and WGMS and address several “Advancing Earth System Science Challenges of the Living Planet”, defined by ESA. |
| Massive Open Online Course (MOOC) – EO Open Data Science | The EO Open Data Science MOOC is hosted on EO-College with the title "Cubes and Clouds" https://eo-college.org/courses/cubes-and-clouds/.This course teaches the concepts of data cubes, cloud platforms, and open [...] | EURAC RESEARCH – ACCADEMIA EUROPEA (IT) | AI4EO | AI4EO, platforms, training and education | The EO Open Data Science MOOC is hosted on EO-College with the title “Cubes and Clouds” https://eo-college.org/courses/cubes-and-clouds/. This course teaches the concepts of data cubes, cloud platforms, and open science in the context of Earth Observation. Its goal is to provide students with practical knowledge on how to effectively use EO Platforms for Open Data Science in the cloud. At the end of the course, students will be able to develop and execute EO applications on the most commonly used cloud platforms (for EO) and to successfully apply the key principles of Openness for EO Scientific research and applications. In particular, the course will help students to develop essential skills and knowledge in: How to programmatically access ESA and other open data in a platform environment; Designing, developing and executing algorithms on EO cloud platforms; Scalable EO and geospatial analytics in the cloud; Open Source development practices. The course explains the concepts of data cubes, EO cloud platforms, and open science by applying them to a typical EO workflow from data discovery, and data processing up to sharing the results in an open and FAIR (Findable, Accessible, Interoperable, Reusable) way. An engaging mixture of videos, animated content, lectures, hands-on exercises, and quizzes transmits the content. You will learn the theoretical concepts of cloud native EO processing and have gained practical experience by conducting an end-to-end EO workflow. You will be capable of independently using cloud platforms to approach EO-related research questions and be confident in how to share research by adhering to the concepts of open science. As proof of the acquired skills a community snow cover map is created where every participant contributes and shares his results openly and FAIR: Cubes and Clouds: Snow Cover STAC Collection The course is now in beta-testing and will be launched in February 2024. This course is part of ESA’s Open Science activities. @EO_OPEN_SCIENCE |
| MedEOS – Mediterranean coastal water monitoring | This activity is part of the ESA Regional Initiatives programme. Its objective is to support the implementation of regional priorities in the Mediterranean region by i) developing and delivering a customized set of EO based products that fully [...] | Deimos Engineering and Systems (ES) | Regional Initiatives | bathymetry and seafloor topography, Mediterranean, regional initiatives, sea surface topography, Sentinel-1, Sentinel-2, Sentinel-3 | This activity is part of the ESA Regional Initiatives programme. Its objective is to support the implementation of regional priorities in the Mediterranean region by i) developing and delivering a customized set of EO based products that fully exploit the large volumes of EO data from the Sentinel missions and other EO missions and ii) achieving measurable progresses in embedding this EO-derived information into the strategies and cooperation actions within the Mediterranean region. The specific objective of the Sea Application project is to improve the characterisation, quantification and monitoring of land-based pollution in the Mediterranean coastal waters by optimizing the use of the Sentinel missions and other relevant space and in-situ datasets to develop multi-mission high resolution gap-free maps of water quality parameters (e.g. Chl-a, turbidity, TSM, nutrients, bacteriological concentration,…) and added-value innovative products (e.g. river plumes contour,…) over the period 2015-present. |
| Mediterranean Regional Initiative Land Project | Objectives: to develop product, method and algorithm to infer the soil sealing within the 20 km of the coast all along the med basin usig S1 and S2 constellation at 10 meters resolution. | Planetek Italia (IT) | Regional Initiatives | applications, land, Mediterranean, regional initiatives, Sentinel-1, Sentinel-2 | Objectives: to develop product, method and algorithm to infer the soil sealing within the 20 km of the coast all along the med basin usig S1 and S2 constellation at 10 meters resolution. |
| Methane Emission Detection from Satellite Measurements | The project, Methane Emission Detection from Satellite Measurements, is being developed by the U.K. National Physical Laboratory (NPL), experienced in emission detection and rate measurement using in-situ measurement technologies, in particular [...] | NATIONAL PHYSICAL LABORATORY (NPL) (GB) | Enterprise | atmosphere, enterprise, permanently open call | The project, Methane Emission Detection from Satellite Measurements, is being developed by the U.K. National Physical Laboratory (NPL), experienced in emission detection and rate measurement using in-situ measurement technologies, in particular with application to land fill sites and the oil and gas industry, and GHGSat Inc., a company operating a state-of-the-art satellite system to detect atmospheric methane. Scope of the activity is a demonstration exercise to determine current and emerging capabilities to detect surface methane emissions from small and facility scale areas using satellites (e.g. leaks from high pressure gas infrastructures and unlicensed land fill sites), which would have a considerable impact for both gas pipeline operators and national EPAs. The aim is to characterize the level of performance, in particular, to what extent leaks can be detected with reference to operator’s requirements. This includes integration of the latest GHGSAT satellite (i.e. GHGSat-C1), which is expected to provide an order of magnitude improvement in methane detection (400 tons per year in the relative absence of wind to 1,000 tons per year in moderate winds) over the previous GHGSat satellite (i.e. GHGSat-D), operational for more than two years. The project envisages a co-design exercise with end-user communities (e.g gas pipeline operators, infrastructures technical services providers, etc…), stakeholders (UK Environment Agency) and partners (U.K. National Grid, which is the owner and operator of the UK National Transmission System comprising approximately 7660 kilometres of high pressure pipeline and 618 above-ground installations).The project will provide key outputs to underpin and stimulate the development of commercial services for the determination of methane mass emissions, in particular from the gas industry. This will be achieved through three key phases Phase 1 – Measurement requirement definition – a key outcome will be the definition of a comprehensive measurement service and data product requirement specification. This will be achieved through discussions and interaction with industry bodies and gas supply companies. A key point is that there is likely to be no single measurement requirement and a range of capabilities will be needed. The project will therefore assess the range of needs from industry, including for example the quantification of methane emissions from sites/facilities and the identification of leaks from distributed infrastructure. By identifying the key needs and drivers, a range of potential data services can be identified and this will enable satellite providers and data providers to tailor current and future services to meet the needs of industry. Phase 2 – Satellite capability validation and calibration – satellite methane column measurements are validated against ground stations such as those in TCONN. However, this does not provide the necessary calibration and validation data to support methane mass emission quantification or specific leak detection data products and services. To support the development and ongoing operation of these services a suitable calibration infrastructure is necessary. This project will develop such an approach utilising existing methane sources. As a demonstration of the feasibility of this approach a landfill site will be used, as these sites emit methane on a continuous basis. Such ground calibration sites would then be available in subsequent commercial data services as routine mass emission rate calibration sites. This project will therefore develop a key element of mass emission data product services, enabling the commercial deployment of such services. Phase 3 – Operational review of GHGSat and other satellites – Satellite capabilities will be reviewed for their applicability specifically to pipeline monitoring. Subject to this review and the results of Phase 1, the project partners aim for a demonstration of GHGSat-C1 capabilities and methane mass emission data products for applicability to monitoring pipeline facilities such as compressors and terminals. |
| Methane+ | The ESA Methane+ project aims at exploiting the SWIR and TIR CH4 observations from different satellites in order to better differentiate between sources and sinks of CH4 on the regional and global scale. For this we will use the CH4 observations [...] | Netherlands Institute for Space Research (NWO-I) (NL) | Science | atmosphere, atmosphere science cluster, atmospheric chemistry, carbon science cluster, CrIS, IASI, Metop, permafrost challenge, science, Sentinel-5P, SUOMI-NPP | The ESA Methane+ project aims at exploiting the SWIR and TIR CH4 observations from different satellites in order to better differentiate between sources and sinks of CH4 on the regional and global scale. For this we will use the CH4 observations of TROPOMI on Copernicus Sentinel-5p, IASI on MetOp-B, and CrIS on Suomi NPP in combination with atmospheric inversion models. OBJECTIVES: Given the identified opportunities and challenges of the current generation of space borne methane sensors, and the scope of the current study, the specific study objectives are as follows: Providing support for the algorithm development for the CH4 SWIR retrieval from TROPOMI, TIR from IASI/CrIS, and joint SWIR-TIR retrieval from TROPOMI and IASI/CrIS. Assess the quality of the TROPOMI, IASI and CrIS CH4 retrievals by comparing data products generated with different algorithms and product validation using independent ”ground-based” measurements. Investigate the added value of combining CH4 SWIR and TIR in regional case studies. Infer global sources and sinks of CH4 from inverse modelling of 2 years of TROPOMI and IASI (and/or CrIS) data. Investigate the added value of the combined use of SWIR and TIR CH4 observations. Investigate the consistency of the SWIR and TIR CH4 satellite data, with model simulated transport and chemistry. Formulate a road map for future CH4 satellite remote sensing based on the outcomes of this study as well as parallel studies covering the use of CH4 from TROPOMI across the full range of scales. The Methane+ project started on 22-Jan-2020 with a duration of 2 years. |
| MethaneCAMP | Climate change is one of the greatest societal challenges of the 21st century. The dominant source of global warming is the increase of anthropogenic greenhouse gases in the Earth`s atmosphere. atmosphere. The two most important of those species [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | atmosphere, carbon cycle, climate, cryosphere, Ecosystems | Climate change is one of the greatest societal challenges of the 21st century. The dominant source of global warming is the increase of anthropogenic greenhouse gases in the Earth`s atmosphere. atmosphere. The two most important of those species are carbon dioxide (CO2) and methane (CH4). Together they account for ~82% of the anthropogenic radiative forcing. However, uncertainties in our knowledge of the budgets of these gases, which are determined by their sources and sinks, as well as inadequately understood feedback mechanisms, limit the accuracy of current climate change projections from the local to the global scale. To reliably predict the climate of our planet, and to guide political conventions on greenhouse gas avoidance, adequate knowledge of the sources and sinks of these greenhouse gases, their feedbacks, and the quantification of natural versus anthropogenic fluxes is mandatory. Wetland emissions of methane constitute the largest single source of methane to the atmosphere, even when considering all anthropogenic emissions, and are the most uncertain part of the budget. After the tropics, the largest distribution of wetlands is in the Arctic. The Arctic is warming twice as fast as compared to the global average, making climate change’s polar effects more intense than anywhere else in the world. The Arctic accounts for nearly 50% of all organic carbon stored in the planet’s soil but rising temperatures and thawing permafrost threatens its stability. The main objectives and tasks of MethaneCAMP are to: Collaborate and coordinate with the AMPAC (Artic Methane and Permafrost Challenge) initiative and forming AMPAC network aiming to contribute to bottom-up and top-down estimates of changes in methane emissions in the Arctic. Prepare a high-latitude-focused assessment of current atmospheric CH4 retrievals from medium spatial resolution and high spatial resolution instruments. Identify the improvement potential for high-latitude retrievals of CH4, test and validate these improvements and synthesize the potential of joint strategies. Analyse the changes in the Arctic CH4 with specific focus on i) quantifying longer-term trends, ii) identifying hot spots directly from observations, and iii) studying the apportionment between biogenic and anthropogenic CH4 sources by employing multi-scale Arctic CH4 observations in inverse modelling. |
| MethEO – Methane emissions in the Northern Hemisphere by applying both data from Earth Observing (EO) satellites and global atmospheric methane inversion model estimates | The project will investigate Northern Hemisphere methane (CH4) sources and their connection to the soil freezing and thawing at high latitudes. We will innovatively combine methods for monitoring of CH4 (methane) emissions in the Northern [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | atmosphere, atmosphere science cluster, biosphere, carbon cycle, carbon science cluster, permafrost challenge, permanently open call, polar science cluster, science, Sentinel-5P, SMOS | The project will investigate Northern Hemisphere methane (CH4) sources and their connection to the soil freezing and thawing at high latitudes. We will innovatively combine methods for monitoring of CH4 (methane) emissions in the Northern Hemisphere by applying both data from Earth Observing (EO) satellites and global atmospheric methane inversion model estimates. The EO data consists of global soil F/T estimates obtained from the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission (from the SMOS+ Frozen soil project) as well as retrievals of atmospheric methane obtained from the Greenhouse Gases Observing Satellite (GOSAT) and the newly launched Sentinel 5 Precursor TROPOMI (S5P-TROPOMI) observations. The project has been kicked-off the 5th September. A first informal progress meeting has been on 20th December. First results have been shown and look promising. |
| MOHeaCAN: Monitoring Ocean Heat Content and Earth Energy ImbalANce from Space | Since the industrial era, anthropogenic emissions of Greenhouse gases (GHG) in the atmosphere have lowered the total amount of infrared energy radiated by the Earth towards space. Now the Earth is emitting less energy towards space than it [...] | MAGELLIUM (FR) | Science | altimeter, climate, GRACE, ocean health flagship, ocean heat budget, ocean science cluster, oceans, permanently open call, science | Since the industrial era, anthropogenic emissions of Greenhouse gases (GHG) in the atmosphere have lowered the total amount of infrared energy radiated by the Earth towards space. Now the Earth is emitting less energy towards space than it receives radiative energy from the sun. As a consequence there is an Earth Energy Imbalance (EEI) at the top of the atmosphere. Because of this EEI, the climate system stores energy, essentially in the form of heat. This excess of energy perturbs the global water-energy cycle and generates the so-called “climate changes”. The excess of energy warms the ocean, leading to sea level rise and sea ice melt. It melts land ice, leading to sea level rise. It makes land surface temperature rise, changing the hydrological cycle and generating droughts and floods. It is essential to estimate and analyse the EEI if we want to understand the Earth’s changing climate. Measuring the EEI is challenging because it is a globally integrated variable whose variations are small (smaller than 1 W.m-2) compared to the amount of energy entering and leaving the climate system (~340 W.m-2). Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m-2. An accuracy of <0.1 W.m-2 at decadal time scales is desirable if we want to monitor future changes in EEI associated with anthropogenic forcing, which shall be a noncontroversial science based information used by the GHG mitigation policies. To date, the most accurate approach to estimate EEI consists of making the inventory of the energy stored in different climate system reservoirs (atmosphere, land, cryosphere and ocean) and estimating their changes with time. At large scale, variations in internal and latent heat energy dominate largely over the variations in other forms of energy (potential energy and kinetic energy). The ocean concentrates the vast majority of the excess of energy (~93%) associated with EEI. For this reason the global Ocean Heat Content (OHC) places a strong constraint on the EEI estimate. Thus it is crucial to characterise the uncertainty in EEI and OHC to strengthen the robustness of this estimation. Four methods exist to estimate the OHC: The direct measurement of in situ temperature based on temperature/Salinity profiles (e.g., Argo floats). The estimate from ocean reanalyses that assimilate observations from both satellite and in situ instruments. The measurement of the net ocean surface heat fluxes from space. The measurement of the thermal expansion of the ocean from space based on differences between the total sea-level content derived from altimetry measurements and the mass content derived from GRACE data (noted “Altimetry-GRACE”). To date, the best results are given by the first method mainly based on Argo network. However, one of the limitations of the method is the poor sampling of the deep ocean (>2000 m depth) and marginal seas as well as the ocean below sea ice. Re-analysis provides a more complete estimation but large biases in the polar oceans and spurious drifts in the deep ocean due to the too-short spin up simulations and inaccurate initial conditions of the reanalysis, mask a significant part of the OHC signal related to EEI. The method based on estimation of ocean net heat fluxes from space is not appropriate for OHC calculation due to a too strong uncertainty (±15 W.m-2) for the science objective on EEI. The last option based on the “Altimetry-GRACE” approach is promising because it provides consistent spatial and temporal sampling of the ocean, it samples nearly the entire global oceans, except for polar regions, and it provides estimates of the OHC over the ocean’s entire depth. To date the uncertainty in OHC from this method is ±0.47 W.m-2, which is greater than what is needed (<0.3 W.m-2) to pin down the global mean value of EEI. This activity focuses on the “Altimetry-GRACE” approach to estimate the EEI. The objectives are twofold: To improve global OHC estimation from space and its associated uncertainty by developing novel algorithms; To assess our estimation by performing comparison against independent estimates based on Argo and on the Clouds and the Earth’s Radiant energy System (CERES) measurements at the top of the atmosphere. This innovative study will be performed in coordination with initiatives focused on climate change studies and EEI as the Global Water and Energy Exchanges project (GEWEX) and the Climate and Ocean Variability, Predictability and Change project (CLIVAR) of WCRP. “Scientific Highlights” The MOHeaCAN product contains monthly time series (between August 2002 and June 2017) of several variables, the main ones being the regional OHC (3°x3° spatial resolution grids), the global OHC and the EEI indicator. Uncertainties are provided for variables at global scale, by propagating errors from sea level measurements (altimetry) and ocean mass content (gravimetry). In order to calculate OHC at regional and global scales, a new estimate of the expansion efficiency of heat at global and regional scales has been performed based on the global ARGO network. A scientific validation of the MOHeaCAN product has also been carried out performing thorough comparisons against independent estimates based on ARGO data and on the Clouds and the Earth’s Radiant energy System (CERES) measurements at the top of the atmosphere. The mean EEI derived from MOHeaCAN product is 0.84 W.m-2 over the whole period within an uncertainty of ±0.12 W.m-2 (68% confidence level – 0.20 W.m-2 at the 90% CL). This figure is in agreement (within error bars at the 90% CL) with other EEI indicators based on ARGO data (e.g. OHC-OMI from CMEMS) although the best estimate is slightly higher. Differences from annual to inter-annual scales have also been observed with ARGO and CERES data. Investigations have been conducted to improve our understanding of the benefits and limitations of each data set to measure EEI at different time scales. The MOHeaCAN product from “altimetry-gravimetry” is now available, documented and can be downloaded at https://doi.org/10.24400/527896/a01-2020.003. Users will be mainly interested in ocean heat content time series at regional (grids) and global scales, and Earth energy imbalance time series. Feedback from interested users on this product are welcome. |
| MONiCA: Development of Standardised Practices for Monitoring Landscape Values and Natural Capital Assessment | The MONiCA project addresses the increasing need for natural capital preservation and landscape protection. The project aims to develop a series of customised indicators allowing to integrate EO datasets with other non-EO data into regional [...] | Astri Polska (PL) | The MONiCA project addresses the increasing need for natural capital preservation and landscape protection. The project aims to develop a series of customised indicators allowing to integrate EO datasets with other non-EO data into regional working practices related to natural capital assessment and landscape auditing. The solution is dedicated to the Mazovian Office of Regional Planning subordinated to the Mazovian Marshall (Voivodeship) Office in Poland. Additionally to the EO indicators the project will develope an analysis support software tool. The developed service will provide automatic data processing, combining all processing steps to provide intermediate products (land cover, investment, humidity/moisture maps) as well as identified landscape types and their indicators. As the service is to be versatile and scalable, it can be hosted on different platforms like The Mazovian Voivodeship Office’s own servers or DIAS, and potentially it can be implemented by other voivodeships in the future. The scope of the project is also to prepare a future uptake roadmap, summarising the recommendations for extending the prepared monitoring approach to the other regions and will draft the funding sources for implementing the enhanced methodology to a wider number of regions. The project is part of the ESA Polish Industrial Incentive Scheme. | ||
| Monitoring, Measurement, Reporting and Verification System for Cocoa sector in the Dominican Republic | The MRV4C project, developing a Monitoring, Measurement, Reporting and Verification (MRV) System for cocoa agroforestry in the Dominican Republic (DR) was a 1-year activity funded by the European Space Agency through the Open Call funding [...] | GMV NSL LTD (GB) | Enterprise | agriculture, AI4EO, artificial intelligence, Biomass, climate, forestry, permanently open call, SAR, Sentinel-1, Sentinel-2, sustainable development | The MRV4C project, developing a Monitoring, Measurement, Reporting and Verification (MRV) System for cocoa agroforestry in the Dominican Republic (DR) was a 1-year activity funded by the European Space Agency through the Open Call funding opportunity, addressing activity line 6, “EO for Sustainable Development”, of the ESA EO SCIENCE FOR SOCIETY programme. The aim of the MRV4C was two-fold: use of EO and development of an interactive tool for supporting sustainable management and decision-making in a supply chain that is key for the DR economy – that of cocoa; and contribute to the sustainability and strengthening of the national REDD+ MRV system, funded by the Bio-Carbon Fund of the World Bank (FCPF). With the support of the World Bank, GMV NSL engaged the DR Ministry of Environment and Natural Resources, The Cocoa Department at the Ministry of Agriculture, the National Cocoa Commission (CONACADO) and the private sector, represented by the country’s main confederation of cocoa producers (DR Cocoa Foundation), besides several NGOs and international observers. Using EO and AI, GMV NSL demonstrated the incredible potential of Sentinel data to benefit cocoa agroforestry and the DR economy by identifying the best areas to grow this crop, mapping current cocoa farms extension and determining above-ground biomass. Furthermore, GMV built a system and an interactive tool within a web-based platform that enables, for instance, the planning of suitable land for growing cocoa and the verification of a zero-deforestation cocoa supply chain. The MRV4C project, leveraging on the data provided through the Copernicus Programme, demonstrated the role of EO to back up EU policies that aim to boost sustainable cocoa production by contributing to enhancing the economic, social, and environmental sustainability of cocoa in several countries (including the Dominican Republic, one of the largest supplier of cocoa beans to the EU). As well as contributing to the DR country objectives, the project provided tangible evidence of how the Sentinel satellites can contribute to the United Nations Sustainable Development Goals (SDGs), in particular, Goals 1, 2, 8, 13 and 15: “No-Poverty”, “Zero Hunger”, “Decent Work and Economic growth”,”Climate Action”, and “Life on Land”. |
| MOOC ATMOSPHERE | The course will introduce learners to the role of satellite ‘Earth observation’ (EO) technology in monitoring the Earth's Atmosphere and the data it produces looking also at the importance of ground based remote sensing and in situ observations, [...] | Imperative Space (GovEd Ltd) (GB) | Science | atmosphere, atmosphere science cluster, science | The course will introduce learners to the role of satellite ‘Earth observation’ (EO) technology in monitoring the Earth’s Atmosphere and the data it produces looking also at the importance of ground based remote sensing and in situ observations, which complements as well as validates EO data. During the first week state of art atmospheric scientists and researchers will guide learners through the basic concepts of how satellites acquire data about the atmospheric composition and will provide an introduction to Atmospheric science, the second week covers atmospheric chemistry, greenhouse gases and ozone, the third week looks at air quality, health and policy, and the fourth week explores atmospheric dynamics and long-range pollution transport. An additional Week focusing on the impacts on the atmospheric composition of COVID-19 lockdown measures, is also included in this course. The course can be taken at this link: https://www.imperativemoocs.com/courses/eo-from-space-the-atmosphere |
| MOOC-CRYO | Thie MOOC aims to provide an introduction to the latest EO methods and the next generation of satellite platforms to monitoring the dynamic behaviour of the Earth's cryosphere. | Imperative Space (GovEd Ltd) (GB) | Science | cryosphere, science | Thie MOOC aims to provide an introduction to the latest EO methods and the next generation of satellite platforms to monitoring the dynamic behaviour of the Earth’s cryosphere. |
| MOOC4LAND – DEVELOPING A MASSIVE OPEN ONLINE COURSE ON EO LAND APPLICATIONS | The key objective of the proposed project is the development and deployment of a massive open online course (MOOC) to convey the spectrum o applications of Earth Observation (EO) over land surfaces. The first course is part of a series of [...] | EARTH OBSERVATION SERVICES GMBH (DE) | Science | land, mooc, training and education | The key objective of the proposed project is the development and deployment of a massive open online course (MOOC) to convey the spectrum o applications of Earth Observation (EO) over land surfaces. The first course is part of a series of online learning materials that will give insights on the potential of remote sensing technologies for applications over land surfaces. Here, you have the chance to learn about a variety of theoretical basics of remote sensing that will give you an understanding of how remote sensing works and it will enable you to follow along in the more practical courses that will be available on our website in the near future. In addition, a series of more application focussed MOOCs is produced covering the following fields: Urban Spaces People, Land, Sustainability Hazards & Disasters Agriculture & Food Forest Ecosystems Dry Ecosystems Wet Ecosystems |
| MULTI ACTOR FOREST INFORMATION SERVICE (MAFIS) | The MAFIS project will develop and demonstrate at pre-operational level a service aimed at providing consistent and statistically reliable information on forests, by combining multi-spectral satellite data and SAR data, to monitor natural and [...] | GMATICS SRL (IT) | Digital Platform Services | forestry, generic platform service, SAR | The MAFIS project will develop and demonstrate at pre-operational level a service aimed at providing consistent and statistically reliable information on forests, by combining multi-spectral satellite data and SAR data, to monitor natural and planted forests growth and forest losses due to human activities or to natural phenomena. The project will develop a specific methodology and will use Artificial Intelligence to routinely produce, at affordable customer price, high accuracy information consistent at local and supranational level. The resulting MAFIS service will provide information useful to different end-users both in the public domain (European, national and local level) and in the industrial domain (forest owners/producers, forestry companies and wood-forestry value chain). The project will develop Artificial Intelligence algorithms (Neural Networks, Random Forest and Expert Systems) to speed-up data analysis and information extraction and will implement a software procedure suitable to run on a cloud infrastructure. The MAFIS service will be accessible through a delivery platform already developed by GMATICS that will be adapted to enable effective visualization of the forest related information for different users. The achievement of the project objectives will be demonstrated over two test areas in Italy through comparison of the results obtained from the MAFIS methodology and software procedure with in-situ survey data. The scalability of the software procedure will be demonstrated through testing it on the ONDA DIAS over two large areas, one in Italy and one in another country, to be selected on the basis of interest obtained from the communication and promotion activities. The usefulness of the information content provided by MAFIS will be validated by the participation of the end-user partners in the analysis of the project results. |
| MULTI-FLEX: towards a strategy for fluorescence monitoring at multiple scales within the context of the FLEX/S-3 tandem mission | Living Planet Fellowship research project carried out by Marco Celesti. The future FLEX/Sentinel-3 tandem mission will provide unique information on vegetation dynamics by exploiting Sun-induced fluorescence and reflectance at the [...] | UNIVERSITY OF MILANO BICOCCA (IT) | Science | biosphere, carbon cycle, carbon science cluster, land, living planet fellowship, science, Sentinel-3 | Living Planet Fellowship research project carried out by Marco Celesti. The future FLEX/Sentinel-3 tandem mission will provide unique information on vegetation dynamics by exploiting Sun-induced fluorescence and reflectance at the unprecedented spatial scale of 300m x 300m. This magnified view into the photosynthetic machinery will enhance our ability to face the actual and future challenges related to food production and to the interactions between natural ecosystems and the climatic and biogeochemical Earth system. Towards the FLEX mission, a lot of technical and scientific development is ongoing in order to build up the knowledge necessary to translate this spectral information into a meaningful and concrete way to retrieve photosynthesis from space. Within this context, the ATMOFLEX project started in February 2018 with the main aim of collecting Sentinel-3A measurements and collocated ground observations characterizing the state of the atmosphere for an extended period of time. As a core objective of ATMOFLEX, several sites have been instrumented with state-of-the-art hyperspectral spectroradiometers continuously measuring over the vegetation. Moreover, for a limited period of time, Sentinel-3B OLCI data in a FLEX-like configuration will be acquired, together with airborne acquisition with the FLEX airborne demonstrator (HyPlant). This will bring the unique opportunity of a multi-scale, multi-platform dataset acquired with fluorescence-capable devices, over a coherent time and geographical frame. This project is focused in exploiting the potential of fluorescence and reflectance to describe photosynthetic dynamics, by exploiting the dataset acquired within the ATMOFLEX project, developing a flexible tool built on physically based RTMs for retrieving information about vegetation biophysical/biochemical parameters and Sun-induced fluorescence, capable of dealing with multiple spectral and spatial resolution data. High level parameters retrieved from model inversion such as the fluorescence quantum efficiency will be compared with simpler fluorescence- and reflectance based metrics proposed to track vegetation photosynthetic dynamics or to correct for mixed pixel problems arising at the spatial scale offered by satellite observations. Apart from contributing to the development of an innovative approach for a coupled retrieval of fluorescence and vegetation parameters, the direct benefit of this approach would be to enrich the dataset of the ATMOFLEX sites with consistent data that can be further exploited at a later stage. Moreover, the multi-scale approach proposed in this project will improve our understanding of the link between punctual measurements performed on the ground and satellite observation in the context of the future FLEX cal/val activities, a fundamental step towards the creation of robust and reliable products out of the mission. |
| Multiple THreats on Ocean health (MiTHO) | A healthy ocean regulates Earth’s climate and mitigates climate changes by absorbing heat and human-induced CO2 emissions. It serves also as a significant service provider supporting marine ecosystems’ integrity and resilience, and providing [...] | CNR-INSTITUTE OF MARINE SCIENCES-ISMAR (IT) | Science | ocean, ocean health flagship, ocean science cluster | A healthy ocean regulates Earth’s climate and mitigates climate changes by absorbing heat and human-induced CO2 emissions. It serves also as a significant service provider supporting marine ecosystems’ integrity and resilience, and providing resources. Maintaining a healthy ocean is thus key for a sustainable life on Earth. With the rising of atmospheric CO2 concentration, ocean’s health is at risk. The ocean is warming, acidifying, and losing its oxygen content (i.e., ocean deoxygenation). Intensified hydrological cycle and altered ocean-atmosphere heat exchange are expected to increase magnitude and frequency of extreme weather events. Our knowledge about the co-occurrence of such extreme multistressor events, when a system is far outside the norm, is relatively limited. The impact of combined extreme events is expected to be very high given the reduced time for biological adaptation, potentially leading to dramatic losses of biodiversity, increased desertification and shifts in species composition and propagating up to higher trophic levels to fish stocks with severe consequences on blue economy sectors (fishing, aquaculture). However, an integrated view of how these combined extreme events in the ocean unfold in time and space and a mechanistic understanding of the relevant processes is missing. The MultIple THreats on Ocean health (MiTHo) project aims at developing innovative EO-based multistressor cumulative hazard indexes, by exploiting the latest EO-based products achieved within the ESA Ocean Science cluster projects – CAREHeat, BOOMs, BiCOME, OceanSODA, MAXSS, Sargassum, SOON, EO4SiBS, PHYSIOGLOB – combining multi-mission independent EO-based datasets, for the detection of extreme events in warming, ocean pH, winds and river inputs, and up to in-situ (BGCArgo) and modelled O2 data for hypoxia an ocean deoxygenation detection. This project will assess the cumulative impact of multiple climate and anthropogenic stressors on key ecosystem services -biodiversity, phytoplankton biomass, macroalgae biomass, zooplankton biomass, fish biomass, food provisioning and costal protection, spanning at different temporal scales, and advance our ability to understand, monitor and predict oceans’ health. Blending EO remote sensing data with in-situ measurements and numerical model outputs, through ML techniques MiTHo will reconstruct dissolved O2 vertical profiles and provide novel EO-based avenues to monitor deoxygenation and from space. |
| Nemo-RBS: Nemo-HD Microsatellite for River Basin Scannings and Observations of SDG Hotspots | The Nemo-HD microsatellite was recently launched by SPACE-SI. This is a very agile multi-payload spacecraft that explores new EO concepts by combining multispectral imaging with video acquisitions for low latency and real-time EO services. In [...] | Centre of Excellence for Space Sciences and Technologies (SPACE-SI) (SI) | Enterprise | rivers, Sentinel-2 | The Nemo-HD microsatellite was recently launched by SPACE-SI. This is a very agile multi-payload spacecraft that explores new EO concepts by combining multispectral imaging with video acquisitions for low latency and real-time EO services. In this project the remarkable capabilities of the Nemo-HD microsatellite will be applied to rapidly prototype new EO operations dedicated to River Basin Scannings (RBS) where several very useful features of Nemo-HD will be integrated and validated. The technical characteristics of Nemo-HD together with its advanced Guidance, Navigation and Control systems make the satellite so agile and GNC-capable that it can conveniently track and monitor across-track features such as long rivers in order to acquire multispectral data and video at a GSD of at least 2.8 m with a 10 km swath. It is expected that Nemo-HD will thus complement Copernicus Sentinel-2 data for river basin EO products. The outputs will apply rapid prototyping and validation for RBS operations in the Danube and Ionian-Adriatic macroregions. |
| NEW PLANT BREEDERS USING EO (NEWBIE) | Plant breeding is the science of changing the traits of plants, in order to produce desired characteristics. Plant breeding has been practiced by farmers since the dawn of agriculture, as they selected plants for larger seeds, tastier fruits, [...] | AGROAPPS PC (GR) | Enterprise | agriculture, permanently open call | Plant breeding is the science of changing the traits of plants, in order to produce desired characteristics. Plant breeding has been practiced by farmers since the dawn of agriculture, as they selected plants for larger seeds, tastier fruits, and other valuable traits. In other words, the goals of plant breeding are to produce crop varieties that boost unique and superior traits for a variety of agricultural applications, a process which may last up to 12 years. NEWBIE is an Assistance Tool for crop selection that aims to improve the selection efficiency of the breeding programs, accelerating genetic gain and reducing the costs. More specifically, NEWBIE Assistance Tool will be based on the combination of Proximal Phenotyping and Remote Sensing Phenotyping. Proximal phenotyping will be used in the early breeding stages, under multiple location trials that include small size plots and many seed varieties. Remote Sensing Phenotyping will be combined with proximal phenotyping at later breeding stages, established at larger plot sizes. Both types of phenotyping combined with climate intelligence and coupled with machine learning and artificial intelligence techniques, will allow for a comparison of multi-temporal feature datasets through the Assistance Tool for crop selection. The result of the process will be the identification of optimal performing candidates that can be used for further breeding, in less time and with less resources than conventional breeding requires, while also building the know-how on the varieties that better suit specific areas of interest. |
| NOvel cOmputational methoDs for reLiablE SAteLlite-based Air quality Data (NOODLESALAD) | NOODLESALAD aims to develop computational methods for improving the satellite-based air quality estimates. More specific, it will concentrate on improving the air quality key indicator PM2.5, which is the dry mass concentration of fine [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | Altitude, atmosphere, atmosphere science cluster, permanently open call, Sentinel-3 | NOODLESALAD aims to develop computational methods for improving the satellite-based air quality estimates. More specific, it will concentrate on improving the air quality key indicator PM2.5, which is the dry mass concentration of fine particulate matter with an aerodynamic diameter of less than 2.5 micrometers (micrograms per cubic meter of air). This activity will be developing a novel artificial intelligence approach for retrieving PM2.5 from earth observation data. The innovative strategy will be based on machine learning post-process correction that we recently developed. The novel approach will utilize an innovative fusion of Sentinel-3 satellite data, simulation model information, ground-based observations, traditional satellite retrieval techniques, and machine learning to produce satellite-based PM2.5. In this development work, data from the year 2019 will be used and select Central Europe as region of interest. The project will produce and validate PM2.5 estimates with a high spatial resolution of 300 meters for the Sentinel-3 satellites overpasses. In addition, this prototype approach will be used to create high temporal resolution air quality datasets for 5-10 European cities. Finally, the PM2.5 datasets produced will be publicly shared together with an open-source code package for Sentinel-3 PM2.5 retrieval. |
| Ocean CIRculation from ocean COLour observations (CIRCOL) | The monitoring of the oceanic surface currents is a major scientific and socio-economic challenge. Ocean currents represent one of the fundamental elements that modulate natural and anthropogenic processes at several different space and time [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | climate, ocean science cluster, oceans, permanently open call, science | The monitoring of the oceanic surface currents is a major scientific and socio-economic challenge. Ocean currents represent one of the fundamental elements that modulate natural and anthropogenic processes at several different space and time scales, from global climate change to local dispersal of tracers and pollutants, with relevant impacts on marine ecosystem services and maritime activities (e.g. optimization of the ship routes, maritime safety, coastal protection). An appropriate monitoring of the oceanic currents must rely on high frequency and high resolution observations of the global ocean, which are achieved using satellite measurements. At present, no satellite sensor is able to provide a direct measurement of the ocean currents – The indirect and synoptic retrieval of the large-scale geostrophic component of the sea-surface motion is given by satellite altimetry at a spatial (~100km) and temporal (~one week) resolution which is not sufficient for many applications, even more in semi-enclosed basins as the Mediterranean Sea where the most energetic variable signals are found at relatively small scales. In this context, the objective of the CIRCOL (Ocean Circulation from Ocean Colour Observations) project is to improve the retrieval of altimeter-derived currents in the Mediterranean Basin combining the largescale, altimeter-derived geostrophic currents with the high-resolution dynamical information contained in sequences of satellite-derived surface Chlorophyll (Chl) observations. The project will be implemented in two phases. During Phase 1, an Observing System Simulation Experiment (OSSE) based on CMEMS (Copernicus Marine Environment Monitoring Service) physical and biogeochemical models will be implemented to investigate the potentialities of the proposed approach for the improvement of the altimeter derived currents. During Phase 2, the optimal Chl-based reconstruction of the sea-surface currents will be implemented using the satellite-derived multi-sensor, L4 (gap-free) altimeter and sea-surface Chl for the Mediterranean Sea distributed by CMEMS. The resulting products will be validated against in-situ velocity measurements (drifting buoys, HF radar). |
| OCEAN HEALTH – OCEAN ACIDIFICATION | As a third project in the EO for Ocean Acidification pathway, the objectives of the current efforts are: (i) to advance the scientific state-of-the-art in Ocean Acidification and its impact on marine life and ecosystems; (ii) to develop [...] | UNIVERSITY OF EXETER (GB) | Science | carbon cycle, marine environment, ocean, Ocean Indicators | As a third project in the EO for Ocean Acidification pathway, the objectives of the current efforts are: (i) to advance the scientific state-of-the-art in Ocean Acidification and its impact on marine life and ecosystems; (ii) to develop the next generation of EO-based products by capitalizing on the synergistic opportunities offered by the increasing fleet of European satellites together with in-situ observations, advanced models and novel technologies; and (iii) to assess how these novel products and related knowledge can be transferred into innovative solutions for society. In particular, a suite of validated high-resolution (weekly and 0.25º) EO-based carbonate system products will be developed and used in three Scientific Case Studies and three downstream Impact Case Studies involving identified ocean conservations stakeholders. |
| Ocean Virtual Laboratory | The aimof this activity is To exploit the synergy between Sentinel instruments and other mission EO datasets together with in situ measurements in complex waters and improve scientific understanding of ocean and coastal processes and impacts.The [...] | OCEANDATALAB (FR) | Science | altimeter, carbon cycle, carbon science cluster, CryoSat, oceans, platforms, Sentinel-1, Sentinel-2, Sentinel-3 | The aimof this activity is To exploit the synergy between Sentinel instruments and other mission EO datasets together with in situ measurements in complex waters and improve scientific understanding of ocean and coastal processes and impacts.The main objective of the project is to develop a virtual plateform to allow oceanographers to discover the existence and then to handle jointly, in a convenient, flexible and intuitive way, the various co-located EO datasets and related model/in-situ datasets over dedicated regions of interest with a different multifacet point of view. This is first demonstrated over the Agulhas region. Developed tools shall foster the emergence of new methods prototype and products making use of the complementarity between sensors to study ocean related processes. The tool shall also provide the best possible visibility on the upcoming Sentinel1/2/3 datatakes to help plan and coordinate with field campaign. The OVL is filling the gap between Space agencies data portals that distributes specific EO data and analysis software like IDL/ENVI or Matlab that are more suitable for in-depth analysis of a given dataset. A few GIS systems such as Google Earth are able to import several data layers but very little interaction with data (apart for basic layer transparency) is possible. The project scientific committee has to ensure that the developed OVL is providing significant added value and is not duplicating existing efforts in the international community. Scientists in the consortium shall ensure that OVL is built for scientists and with a large beta-tester community and response effectiveness to satisfy most needs of a rather versatile community. |
| OPEn platform for the Retrieval of Aerosol and CO2 from S5 (OPERA-S5) | The aim of the OPEn platform for the Retrieval of Aerosol and CO2 from S5 (OPERA-S5) project is to develop a totally modular open scientific platform for the combined retrieval of CO2, CH4, aerosol and surface properties based on GRASP [...] | GRASP-SAS (FR) | Science | Aerosols, air quality, atmosphere, atmosphere science cluster, platforms, Sentinel-5, Sentinel-5P, Surface Radiative Properties | The aim of the OPEn platform for the Retrieval of Aerosol and CO2 from S5 (OPERA-S5) project is to develop a totally modular open scientific platform for the combined retrieval of CO2, CH4, aerosol and surface properties based on GRASP (Generalized Retrieval of Atmosphere and Surface Properties) code with the measurements of Sentinel-5 spectrometer UVNS as stand alone, and in combination with the Multiangular Polarimeter 3MI. This new open platform will allow state-of-the-art characterization of atmospheric and surface properties. But also, thanks to its modular architecture, it will serve as a scientific hub for the development of new modeling and retrieval techniques based on AI methodologies. Two of the main challenges to reach the accuracy requirements in the retrieval of GreenHouse gas concentrations from spaceborne sensors are the scattering elements (aerosol and surface) and the computationally expensive calculations involved in the hyperspectral gas absorption features. OPERA-S5 platform tackles both of them by taking advantage of the highly accurate aerosol and surface characterization of GRASP with Multiangle-Polarimetric measurements and the acceleration possibilities offered by AI based approaches. |
| OPEN SAR LIBRARY (AlignSAR) | The AlignSAR project aims to provide FAIR-guided open datasets and tools designed for SAR applications, ensuring interoperability and consistency with existing and upcoming initiatives and technologies. The project facilitates a wider [...] | UNIVERSITY OF TWENTE (NL) | Science | open science, platforms, SAR, Sentinel-1 | The AlignSAR project aims to provide FAIR-guided open datasets and tools designed for SAR applications, ensuring interoperability and consistency with existing and upcoming initiatives and technologies. The project facilitates a wider exploitation of SAR data and its integration and combination with other datasets. The project aims to achieve the following objectives: Define a procedure for creating SAR benchmark datasets for machine learning applications. Develop a reference, quality-controlled, documented, open benchmark datasets of SAR spatial and temporal signatures of complex real-world targets with high diversity to serve a wide range of applications with societal relevance. The database will respect FAIR (Findable, Accessible, Interoperable, Reproducible) and Open Science principles. Create the database considering both open and closed SAR missions (including at minimum Sentinel-1), maximizing the geographical and temporal coverage, and integrating and aligning multi-SAR images and other geodetic measurements in time and space. Define a specification of the signatures and their associated descriptors so that they can be easily indexed, programmatically searched, and retrieved. Develop an open-source software library with associated documentation to create, describe, test, validate, and publish SAR signatures, and expand the database. Demonstrate, test, and validate the Open SAR Library (database and open-source software) on at least two use cases for machine learning applications. Ensure long-term availability of the database and open-source library, potentially through integration with other relevant open platforms and tools. |
| openEO platform: a Federated Open Earth Observation Platform | openEO platform is being implemented as a versatile cloud-based processing and analytics environment for Earth Observation data. It is being established to address the prevailing capability gap in cloud-based platforms for big EO data [...] | EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT) | Digital Platform Services | generic platform service, platforms, Sentinel-1, Sentinel-2 | openEO platform is being implemented as a versatile cloud-based processing and analytics environment for Earth Observation data. It is being established to address the prevailing capability gap in cloud-based platforms for big EO data processing and analytics. The concepts builds on a federated architecture with initial deployments in EODC, TerraScope, CreoDIAS and the EuroDataCube. openEO platform is a collaborative effort of a experienced European consortium, consisting of partners with strong expertise in cloud platform operation and development, EO science and service provisioning: EODC (AT), VITO (BE), Sinergise (SI), EURAC (IT), EGI (NL) and University Muenster (DE). Additional in kind support is provided by GEO. The current federated architecture includes backends in EODC, VITO Terrascope and CreoDIAS while EuroDataCube is utilised for data access in additional cloud environments. Several guiding principles govern the implementation of openEO platform. These include: • Abstracting the complexity of processing and analytic operations through intuitive, high-level API, processes and front end libraries; • Providing full flexibility and scalability from pixel- to continental level; • Ensuring transparency, confidentiality, scientific integrity and reproducibility; The agile open source development is following 9 key use cases that incrementally enhance the capabilities of openEO platform. The first ones that have been addressed include on-demand Analysis Ready Data generation for SAR and multi-spectral data, systematic feature engineering and time series based change detection. |
| Operational Snow Avalanche Detection Using Sentinel-1 | NORUT has developed an automatic avalanche detection method within a pre-operational processing chain that uses Sentinel-1 data to detect avalanches. This system is being tested in Northern Norway and is used operationally during winter [...] | NORTHERN RESEARCH INSTITUTE (NORUT) (NO) | Applications | applications, disaster risk, permanently open call | NORUT has developed an automatic avalanche detection method within a pre-operational processing chain that uses Sentinel-1 data to detect avalanches. This system is being tested in Northern Norway and is used operationally during winter 2017-2018 with the Norwegian Avalanche Warning Service. The goal of this project is to develop our avalanche detection processing chain to operational status anywhere on Earth, where Sentinel-1 data is available. This will be done by setting up the processing chain for five selected avalanche forecasting regions worldwide including Switzerland, North America and Northern Afghanistan with the aim to transfer the methodology to users with in mind the challenge of delivering consistent avalanche activity monitoring data. in space and time. |
| OPPORTUNITIES FOR WIDER USE OF CIVILIAN EARTH OBSERVATION IN COUNTER-PROLIFERATION | The aims for the study are: To summarize current understanding of the main proliferation related actors, threats and underlying processes and their evolution expected over the next 5 years. To identify organizations responsible for [...] | CSNSC Szolgáltató Korlátolt Felelős (HU) | Enterprise | natural hazards and disaster risk | The aims for the study are: To summarize current understanding of the main proliferation related actors, threats and underlying processes and their evolution expected over the next 5 years. To identify organizations responsible for collecting information and analysing threats and risks related to chemical, nuclear and radiological proliferation and their interaction. To review the information collection and analysis systems and methods operated by these organizations and identify gaps or constraints in information collection and analysis processes (both at present and with respect to potential threat/risk evolution). To identify information products of relevance for counter-proliferation derived from civilian EO satellites, characterize the extent to which these address the gaps and constraints in conventional information collection and analysis capabilities (both at present and with respect to potential threat/risk evolution) and elaborate the required levels of performance to be achieved for the EO data collection systems in order to ensure the identified gaps and constraints are comprehensively addressed. |
| OrthoVHR: Automatic Orthorectification Service For Very High-Resolution Optical Satellite Data | The main objective of this project is to develop a prototype automatic orthorectification service for optical satellite images that will be ready for deployment into the cloud. The project will specify, implement and test a service for [...] | ZRC SAZU – Research Centre of the Slovenian Academy of Sciences and Arts (SI) | Enterprise | permanently open call | The main objective of this project is to develop a prototype automatic orthorectification service for optical satellite images that will be ready for deployment into the cloud. The project will specify, implement and test a service for automatic orthorectification of optical high-resolution (HR) and very high-resolution (VHR) satellite images based on a prototype system (STORM) developed previously. The service will interface with existing elements in the European EO platform services ecosystem (eg thematic exploitation platforms, DIAS, etc) and will meet the demands of the remote sensing community and other public or private sector users interested in reliable, high accuracy and fast orthorectification of data for various applications. The primary objective is for the service to be easy to use, in particular by non-experts and this will be reflected in the primary user interface although other interface options will also be put in place. |
| OSIRIS FO – “OSIRIS FOLLOW-ON – OPTICAL AND SAR DATA AND SYSTEM INTEGRATION FOR RUSH IDENTIFICATION OF SHIP MODELS – FOLLOW-ON ” – EXP | The project is a follow up of the ESA funded OSIRIS project, aimed at developing a series of modules for maritime surveillance into a prototype deployed on a shared processing system with a tested full chain for Sentinel 1 and 2 data. The team [...] | MAPSAT TELERILEVAMNETO MEDITERRANEA (IT) | Enterprise | optical, SAR, Sentinel-1, Sentinel-2 | The project is a follow up of the ESA funded OSIRIS project, aimed at developing a series of modules for maritime surveillance into a prototype deployed on a shared processing system with a tested full chain for Sentinel 1 and 2 data. The team performed a survey on most commonly used spaceborne sensors for thermal infrared, selecting four sensors for the demonstration phase, characterized by better values of resolution and accuracy and different equatorial crossing times. The team set up the full chain of processing for Temperature maps extrapolation, based on processing of Top of the Atmosphere (ToA) radiance, brightness temperature at the sensor, and land masking. An impact assessment study was conducted the issue of calculating and using of the Sea Surface Temperature map instead of the atmospherically correct products. The interface of the Ship Detection module based on the CFAR detection algorithm is being updated for the ingestion of temperature map raster. As for the Ship Classification module, the ground-truth database has been finalized. The feature extraction code was modified to automatize the access to OpenSARShip ( open dataset), and to provide the updated features, which are being reconsidered during the study of the classification algorithms. The team is working to improve the ship classification methods from SAR HR images, focusing on Random Forest algorithm, with average accuracies of about 70% for noisy data and 80% for ground-truth data, on four ship types, compared to other methods (Naive Bayes and Multiple Kernel Learning). The kinetic parameters extraction module exploits single look complex (SLC) SAR images and a clutterlock algorithm to estimate the doppler frequency shift. The team is also advancing Ship Behaviour Analysis based on Sentinel 2 and sat- AIS historical datasets from AstraPaging and ExactEarth. |
| OVALIE: Oceanic intrinsic Variability versus Atmospheric forced variabiLIty of sea level changE | Living Planet Fellowship research project carried out by William Llovel and Alice Carret. Global mean sea level rise is one of the most direct consequences of actual global warming. Since the beginning of the 20th century, global mean sea [...] | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) (FR) | Science | living planet fellowship, ocean science cluster, oceans, science | Living Planet Fellowship research project carried out by William Llovel and Alice Carret. Global mean sea level rise is one of the most direct consequences of actual global warming. Since the beginning of the 20th century, global mean sea level experiences an unabated increase of 1.1-1.9 mm.yr-1 recorded by tide gauges. Based on satellite altimetry and since 1993, global mean sea level rises at a higher rate of 3 mm.yr-1. This higher rate denotes a possible acceleration in this global rise. Actual global mean sea level rise mainly reflects global ocean warming (through thermal expansion of sea water) and land ice melt (from Greenland, Antarctica and mountain glaciers). Monitoring precisely these climate variables is mandatory to better understand processes at work under current global warming and to validate climate models used for projections. Careful investigations of these observations jointly with state-of-the-art numerical simulations have also helped for interpreting these changes and underlying mechanisms. Some of these joint observational/numerical investigations have demonstrated that the evolution of the ocean in the turbulent regions has a stochastic character even over interannual to multidecadal periods. This stochastic character of the ocean is known as intrinsic variability. This latter is poorly known in the global ocean despite its recently acknowledged contribution to the oceanic variability. Thus, this intrinsic variability may bias our interpretation of low-frequency variability of the ocean. One barely knows the temporal and spatial signature of the intrinsic variability, the precise footprints of this intrinsic variability as a function of depth and its signature on observations. Furthermore, we do not have enough knowledge on how this intrinsic variability contributes to the recent regional sea level change and its contributions such as temperature, salinity and mass changes. Therefore, the atmospheric evolution may force a variety of long-term oceanic variability. This means that the most accurate satellite/in situ observations can describe the atmospheric forced variability along with the chaotic ocean intrinsic changes. The OVALIE project proposes to scientifically investigate and partition the respective contribution of the atmospheric forced variability versus the oceanic intrinsic variability for the sea level observations (satellite data -based on Topex/Poseidon, Jason 1-2-3, ERS1, ERS2, ENVISAT, Altika and GRACE- and in situ measurements –based on Argo floats and other in situ measurements). |
| Ozone Recovery from Merged Observational Data and Model Analysis (OREGANO) | Stratospheric ozone (the “ozone layer”) protects the biosphere from harmful UltraViolet (UV) radiation. Ozone (O3) is expected to recover as a consequence of the Montreal Protocol signed in 1987 and its Amendments regulating the phase-out of [...] | UNIVERSITY OF BREMEN (DE) | Science | Altitude, atmosphere, atmosphere science cluster, atmospheric chemistry, science | Stratospheric ozone (the “ozone layer”) protects the biosphere from harmful UltraViolet (UV) radiation. Ozone (O3) is expected to recover as a consequence of the Montreal Protocol signed in 1987 and its Amendments regulating the phase-out of ozone-depleting substances (ODS). The stratospheric halogen amount (mainly bromine and chlorine) released by ODSs reached its maximum abundance in the middle of the 1990s. Observations from satellites and the ground confirmed that the long-term decline of stratospheric ozone was successfully stopped. Future, stratospheric ozone levels do not only depend on changes in ODS but also on changes in greenhouse gases (GHG) and possibly stratospheric aerosols. The latter modifies both ozone chemistry and dynamics (transport, circulation) of ozone. The rate of ozone recovery thus depends on the geographic region and altitude. In some altitude domains like the lower tropical stratosphere, ozone will likely continue to decline according to the majority of chemistry-climate models. At middle latitudes, the current trends in lower stratospheric ozone remain highly uncertain in part due to larger uncertainties in observational data and larger year-to-year variability in ozone. The major goal of the OREGANO project is to advance our understanding of ozone recovery using a combination of observations and model analyses. The study topics in this project are: Long-term ozone column and profile trends from models and observations; Impact of atmospheric dynamics and chemistry on polar and extrapolar ozone; Role of tropospheric ozone in column ozone trends; Evaluation of the bromine monoxide – chlorine monoxide (BrO-ClO) cycle using nadir BrO and chlorine dioxide (OClO) observations; Impact of aerosol and GHG changes on stratospheric ozone trends (past and future). Recommendations for future satellite missions and programs shall be made following the results of this study in support of continued ozone monitoring. |
| PACIFIC | Global mean sea level (GMSL) is considered one of the leading indicators of global climate change as it reflects changes taking place in different components of the climate system. Present-day sea level rise and its acceleration, currently [...] | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) (FR) | Science | altimeter, climate, living planet fellowship, ocean, science | Global mean sea level (GMSL) is considered one of the leading indicators of global climate change as it reflects changes taking place in different components of the climate system. Present-day sea level rise and its acceleration, currently estimated by high-precision satellite altimetry measurements, are primarily driven by anthropogenic global warming, more specifically by ocean warming-induced thermal expansion, and ice mass loss from glaciers, Greenland and Antarctica. Since the early 1990s, sea level is measured by high-precision satellite altimeters, that allow the monitoring of sea level change from global to regional scales. In addition, various observing systems from space (e.g., GRACE and GRACE-FO) and in situ (e.g., Argo floats) are used to monitor the components of the sea level variability. Ocean model simulations have revealed that besides the atmospherically-forced variability(AFV) of sea level, a strong low-frequency chaotic intrinsic variability (CIV) spontaneously emerges from the ocean. Recent studies have disentangled the imprints of AFV and CIV on the inter annual variability and on the trends of regional sea level. Results indicate that very low-frequency chaotic ocean variability may hinder the unambiguous attribution of regional sea level trends to the atmospheric forcing over 38% of the global ocean area. Another study showed that the chaotic part of the inter annual (1993-2015) sea level variability exceeds 20%over 48%of the global ocean area; these fractional areas are 48% and 26% for steric and manometric sea level, respectively. However, the frequency distribution and the spatial structure of the chaotic variability have not been studied yet. The first goal of this project is to quantify, for the first time as a function of frequency (temporal scales from 10 days to 36 years) and within each oceanic region, the chaotic and atmospherically-forced variability of sea level observations (satellite data from the ESA CCI project, Argo floats and GRACE and GRACE-FO). The second goal is to adapt and extend an existing filtering method to attenuate the imprint of chaotic variability on observational fields of sea level (steric and manometric) components. This study will also help identify the mechanisms that are revealed by the regional patterns of chaotic sea level variability. |
| PASS-SWIO | PASS-SWIO, a project funded by ESA (via the Permanent Open Call), aims to establish a sea level monitoring system for Madagascar based on the installation and deployment of a low-cost relocatable tide gauge (Portagauge). Portagauge uses GNSS [...] | National Oceanography Centre (NOC) (GB) | Science | coastal zone, permanently open call, science, tides | PASS-SWIO, a project funded by ESA (via the Permanent Open Call), aims to establish a sea level monitoring system for Madagascar based on the installation and deployment of a low-cost relocatable tide gauge (Portagauge). Portagauge uses GNSS interferometric reflectometry (GNSS-IR) technology alongside a conventional radar. By combining these measurements with the analysis of satellite altimeter sea level data we will provide validation and wider scale knowledge of sea-level variability. Madagascar has very limited tidal prediction, primarily based on model data. It has no national sea level monitoring capability. There is currently only one functioning tide gauge station. A previous tide gauge, in the cyclone-prone north of the island, was destroyed several years ago. The project partners will work with the national Madagascar Meteorological Agency (DGM – Direction Générale de la Météorologie). DGM will take responsibility for the local maintenance and operation of the Portagauge. They will also receive training to carry out the data processing and analysis of tide gauge and satellite altimeter data. Discussions will be held with key stakeholders to review the project and agree a long-term Road Map for the sustainable implementation of a national sea-level monitoring system for Madagascar. This will serve as model for other island states and coastal countries in the South West Indian Ocean (SWIO) region and beyond. If you would like to access any of the data sets produced, please contact the Project Manager via the Project website. The Kick Off meeting was held on 5 May 2022. The activity has a duration of one year. |
| PEOPLE – Ecosystem Restoration | The UN Decade on Ecosystem Restoration focus on the restoration of ecosystems on a large scale to achieve the United Nations sustainable development agenda in 2030. The PEOPLE Ecosystem Restoration project will develop innovative products and [...] | HATFIELD CONSULTANTS (CA) | Applications | applications, Ecosystems, environmental impacts, forestry, sustainable development | The UN Decade on Ecosystem Restoration focus on the restoration of ecosystems on a large scale to achieve the United Nations sustainable development agenda in 2030. The PEOPLE Ecosystem Restoration project will develop innovative products and indicators determining and monitoring processes, both degradation and/or recovery. In several pilot sides in various ecosystems like boreal peatland and forests, temperate forests, and tropical wetlands and forest biomes, it will distinguish fast or slow dynamic processes, like meteorological conditions, seasonal conditions, climate long-term variability, human actions affecting the health of the ecosystem. It will prepare the future roadmap for subsequent studies with a larger deployment in terms of both the geographic region and user communities. |
| PHAB-IV: PHAse-Based sentinel-1 Ice Velocity | The project aims to develop the technical basis for an advanced Sentinel-1 Ice Velocity (IV) product for ice sheets and ice caps with improved spatial resolution and accuracy, based on Sentinel-1 interferometric phase measurements. | Technical University of Denmark (DK) | Science | Glaciers and Ice Sheets, permanently open call, polar science cluster, science, Sentinel-1 | The project aims to develop the technical basis for an advanced Sentinel-1 Ice Velocity (IV) product for ice sheets and ice caps with improved spatial resolution and accuracy, based on Sentinel-1 interferometric phase measurements. |
| PHOTOPROXY: TECHNICAL ASSISTANCE FOR THE PHOTOSYNTHETIC-PROXY EXPERIMENT | In few years from now, ESA’s BIOMASS and FLEX Earth Explorers satellite missions will open a new opportunity to enhance our knowledge of the global carbon cycle. In particular, the scientific exploitation of BIOMASS and FLEX in synergy with the [...] | FORSCHUNGSZENTRUM JUELICH GMBH (DE) | Science | Biomass, biosphere, carbon cycle, carbon science cluster, FLEX, land, science | In few years from now, ESA’s BIOMASS and FLEX Earth Explorers satellite missions will open a new opportunity to enhance our knowledge of the global carbon cycle. In particular, the scientific exploitation of BIOMASS and FLEX in synergy with the Sentinel satellite series and other existing and future missions (e.g. CMOS, GEDI, NISAR, Tandem-X/L) will provide an unprecedented opportunity to better understand and characterize the different components of the carbon cycle and its dynamics. Preparing for the fast exploitation of this unique and unprecedented observational capacity, ESA has launched the Carbon Science Constellation Initiative. This initiative will be implemented through a cluster of different studies, research activities, campaigns and tool development efforts dedicated to support the scientific community to explore the potential synergies between different Earth Observation approaches and maximize the scientific impact of this unique set of sensors for carbon cycle research. With the PhotoProxy project, we address relevant open aspects that are related to the quantitative assessment of vegetation photosynthesis and vegetation stress from space. In the past years the fluorescence signal that is emitted from the core of the photosynthetic apparatus during photosynthetic energy conversion, has become the most promising indicator of actual photosynthetic rates. In 2012, the European Space Agency has selected the FLEX satellite mission to become ESA’s 8th Earth Explorer mission (Drusch et al. 2017). FLEX will be the first dedicated fluorescence mission that will provide global maps of both peak of the fluorescence signal on a high spatial resolution and relevant revisiting time. In addition to fluorescence, which can be measured across various scales ranging from the single leaf to the ecosystem (Rascher et al 2015, Wieneke et al 2018), in recent years, alternative approaches to the remote detection of photosynthetic carbon fluxes (photosynthesis or gross primary productivity, GPP) have been proposed. These approaches include reflectance-based measures by NIRv (Badgely et al. 2017) and CCI (Gamon et al. 2016), which are both related to pigment and structurally-based changes in vegetation [see Fig below as an example for the complementary information content of the different remote sensing measures]. Together, these remote sensing approaches offer a way to revolutionize our assessment of photosynthetic carbon uptake and vegetation health from space. However, major questions remain regarding the exact function of each of these signals and their relationship to each other. There are several indications that fluorescence may be the best remote sensing parameter to constrain predictions of CO₂ uptake rates, but we expect that a combination of the different measures will provide the best estimates of actual vegetation function. Thus with this activity we are working in an international consortium to address the following objectives: Test the applicability of the recently developed reflectance indices CCI and NIRv to track diurnal and seasonal vegetation dynamics. Perform a comparison of CCI, NIRv and solar induced chlorophyll fluorescence to better judge the quality of the different approaches to understand and model vegetation dynamic. Compare a benchmark dataset of those parameters to flux estimates from airborne and ground-based systems. Determine the scale-dependence (temporal and spatial) of the correlation between each optical metric and photosynthetic carbon uptake. Determine the factors that confound the interpretation of reflectance-based signals, and the conditions under which these occur. Determine the degree by which physiological regulation and structural adjustments influence each signal. Related publications Badgley G, Field C.B. and Berry J.A. (2017) Canopy near-infrared reflectance and terrestrial photosynthesis. Science Advances, 3; e1602244 Drusch M., Moreno J., Del Bello U., Franco R., Goulas Y., Huth A., Kraft S., Middleton E., Miglietta F., Mohammed G., Nedbal L., Rascher U., Schüttemeyer D. & Verhoef W. (2017) The FLuorescence EXplorer mission concept – ESA’s Earth Explorer 8. IEEE Transactions on Geoscience and Remote Sensing, 55, 1273-1284 Gamon J.A., Huemmrich K.F., Wong C.Y.S, Ensminger I., Garrity S., Hollinger D.Y., Noormets A., Peñuelas J. (2016) Photosynthetic phenology of evergreen conifers. Proceedings of the National Academy of Sciences, 113 (46), 13087-13092 Rascher U., Alonso L., Burkart A., Cilia C., Cogliati S., Colombo R., Damm A., Drusch M., Guanter L., Hanus J., Hyvärinen T., Julitta T., Jussila J., Kataja K., Kokkalis P., Kraft S., Kraska T., Matveeva M., Moreno J., Muller O., Panigada C., Pikl M., Pinto F., Prey L., Pude R., Rossini M., Schickling A., Schurr U., Schüttemeyer D., Verrelst J. & Zemek F. (2015) Sun-induced fluorescence – a new probe of photosynthesis: First maps from the imaging spectrometer HyPlant. Global Change Biology, 21, 4673–4684 Wieneke S., Burkart, A., Cendrero-Mateo M. P., Julitta T., Rossini M., Schickling A., Schmidt M., Rascher U. (2018) Linking photosynthesis and sun-induced fluorescence at sub-daily to seasonal scales. Remote sensing of environment, 219, 247 – 258 [Book chapter]: J. Quiros-Vargas, B. Siegmann, A. Damm, R. Wang, J. Gamon, V. Krieger, B.S.D. Sagar, O. Muller, U. Rascher, “Fractal Geometry and the Downscaling of Sun-induced Chlorophyll Fluorescence Imagery” in Encyclopaedia of Mathematical Geosciences, B.S. Daya Sagar, Q. Cheng, J. McKinley, F. Agterberg, Eds. (Springer Nature, 2022) |
| PHYSIOGLOB: Assessing the inter-annual physiological response of phytoplankton to global warming using long-term satellite observations | Living Planet Fellowship research project carried out by Marco Bellacicco. Phytoplankton is considered to be responsible for approximately 50% of the planetary primary production and is at the basis of the trophic chain. Large scale factors [...] | ITALIAN NATIONAL AGENCY FOR NEW TECHNOLOGIES, ENERGY AND SUSTAINABLE ECONOMIC DEVELOPMENT (ENEA) (IT) | Science | carbon cycle, carbon science cluster, climate, living planet fellowship, ocean science cluster, oceans, science | Living Planet Fellowship research project carried out by Marco Bellacicco. Phytoplankton is considered to be responsible for approximately 50% of the planetary primary production and is at the basis of the trophic chain. Large scale factors such as climate, ocean circulation, and mostly anthropogenic activities, affect phytoplankton biomass and distribution. For all of these reasons, in the ocean, phytoplankton is defined as a sort of sentinel of changes in the ecosystem, because they rapidly respond to environment perturbations. Light, nutrients and temperature are the most important environmental variables that influence phytoplankton production. Phytoplankton cells respond to changes in light and nutrients with physiological strategies that enhance the efficiency of light capturing, photosynthetic capacity, growth and persistence. There are two different kinds of phytoplankton responses to light: photoadaptation and photoacclimation. The photoadaptation describes changes that might happen at genotype level, and are expected to occur at a long evolutionary time-scale. The photoacclimation is a cellular process that allows phytoplankton to change the intracellular chlorophyll-a concentration (Chl) in relation to environmental factors and it includes, among the others, regulation of the pigment amount and other components of the photosynthetic machinery. The temperature is the other main environmental agent that affects phytoplankton. It has been proved that ocean warming, mostly due to anthropogenic activities, causes an expansion of the low-Chl and low-productivity areas impacting strongly on marine ecosystem. The most important and easily observable mechanism due to photoacclimation is variation of the photosynthetic pigment concentration (i.e. Chl) at the cellular scale which is thus can be observed and quantified using space-borne observations. Photoacclimation can be described in terms of variation of the ratio between chlorophyll-a and carbon (Chl:C ratio). Unfortunately, this process is currently overlooked by standard operational ocean colour algorithms used to retrieve information about both the phytoplankton standing stock and production. PhysioGlob wants to study the inter-annual physiological response of phytoplankton to global warming using long-term satellite observations (i.e. entire ESA OC-CCI time-series) through the Chl:C ratio. Phytoplankton carbon could be estimated from the particle backscattering (bbp, λ). One of the most used and applied algorithm for bbp (λ) is the Quasi Analytical Algorithm (QAA). We want to re-evaluate retrieval of bbp (λ) over the global ocean with the QAA, using field data of remote-sensing reflectance (Rrs) and inherent optical properties (IOP), and then compare phytoplankton carbon with Chl to estimate the physiological signal. In order to study the trend and oscillation of this process we: i) study the single time series in separate M-SSA analyses to evaluate similarities among the inter-annual variabilities of the Chl:Cphyto ratio, SST, and phytoplankton indices also highlighting possible differences; ii) proceed with a joint M-SSA analysis of the time series to better understand the spatio-temporal structure associated with inter-annual variability in the Chl:Cphyto ratio or phytoplankton indices and global ocean temperature field. This coupled analysis will also help in addressing the question to which extent the inter-annual oscillatory modes found in the Chl:Cphyto ratio or phytoplankton indices can be attributed to its response to inter-annual variability in SST field. |
| Phytoplankton and fisheries under regional warming in the global oceans – POSEIDON | POSEIDON aims to understand the response of ocean ecosystems to climate warming and extreme events (e.g., marine heatwaves). Long-term trends (> 23 years) in phytoplankton ecological indicators (biomass, size structure and phenology) will be [...] | NATIONAL AND KAPODISTRIAN UNIVERSIT (GR) | Science | Biomass, biosphere, climate, living planet fellowship, oceans, science, SST | POSEIDON aims to understand the response of ocean ecosystems to climate warming and extreme events (e.g., marine heatwaves). Long-term trends (> 23 years) in phytoplankton ecological indicators (biomass, size structure and phenology) will be analysed in different regions, encompassing a range of conditions found in the global oceans. POSEIDON will further investigate the spatiotemporal variability of these indicators under oceanic warming, and examine links between phytoplankton, climate and fisheries. POSEIDON will employ a novel, multidisciplinary approach by integrating contemporary oceanographic datasets, including satellite remote sensing observations, in situ cruise data and Biogeochemical Argo (BGC-Argo) floats. Specific research objectives include: Use a combination of remotely-sensed and available in situ datasets to regionally-tune and validate existing algorithms for computing phytoplankton ecological indicators (biomass, phenology and size structure) in several case study regions of the global oceans. Apply a marine heatwave detection algorithm on long-term SST data (ESA SST-CCI) and construct an atlas that describes the spatiotemporal distribution of extreme heating events (marine heatwaves [MHWs]) within the regions of interest. Utilise remotely-sensed datasets to investigate the response of ecological indicators in identified MHW hotspots. Elucidate the impacts of climate change on ecosystem structure through a combination of statistical analysis and metabolic theory (e.g., biomass size spectrum modelling) that describe relationships between phytoplankton indicators and the biomass of pelagic fish species. Scientific Papers: Gittings, J.A., Raitsos, D., Brewin, R.J.W., Hoteit, I. (2021). Links between Phenology of Large Phytoplankton and Fisheries in the Northern and Central Red Sea. Remote Sensing, 13, 231. Gittings, J. A., Brewin, R. J. W., Raitsos, D. E., Kheireddine, M., Ouhssain, M., Jones, B. & Hoteit, I. (2019). Remotely sensing phytoplankton size structure in the Red Sea. Remote Sensing of Environment, 234, 111387. Gittings, J. A., Raitsos, D. E., Kheireddine, M., Racault, M.-F., Claustre, H., & Hoteit, I. (2019). Evaluating tropical phytoplankton phenology metrics using contemporary tools. Scientific Reports, 9(1), 674. Gittings, J. A., Raitsos, D. E., Krokos, G., & Hoteit, I. (2018). Impacts of warming on phytoplankton abundance and phenology in a typical tropical marine ecosystem. Scientific Reports, 8(1), 2240. Gittings, J. A., Raitsos, D. E., Racault, M., Brewin, R. J. W., Pradhan, Y., Sathyendranath, S., & Platt, T. (2017). Remote Sensing of Environment Seasonal phytoplankton blooms in the Gulf of Aden revealed by remote sensing. Remote Sensing of Environment, 189, 56–66. Papagiannopoulos, N., Raitsos, D. E., Krokos, G., Gittings, J. A., Brewin, R. J. W., Papadopoulos, V. P., Pavlidou, A., Selmes, N., Groom, S., & Hoteit, I. (2021). Phytoplankton Biomass and the Hydrodynamic Regime in NEOM, Red Sea. Remote Sensing, 13, 2082. Gokul, E.A., Raitsos, D.E., Gittings, J.A., Hoteit, I. (2020). Developing an atlas of harmful algal blooms in the red sea: Linkages to local aquaculture. Remote Sensing, 12, 1–14. Wang, Y., Raitsos, D.E., Krokos, G., Gittings J. A., Zhan, P. & Hoteit, I. (2019). Physical connectivity simulations reveal dynamic linkages between coral reef regions in the southern Red Sea and the Indian Ocean. Scientific Reports, 9, 16598. Brewin, B., Morán, X.A.G., Raitsos, D.E., Gittings, J. A., Calleja, M.L., Viegas, M.S., Ansari, M.I., Al-Otaibi, N., Huete-Stauffer, T.M. and Hoteit, I. (2019). Factors regulating the relationship between total and size-fractionated chlorophyll-a in coastal waters of the Red Sea. Frontiers in Microbiology, 10, 1964. Gokul, E.A., Raitsos, D.E., Gittings, J. A., Alkawri, A., Hoteit, I. (2019). Remotely sensing harmful algal blooms in the Red Sea. PLoS One, 14. Dreano, D., Raitsos, D. E., Gittings, J. A., Krokos, G., & Hoteit, I. (2016). The Gulf of Aden Intermediate Water Intrusion Regulates the Southern Red Sea Summer Phytoplankton Blooms. PLoS ONE, 1–20. POSEIDON will contribute to advances in Earth system science by addressing some of the major impacts associated with climate change, as outlined by the IPCC and ESA EO Science Strategy. The project will also exploit ESA EO-based missions (CCI, Sentinel-3), as well as deliverables from other ESA-funded projects (BICEP, ESA-S5POC), to deliver a more complete understanding of the impacts of climate change over several areas of the global oceans, providing knowledge for the responsible management of ecosystem services, including phytoplankton production and fisheries. |
| Pioneer new EO applications: tipping and cueing for maritime surveillance service | One of the advantages of constellations of EO satellites is the capability to observe areas or features of interest more often than a conventional satellite would allow. However this usually requires rapid tasking of follow-on satellites [...] | DEIMOS IMAGING S.L.U. (ES) | Enterprise | marine environment, permanently open call | One of the advantages of constellations of EO satellites is the capability to observe areas or features of interest more often than a conventional satellite would allow. However this usually requires rapid tasking of follow-on satellites based on information collected from a lead satellite. This “Tipping and cueing” is critical to ensuring an effective monitoring response but there are a range of issues to be addressed if it is to be successfully implemented. Considerations as to what information is available compared to what is ideally required, what constitutes an optimized follow-up observation in different circumstances and how fast cueing is required are all dependent on the feature or target being observed. This contract is testing a range of scenarios and assessing the effectiveness and utility of different tipping and cueing approaches. |
| Platform Common Architecture | The project has defined, developped and validated a reference architecture and related implementation of a generic EO Exploitation Platform, as well as its interconnection within a Network of Resources. The architecture and implementation are [...] | TELESPAZIO VEGA UK LIMITED (GB) | Digital Platform Services | platforms | The project has defined, developped and validated a reference architecture and related implementation of a generic EO Exploitation Platform, as well as its interconnection within a Network of Resources. The architecture and implementation are based on open standards and open source.Reusable open source code covering three main domain areas (Federated Identity Management and Authentication plus Authorisation, Processing plus Production Chaining, Data Provisioning and Management plus Accounting) has been released and will be deployed on the varius NoR Resource Tier providers as interoperable layer by the operations teams. |
| Platform Common Architecture – OGC Testbed 14 | The activity (a thread within the OGC Testbed 14 initiative) builds up on the previous Testbed 13 activities by allowing the definition of more complex algoritms (worflows, i.e. multiple tasks executed in proper order) can be defined, deployed [...] | CGI IT UK LIMITED (GB) | Digital Platform Services | platforms | The activity (a thread within the OGC Testbed 14 initiative) builds up on the previous Testbed 13 activities by allowing the definition of more complex algoritms (worflows, i.e. multiple tasks executed in proper order) can be defined, deployed and executed with appropiate access control mechanisms in an interoperable manner across a number of different environments. |
| Platform Common Architecture – OGC Testbed 13 | The activity (a thread within the OGC Testbed 13 initiative) demonstrated how an EO algorithm could be package, deployed and executed in an interoperable manner across a number of different environments. | CGI IT UK LIMITED (GB) | Digital Platform Services | platforms | The activity (a thread within the OGC Testbed 13 initiative) demonstrated how an EO algorithm could be package, deployed and executed in an interoperable manner across a number of different environments. |
| POINTOUT (Automatic Target Detection in Planet Imagery) | Traditional empirical and analytical Earth Observation (EO) algorithms retrieving physical parameters are getting to a fundamental change where learning algorithms without any prior background will be able to set themselves through the ingestion [...] | STARLAB BARCELONA SL (ES) | Enterprise | artificial intelligence, permanently open call, platforms | Traditional empirical and analytical Earth Observation (EO) algorithms retrieving physical parameters are getting to a fundamental change where learning algorithms without any prior background will be able to set themselves through the ingestion of Inputs/Outputs training datasets. Nowadays, Deep Learning (DL) networks among many other Machine Learning (ML) techniques are accurate enough, and computation technology is available to run such models. One of the key issue of such approach is the availability of massive or, large enough, reference datasets to train the models. As the models learn from the available data within the training datasets, if the size of such dataset is relatively small, the models learn very specific features that do not allow o generalize to any input data due to the lack of representativeness of the training dataset. This project addresses this issue in the context of a specific ML application, ie target/feature detection. The main goals are (1) to develop a PLATFORM to build and share collaborative training datasets for combined EO/ML communities, and (2) to implement a generic ML algorithm to detect targets in EO scenes for expert and/or non-expert users online |
| Polar TEP extension with AI capabilities | EO has a unique role in monitoring the Polar Regions by providing information that is consistent, repeatable, year-round, and covers the extensive area. In particular, Synthetic Aperture Radar (SAR) missions, such as Sentinel-1, have for many [...] | POLAR VIEW EARTH OBSERVATION LTD (GB) | Digital Platform Services | artificial intelligence, natural hazards, platforms, polar flagship, Sentinel-1 | EO has a unique role in monitoring the Polar Regions by providing information that is consistent, repeatable, year-round, and covers the extensive area. In particular, Synthetic Aperture Radar (SAR) missions, such as Sentinel-1, have for many years proven useful in high resolution monitoring due to their capability of acquiring data independent of cloud cover and polar night. However, the size of the polar regions means that relying on human analysis of the large volume of data available is not practical. The polar user communities have been early adopters of AI/ML applied to EO data. This project addresses the need for a ML platform to better serve the polar user communities. The work will implement MLflow, a well-proven ML platform, augmented by DVC to manage training data. The operation and benefits of MLflow within Polar TEP will be validated and illustrated through the following showcases: Showcase 1: Nature-Based Solutions for Flood and Erosion Protection, and Showcase 2: Polar Voyage Planning and Support Showcase 1 addresses the need for resilient infrastructures to mitigate increased coastal and riverine flood and erosion potential as a consequence of climate change. Employing nature-based methods to mitigate flood and erosion hazards is an environmentally friendly solution. Showcase 2 responds to the needs of ships and people operating in the polar regions for past, present, and future environmental information, especially concerning sea ice. These regions are experiencing climate change at a rate that is up to five times greater than the rest of the planet. ML applied to environmental data can help mitigate the impact of these changes by providing better information with which to plan and conduct polar operations and thus provide improved safety for people, infrastructure, and the environment. |
| Polar Thematic Exploitation Platform | The Polar Thematic Exploitation Platform provides a complete working environment where users can access algorithms and data remotely, providing computing resources and tools that they might not otherwise have, avoiding the need to download and [...] | POLAR VIEW EARTH OBSERVATION LTD (GB) | Digital Platform Services | applications, cryosphere, platforms | The Polar Thematic Exploitation Platform provides a complete working environment where users can access algorithms and data remotely, providing computing resources and tools that they might not otherwise have, avoiding the need to download and manage large volumes of data. This new approach removes the need to transfer large Earth Observation data sets around the world, while increasing the analytical power available to researchers and operational service providers. Earth Observation is especially import in the polar regions at a time when climate change is having a profound impact and excitement about new economic opportunities is driving increased attention and traffic, resulting in concerns about the state of the region’s delicate ecosystems. Developing tools to model, understand and monitor these changes is vitally important in order to better predict and mitigate the resulting global economic and environmental consequences. Polar TEP provides new ways to exploit EO data for research scientists, industry, operational service providers, regional authorities and in support of policy development. |
| Polar+ Ice Shelf | The aim of this project is to produce a suite of Earth Observation datasets to characterise how ice shelves in Antarctica have changed over the last decade, and to make use of these data sets to investigate the physical processes driving this [...] | UNIVERSITY OF LEEDS, SCHOOL OF EARTH AND ENVIRONMENT (GB) | Science | Glaciers and Ice Sheets, polar science cluster, science | The aim of this project is to produce a suite of Earth Observation datasets to characterise how ice shelves in Antarctica have changed over the last decade, and to make use of these data sets to investigate the physical processes driving this evolution. This project will exploit the 25-year record of ESA satellite observations, including SMOS, S-1, S-2, and swath mode processed CryoSat-2 data, to produce a provides a comprehensive record of ice shelf change that extends the temporal coverage and improves the spatial resolution with which we can study Antarctic Ice Shelves. This will reveal small scale ice shelf features such as the propagation of cracks along the ice shelf surface, deep sub-shelf meltwater channels that can erode ice locally by up to 200 meters, and changes in the calving front and grounding line location. These datasets will improve our understanding of the way in which ice shelves around Antarctica are changing today, which we will use to discover new insights about the physical mechanisms driving change and affecting the future stability of ice shelves in this remote and inaccessible continent. |
| Polar+ Snow on Sea ice | The project aims to develop and validate different approaches to retrieve snow thickness over the sea ice; to develop a new prototype processor; and to produce and validate an experimental dataset of snow thickness over the Arctic. | MULLARD SPACE SCIENCE LABORATORY-UNIVERSITY COLLEGE LONDON (GB) | Science | polar science cluster, science, snow and ice | The project aims to develop and validate different approaches to retrieve snow thickness over the sea ice; to develop a new prototype processor; and to produce and validate an experimental dataset of snow thickness over the Arctic. |
| POst-Process CORrection of satellite data products with New machine learning based approach (POPCORN) | POPCORN is a novel data processing approach for satellite data post-process correction. POPCORN combines the best aspects of the conventional physics-based retrieval algorithms and state-of-the-art machine learning techniques. The aim of the [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | AI4EO | Aerosols, AI4EO, atmosphere, Sentinel-3 | POPCORN is a novel data processing approach for satellite data post-process correction. POPCORN combines the best aspects of the conventional physics-based retrieval algorithms and state-of-the-art machine learning techniques. The aim of the POPCORN project is to develop novel machine-learning-based post-process correction methodology that will improve the Earth observation satellite data accuracy. The methodology will be general and applicable to most satellite data. In POPCORN, we will use Sentinel-3 atmospheric aerosol data as an example data to develop and test the new methodology. The main users of the POPCORN methods and data are the atmospheric scientists and satellite algorithm developers. Satellites are the only way to obtain near real-time global daily information of Earth’s atmosphere and there is a widespread need for accurate satellite-based information about the atmosphere. With POPCORN methods it may be possible to significantly improve the accuracy of existing satellite data with reasonable computational costs. The main product of POPCORN is the novel methodology that combines the best aspects of conventional physics-based satellite retrieval algorithms and state-of-the-art machine learning algorithms. In addition, we have applied the POPCORN methodology to Sentinel-3 high-resolution atmospheric aerosol data and this data is available as open data for year 2019 and five regions of interest (Central Europe, East USA, West USA, Southern Africa, India). POPCORN shows the true potential of satellite data in atmospheric remote sensing and improves the current operational atmospheric aerosol satellite data product accuracy |
| Pre-Operational Sentinel-3 snow and ice products (SICE) | Land ice mass loss is the largest source of global sea level rise. Since 1992, two thirds of sea level contribution from land ice comes from the Arctic. Roughly half of Greenland ice sheet mass loss is from increased surface melting. The [...] | GEOLOGICAL SURVEY OF DENMARK AND GREENLAND (DK) | Science | permanently open call, polar science cluster, science | Land ice mass loss is the largest source of global sea level rise. Since 1992, two thirds of sea level contribution from land ice comes from the Arctic. Roughly half of Greenland ice sheet mass loss is from increased surface melting. The fraction from surface melting is even higher for smaller Arctic ice masses. The dominant energy source for melt is absorbed sunlight controlled by surface albedo. Bare ice and snow impurities, including biological effects present strong melt amplifiers through surface albedo. NASA MODIS sensors provide a climate data record (CDR) of snow extent and ice albedo since 2000 with the hosting Terra and Aqua missions now several years beyond design lifetime. The NOAA VIIRS sensor bridges the need for a satellite-derived albedo. However, Copernicus Sentinel-3 also fulfils the WMO essential climate variable mandate and for decades to come with the following additional advantages over VIIRS and MODIS: 1. The Sentinel-3 OLCI instrument offers higher (300 m) finest spatial resolution (SR). The finest SR for MODIS is 500 m. For VIIRS, the finest SR is 750m. 2. Sentinel-3 OLCI and SLSTR instruments offer more spectral coverage than MODIS or VIIRS, with the OLCI channel 21 being of particular value being located in the part of the spectrum most sensitive to snow grain size. Neither MODIS nor VIIRS measure in this spectral channel. 3. The algorithms proposed here are a full physics based retrievals vs often used empirical techniques. 4. The recently completed Scientific Exploitation of Operational Missions (SEOM) Sentinel-3 for Science (S34Sci) Land Study 1: Snow (S3 Snow) albedo algorithm outperforms NASA MODIS MOD10A1 product for dry clean snow. Main objectives / end goals of the study are: 1. deliver an automated open source processing chain using Sentinel-3 OLCI and SLSTR sensors to determine a dry/wet snow and clean/polluted bare ice spectral and broadband optical albedo 1 km daily product for land ice (glaciers, ice caps, ice sheet). 2. determine an optimal cloud clearing process for cryospheric application leveraging cloud ID insight from SEOM Sentinel-3 for Science, Land Study 1: Snow 3. test the above for application to sea ice (as opposed to land ice). 4. implement terrain correction for slopes under 4 degrees typical of more than 90% of land ice. Justification: terrain slope and azimuth has a strong impact on snow and ice anisotropic reflectance in optical wavelengths. Above 4 degrees remains in development elsewhere, and does not comprise a significant portion of the ice sheet. 5. validate the algorithms using field data. 6. deliver daily 15 March – 30 September 1km pan-Arctic glacierized region albedo products for years 2017 and 2018 via the PROMICE.org web portal. 7. demonstrate a pre-operational near-realtime (under 6 hours latency) capability for Sentinel-3A and Sentinel-3B for delivering spectral and broadband albedo. |
| Precise Monitoring of Transportation Infrastructures Using InSAR | The project goal is to develop a core service application for the TITCMS (transportation infrastructure technical condition monitoring support service) business service of the company DATEL, an on-demand deformation measurement and technical [...] | DATEL AS (EE) | Enterprise | enterprise, urban | The project goal is to develop a core service application for the TITCMS (transportation infrastructure technical condition monitoring support service) business service of the company DATEL, an on-demand deformation measurement and technical monitoring service. The purpose of TITCMS service is to monitor specific infrastructure objects by applying EO data, based on time series analysis with regular interval. The main information product of this service is the deformation value for a specific location. The TITCMS service taking advantage of the Sentinel-1 revisit frequency and global coverage. |
| PRISMA + S5P demonstration for COVID-19 studies | Recent climate remote study showed essential effect of COVID-19 on trace gases emissions, in particular, of NO2 and CO2. In Europe, Italy was one of the first countries to be infected by the COVID-19 virus, starting in the beginning of February [...] | GRASP-SAS (FR) | Science | Aerosols, air quality, atmosphere science cluster, atmospheric chemistry, covid19, environmental impacts, health, public health, Sentinel-5P | Recent climate remote study showed essential effect of COVID-19 on trace gases emissions, in particular, of NO2 and CO2. In Europe, Italy was one of the first countries to be infected by the COVID-19 virus, starting in the beginning of February 2020, and numbers soaring up to over 100,000 infections and 20,000 deaths by mid-April. Severe limitations of people movements following the lockdown determined a significant reduction of pollutants concentration mainly due to vehicular traffic (PM10, PM2.5, BC, benzene, CO, and NOx), which is visual, for example, in S5P images of NO2 distributions. The lockdown also led to an appreciable drop in SO2. Despite the significant decrease in NO2, the O3 exhibited a significant increase, probably, due to the minor NO concentration. At the same time the effect on aerosol emission and loading has not been reported yet widely in the scientific literature, although news and social media stories report spectacular cleaner air due to various lock-downs (e.g. “Himalayas being visible from India for the first time in 30 years”). Furthermore, a possible influence of long-term exposure to small particulate matter on COVID-19 mortality has been reported. In general, aerosol distribution is strongly spatially and temporally inhomogeneous. Therefore, to investigate COVID-19 effect on aerosol the remote sensing measurements with frequent revisiting time and fine spatial resolution may be necessary. In this project we investigate the possibility to exploit PRISMA (PRecursore IperSpettrale della Missione Applicativa, an Italian Space Agency (ASI) hyperspectral mission) fine resolution measurements together with daily S5P/TROPOMI and AERONET measurements for motoring environmental dynamics associated with COVID-19 epidemic appearance and evolution in regional scale. |
| Privacy Preserving Machine Learning (PPML) | The project is dedicated to demonstration of Privacy Preserving Machine Learning (PPML) in EO data analytics as an emerging field in data science that strives to address protecting data privacy and confidentiality in a variety of machine [...] | DEIMOS SPACE UK LTD (GB) | AI4EO | AI4EO | The project is dedicated to demonstration of Privacy Preserving Machine Learning (PPML) in EO data analytics as an emerging field in data science that strives to address protecting data privacy and confidentiality in a variety of machine learning applications. It is aimed to research and demonstrate secure frameworks for AI/ML, including cryptographic techniques such as Federated Learning (FL), Secure Multi-Party Computation (MPC), Homomorphic Encryption (HE), and Differential Privacy (DP), as well as hardware-based approaches (TEE – Trusted Execution Environment) to provide computing environment suitable for handling and protecting confidential data as well as AI models from disclosure or interference. |
| Privacy Preserving Federated Machine Learning in EO Science | Big Data and artificial intelligence (AI) pave the way for new pathways in the improvement of healthcare. But they also hide risks for the security of sensitive clinical data stored in critical healthcare ICT infrastructure. The EU-funded [...] | GMV SOLUCIONES GLOBALES INTERNET SA (ES) | AI4EO, Digital Platform Services | AI4EO, generic platform service, permanently open call, platforms | Big Data and artificial intelligence (AI) pave the way for new pathways in the improvement of healthcare. But they also hide risks for the security of sensitive clinical data stored in critical healthcare ICT infrastructure. The EU-funded FeatureCloud project proposes a transformative security-by-design concept aiming to reduce the possibility of cyber crime and allow safe cross-border collaborative data mining efforts. The concept will be applied to a software toolkit employing the worldwide first privacy-by-architecture method. Central features of this method are no sharing of sensitive data via any communication channels and no data storage in one central point. FeatureCloud will integrate federated machine learning with blockchain technology to safely apply next-generation AI technology in medical innovations. The digital revolution, in particular big data and artificial intelligence (AI), offer new opportunities to transform healthcare. However, it also harbors risks to the safety of sensitive clinical data stored in critical healthcare ICT infrastructure. In particular data exchange over the internet is perceived insurmountable posing a roadblock hampering big data based medical innovations. FeatureCloud’s transformative security-by-design concept will minimize the cyber-crime potential and enable first secure cross-border collaborative data mining endeavors. FeatureCloud will be implemented into a software toolkit for substantially reducing cyber risks to healthcare infrastructure by employing the world-wide first privacy-by-architecture approach, which has two key characteristics: (1) no sensitive data is communicated through any communication channels, and (2) data is not stored in one central point of attack. Federated machine learning (for privacy-preserving data mining) integrated with blockchain technology (for immutability and management of patient rights) will safely apply next-generation AI technology for medical purposes. Importantly, patients will be given effective means of revoking previously given consent at any time. Our ground-breaking new cloud-AI infrastructure only exchanges learned model representations which are anonymous by default. Collectively, our highly interdisciplinary consortium from IT to medicine covers all aspects of the value chain: assessment of cyber risks, legal considerations and international policies, development of federated AI technology coupled to blockchaining, app store and user interface design, implementation as certifiable prognostic medical devices, evaluation and translation into clinical practice, commercial exploitation, as well as dissemination and patient trust maximization. FeatureCloud’s goals are bold, necessary, achievable, and paving the way for a socially agreeable big data era of the Medicine 4.0 age. |
| Proba-V Mission Exploitation Platform – Third-Party Services | The project has demonstrated the Proba-V Mission Exploitation Platform (MEP) capabilities (in terms of infrastructure and vegetation product access) with a number of identifies pilot users (scientists and industry) giving them the opportunity to [...] | SPACE APPLICATIONS SERVICES S.A./N.V. (BE) | Digital Platform Services | platforms | The project has demonstrated the Proba-V Mission Exploitation Platform (MEP) capabilities (in terms of infrastructure and vegetation product access) with a number of identifies pilot users (scientists and industry) giving them the opportunity to prototype potential tools and services. |
| PROMCOM: Production of lower tropospheric methane and carbon monoxide distributions through combined use of ESA Sentinel-5 Precursor shortwave infrared and IASI/CrIS thermal infrared satellite data | Living Planet Fellowship research project carried out by Diane Knappett. Global distributions of the methane (CH4) column average and carbon monoxide (CO) total column are observable by satellite shortwave infrared (SWIR) spectrometers [...] | UKRI Rutherford Appleton Laboratory (GB) | Science | atmosphere, carbon cycle, carbon science cluster, living planet fellowship, science, Sentinel-5P, TROPOMI | Living Planet Fellowship research project carried out by Diane Knappett. Global distributions of the methane (CH4) column average and carbon monoxide (CO) total column are observable by satellite shortwave infrared (SWIR) spectrometers through detection of surface-reflected solar radiation. Observations by ENVISAT SCIAMACHY and GOSAT-TANSO have been exploited extensively to investigate biogenic, pyrogenic and anthropogenic sources and, in the case of methane, to quantify emissions through inverse modelling. ESA’s S5P offers a major advance on these preceding satellite SWIR spectrometers for identification and quantification of sources on finer scales by providing the first contiguous, daily global coverage at high spatial resolution (7 x 7 km). However, for inverse modelling of emission sources, height-resolved information would offer a major innovation on column information; particularly resolution of the lower tropospheric layer. This Fellowship proposes to develop and apply a scheme to achieve this by combining SWIR and TIR information on CH4 and CO. RAL has developed a state-of-the-art scheme to retrieve global height-resolved methane distributions from thermal infrared (TIR) measurements in the Infrared Atmospheric Sounding Interferometer (IASI) 7.9 µm band (Siddans et al., 2017). While providing information on two independent vertical layers in the troposphere, sensitivity in this band decreases towards the ground, due to decreasing thermal contrast between the atmosphere and surface. A combined retrieval scheme exploiting in addition the high signal-to-noise information from S5P (SWIR/column) with that from IASI or CrIS (TIR/height-resolved) would enable lower tropospheric distributions of methane and CO to be resolved. Lower tropospheric concentrations are more closely-related to emission sources than are column measurements and inverse modelling of surface fluxes should be less sensitive to errors in representation of transport at higher altitudes; a limiting factor for current schemes. As baseline, ESA S5P Level 2 (L2) products will be combined with retrievals from RAL’s IASI scheme; either as additional prior information for the IASI retrieval (L2-L1) or by combining retrieved L2 products (L2-L2). The IASI TIR scheme will then be modified and applied to CrIS (Suomi-NPP or NOAA-20), whose observations are separated by ~5 minutes from S5P compared to ~4 hours for IASI. Test data sets will be compared with analyses, models and surface measurements. Possibilities to improve on: (a) ESA’s S5P products, (b) the TIR scheme or (c) the SWIR-TIR scheme will then be assessed. Finally, the best performing scheme will be run to produce a fully-sampled 1-year CH4 and CO height-resolved dataset which will be made accessible to the science community. |
| QuAI4EO | Quantum Computing (QC) is rapidly emerging as an alternative to traditional classical computing thanks to its potential advantages in terms of representational power and computing time. This activity targets to study the application and explore [...] | CERN (CH) | AI4EO | AI4EO | Quantum Computing (QC) is rapidly emerging as an alternative to traditional classical computing thanks to its potential advantages in terms of representational power and computing time. This activity targets to study the application and explore the potential of Quantum Machine Learning (QML) on realistic Earth Observation (EO) use cases. Several EO scenarios are investigated. A first line of work focus on the classification of EO images by constructing a multi-task hybrid classical-quantum (MTCQ) model which executes the reconstruction and classification of EO images at once via end-to-end training, exploring also concepts of invariance in quantum neural networks. Especially, different quantum circuit ansatzes are tested to understand the correlation between their expressive power and classification accuracy. A second objective considers generative models, in particular quantum generative adversarial networks (qGANs). It aims to develop qGANs able to model the distribution of EO data allowing a wide panel of applications, including generation and composition of image. Finally, a third objective consists in exploring how quantum algorithms could help in time series data analysis with a focus on learning dynamical systems from data. This line of work investigates how Quantum encoding of dynamics can be useful to detect patterns and instabilities or anomalies. Given the very exploratory nature of the field, this activity is implemented as a joint early-career research programme between ESA and CERN as part of the CERN Doctoral Student programme. Additional resources: Su-yeon Chang, S. Vallecorsa, M. Grossi, B. Le Saux, Quantum Convolutional Circuits for Earth Observation Image Classification, IGARSS 2022, July 2022 Su Yeon Chang, Bertrand Le Saux, Michele Grossi, Sofia Vallecorsa, Hybrid Quantum-Classical Networks for Reconstruction and Classification of Earth Observation Images, ACAT Physics research workshop, Oct. 2022 Su-yeon Chang, S. Vallecorsa, B. Le Saux, Quantum Machine Learning for Earth Observation Images, NeurIPS 2nd WS on Quantum Tensor Networks in Machine Learning, Dec. 2022. Su-yeon Chang, B. Le Saux, S. Vallecorsa, M. Grossi, Correlation between PQC Descriptors and Training Accuracy in Hybrid Quantum-Classical Model for Earth Observation Image Classification, 26th Conference on Quantum Information Processing, Feb. 2023. Alice Barthe, V. Dunjko, J. Tura, M. Grossi, Method for the visualization of multi-qubit systems pure states 26th Conference on Quantum Information Processing, Feb. 2023. Su-yeon Chang, M. Grossi, B. Le Saux, S. Vallecorsa, Approximately equivariant quantum neural network for p4m group symmetries in images, IEEE International Conference on Quantum Computing and Engineering (QCE), Sep. 2023. Paper Alice Barthe, Vedran Dunjko, Jordi Tura, Michele Grossi, Continuous Variables Quantum Algorithm for Solving Ordinary Differential Equations, IEEE International Conference on Quantum Computing and Engineering (QCE), Sep. 2023. Paper |
| QuantEO: a new Intelligent Automation (IA) service for Sentinel-2 Data | This project developed a service for automated clustering of Sentinel-2 pixels which allows its users to focus on Earth surface changes rather than on remote sensing problems, and hence to develop their own downstream applications. Available [...] | PIXSTART (FR) | AI4EO | AI4EO, applications, artificial intelligence, permanently open call, Sentinel-2 | This project developed a service for automated clustering of Sentinel-2 pixels which allows its users to focus on Earth surface changes rather than on remote sensing problems, and hence to develop their own downstream applications. Available via a standard interface, it produces on demand and in near real time classified Sentinel-2 images at 10 meter resolution, in a new 2D space which preserves all properties of Sentinel-2 information (spectral complexity and topology, maximum spatial resolution), and which is consistent over time and space (from a Sentinel 2-tile to another). This simplified new space is allowing pixel labelling or grouping by a posteriori classes identification, change detection by distance computation, interpolation, and may be used as a pre-processing step for all kinds of machine learning algorithms. |
| QUANTUM ADVANTAGE FOR EARTH OBSERVATION STUDY (QA4EO STUDY) | The main scope of the QA4EO project (Quantum Advantage for Earth Observation) is to identify three to five intractable Earth Observation Use-Cases (EO UCs) of practical importance based on their computational advantage as well as strategic value [...] | DLR – GERMAN AEROSPACE CENTER (DE) | AI4EO | hyperspectral | The main scope of the QA4EO project (Quantum Advantage for Earth Observation) is to identify three to five intractable Earth Observation Use-Cases (EO UCs) of practical importance based on their computational advantage as well as strategic value that can be usefully expressed and solved by a quantum computing approach on quantum computers (QC). The proposed EO UCs are: UC1) Variational quantum algorithms for EO Image processing, UC2) Climate adaptation digital twin HPC+QC workflow, UC3) feature selection for environmental monitoring hyperspectral imagery, and UC4) Uncertainty quantification for remotely-sensed datasets. To assess the selected EO UCs, we evaluate their hardness by using the computational complexity measures, and their hardness implies that conventional classical computers cannot solve efficiently our identified EO UCs but QC promise to tackle them efficiently. |
| QUANTUM COMPUTING FOR EARTH OBSERVATION STUDY (QC4EO STUDY) | Earth Observation (EO) satellites generate a growing amount of data every year and highlight the need for scalable algorithms and adequate computational resources. However, the question about how to leverage quantum computing for enhancing the [...] | FORSCHUNGSZENTRUM JUELICH GMBH (DE) | AI4EO | Earth Observation (EO) satellites generate a growing amount of data every year and highlight the need for scalable algorithms and adequate computational resources. However, the question about how to leverage quantum computing for enhancing the required computational steps is still largely unanswered. The QC4EO study proposes insightful answers and potential solutions to this question. The study has been conducted in the period March 2023 – October 2023 by a consortium led by Forschungszentrum Jülich, with Thales Alenia Space Italy/France, INFN and IQM, and supported by the European Space Agency. The scope of the study covers 12 use cases and a 15-year timeframe, evaluating a potential practical advantage of quantum computing in specific computational tasks and the availability of the required hardware in the near future. USE CASE SHORT DESCRIPTION BOTTLENECKS OF THE CONSIDERED CLASSICAL SOLUTION PROPOSED QUANTUM SOLUTION UC1: Mission Planning for EO applications Finding an optimal acquisition plan of a satellite constellation given user requests Acquisition planning is a combinatorial optimization problem of exponential complexity, currently solved with deterministic or heuristic methods Two different approaches have been studied: quantum optimization and quantum machine learning UC2: Multiple-view Geometry on Optical Images Analyzing satellite images of a specific area captured from various perspectives Keypoint extraction: combinatorial optimization problem of exponential complexity Quantum clustering: quantum k-medoids, quantum kernel density UC3: Optical Satellite Data Analysis Analyzing the semantic content of satellite images Kernel methods: quadratic algorithmic complexity and time overhead of kernel computation, expressivity of the kernel Quantum kernels UC4: SAR Raw Data Processing Image generation of an area of interest from the raw signal received by the SAR system Frequency-based methods (Range Doppler): polylogarithmic complexity of Fourier transformation Quantum Range Doppler Algorithm This study culminated in the release of four technical deliverables and an executive summary, each encompassing a detailed analysis of four selected use cases, i.e., mission planning for EO acquisitions, multiple-view geometry on optical images, optical satellite data analysis, and SAR raw data processing. The use cases have been selected according to their impact for the space industry and their compatibility with the expected development of quantum computing devices in the considered timeframe. For each use case, a relevant quantum algorithm is selected, a realistic problem instance is defined, and a timeline is proposed, mapping the problem size with quantum hardware requirements. Superconducting qubits and ion-traps are considered the most promising quantum computing technologies. The QC4EO study concludes that executing experiments on real hardware is expected to be possible for a reasonable problem size in the near future, providing practical insights on the theoretical advantage of the designed quantum algorithms. The QC4EO study provides an analysis of the exploitation of quantum algorithms and computing technologies for four selected use cases that hold high interest and impact in the domain of Earth Observation (EO). The main results regarding the expected predictions for effective usage of quantum computing are illustrated in the timeline. The tables show time predictions regarding the applicability of quantum computing to the use cases for different problem instance sizes. Some problems of small size, which are still distant from effective practical use, might be solved in a 3-5 year time frame. Full-size problems, on the other hand, are expected to be efficiently solved in at least 15 years, with improved, and possibly error-resilient, quantum computing hardware. It is important to point out, however, that these predictions were made considering the current knowledge of different quantum hardware platforms, and therefore, the actual possibility of efficiently solving the use-cases using quantum computing may change depending on future research findings. To further explore the intersection of High-Performance Computing (HPC) and EO, the HPC and Innovative Computing workshop was organized. The workshop, held at ESRIN, the ESA center for Earth Observation in Frascati, Italy, on October 12th, 2023, brought together experts from the HPC and EO fields to discuss their interconnections, future prospects, and challenges.The event featured speakers from European HPC centers such as FZ Julich, Cineca, and CSC, as well as representatives from IQM computers, the University of Padova, and ESA. The workshop had 25 attendees in person and an additional 75 participants online. The presentations and the report on the workshop can be found below. | |
| Query Planet | QueryPlanet aims at democratizing the access of Artificial Intelligence to the Earth Observation community by developing open-tools for the creation of AI-ready EO dataset and use-cases that leverage such datasets to build global insights [...] | SINERGISE LTD. (SI) | AI4EO | AI4EO, forestry, platforms, Sentinel-2 | QueryPlanet aims at democratizing the access of Artificial Intelligence to the Earth Observation community by developing open-tools for the creation of AI-ready EO dataset and use-cases that leverage such datasets to build global insights applications. Material and datasets develop under QueryPlanet are open-access. The project aims at providing open-source tools for the exploitation of Earth Observation data, in particular of Sentinel-2 imagery. The target audiences of the project are the EO and AI communities, fostering their engagement in exploiting EO dataset, in particular Sentinel-2, to build applications that tackle relevant topics.In the first phase of the project, tools to annotate Sentinel-2 imagery are developed, allowing any user to set-up and share with the community their labeling campaign. Following the creation of the label datasets, the creation of the EO processing workflow is facilitated by eo-learn, the open-source Python package developed within the project. eo-learn provides common processing tasks to scale the analysis of satellite imagery to global scale through seamless parallelization. To further promote the upake of the tools created, AI-ready dataset and use-cases capitalising on such datasets are created and published. Currently developed use-cases include: super-resolution of Sentinel-2 bands beyond the 10 metre spatial resolution, using the HighResNet multi-frame super-resolution algorithm and VHR imagery as target reference. The training dataset for such algorithm is globally sampled and includes humanitarian targets; a hierarchical object detection scheme which uses several data sources with increased spatial resolution to detect buildings in an efficient and scalable way. The hierarchical scheme in this case uses Sentinel-2, Airbus SPOT and Airbus Pleiades imagery to perform object detection using rotated bounding boxes; a pan-European map of forest and forest types using Sentinel-2 time-series. The developed algorithm is based on the latest deep learning architectures for the analysis of spatio-temporal datasets, and uses tens of thousands of samples collected over the EEA countries area. Open-source tools to ease labelling of EO imagery Open-source tools to process EO imagery for the creation of AI-ready datasets Publishing of AI-ready datasets covering a wide range of thematics Publishing of material to create use-case applications based on AI to extract insights from the EO datasets Facilitate entry to the field to non EO experts |
| QUID-REGIS | The day-to day variability of quiet-time ionosphere is surprisingly high even during periods of negligible solar forcing. Relatively well understood is the high-latitude variability where the solar wind is directly driving the high latitude [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | science, solid earth, swarm | The day-to day variability of quiet-time ionosphere is surprisingly high even during periods of negligible solar forcing. Relatively well understood is the high-latitude variability where the solar wind is directly driving the high latitude currents, convection electric field or polar aurorae. But the current understanding does not allow to accurately model the ionospheric state during the quiet-time conditions also at mid- and low-latitudes. Surprising effects remains even at mid-latitudes, including for instance double daily maxima of ionospheric critical frequency. SWARM measurements allow the characterization of the upper atmospheric conditions and dynamics (80-400 km) for more than 10 years now. The analysis of SWARM data also showed that the ionosphere is sometimes disturbed even during “quiet” solar periods: the electron density and electric field, for instance, can show significant variability that currently remains unexplained. Using SWARM data, supported by extensive ground-based measurements of both, the upper mesospheric/ lower thermosphere (UMLT) and ionospheric D-, E- and F-region, as well as the International Reference Ionosphere Model (IRI), we contribute to characterize the atmospheric state during these quiet periods. Thus, QUID-REGIS contributes to the understanding of disturbances in the upper atmosphere and clarifies whether these are at least in parts a result of neutral atmospheric dynamics from the lower atmosphere at mid-latitudes. During solar quiet periods, we will analyze SWARM data to detect unexpected variability. For these periods, we will investigate measurements at lower heights for atmospheric variability. These measurements comprise airglow observations representative for the neutral atmosphere in the UMLT (80-100km), magnetic field (and other) observations representative for the ionospheric dynamo region (85-200km) as well as airglow observations from 200-300km altitude. Whenever we detected unexpected variability in SWARM data we will statistically evaluate if the lower atmosphere might serve as a source region for these variabilities. Then, atmospheric waves may serve as an explanation. We will derive and analyze our well-established indices of planetary wave and gravity wave dynamics in the UMLT to characterize those waves and quantitatively estimate their contribution to the observed variability in the ionosphere. We evaluate, if the disturbances in the ionosphere during the quiet periods are causing less accurate outputs of the IRI-model, in such case we would provide the improved version of IRI model based on Swarm electron density data. We aim to deliver the typical quantities of the dynamics as a look up table to contribute to modeling of the baseline conditions. A better quantification of the role of UMLT wave dynamics in the occurrence of solar quiet ionospheric disturbances will be achieved along with abetter representation of baseline ionospheric conditions. |
| R4OpenEO – Integrating R Analytics with openEO Platforms | This project will develop, test and demonstrate the use of the R data science language within openEO platform. This involves the continuation of development of the openEO R client, integration of openEO software components in R integrated [...] | EURAC RESEARCH – ACCADEMIA EUROPEA (IT) | Digital Platform Services | permanently open call, platforms | This project will develop, test and demonstrate the use of the R data science language within openEO platform. This involves the continuation of development of the openEO R client, integration of openEO software components in R integrated development environments (Rstudio, Project Jupyter), as well as R user-defined functions that directly operate on data cubes and their interaction with the openEO back-end drivers. Three selected use cases, from the context of the ESA Regional Initiatives, will demonstrate the usability of the developed components and foster collaboration with the EO4Alps regional initiative and the openEO Platform project. |
| RACE – Rapid Action on Covid-19 and EO | The Rapid Action coronavirus Earth observation dashboard presents the results of the Joint cooperation between ESA and the European Commission on Covid 19 and EO.The platform demonstrates how the use of Earth [...] | European Space Agency (ESA) – EOP | Digital Platform Services | covid19, platforms, science | The Rapid Action coronavirus Earth observation dashboard presents the results of the Joint cooperation between ESA and the European Commission on Covid 19 and EO. The platform demonstrates how the use of Earth observation data can help shed new light on societal and economic changes currently taking place owing to the coronavirus pandemic. Across all European countries and ESA Member States, the dashboard showcases examples of how different analyses over a wide range of Earth observation data coming from the Copernicus Sentinels and Third Party Missions, as well as ground-based observations and advanced numerical models via the Copernicus Services can illustrate these socio-economic and environmental changes. The dashboard not only captures the effects of the lockdown, but also shows how Europe is beginning its recovery and is relaunching a number of activities. The data populating the dashboard are a collective effort of a number of industrial and academic partners. |
| Raincast – Scientific Evaluation of Future Atmospheric Mission Concepts to Monitor Precipitation | The holistic understanding of the Earth’s water and energy cycle remains one of the grandchallenges that the international scientific community needs to address in the next decade.The Raincast project is a multi-platform and multi-sensor study [...] | UNIVERSITY OF LEICESTER (GB) | Science | atmosphere | The holistic understanding of the Earth’s water and energy cycle remains one of the grandchallenges that the international scientific community needs to address in the next decade.The Raincast project is a multi-platform and multi-sensor study to address the requirement from theresearch and operational communities for global precipitation measurements. Raincast aims atidentifying and consolidating the science requirements for a satellite mission that couldcomplement the existing space-based precipitation observing system and that could optimallyliaise with efforts currently made by other agencies in this area (especially by NASA andJAXA). Because of the complexity of the cloud and precipitation processes the study capitalizeson the most recent advancement and mission concepts for precipitation observations with state-of-the-art instrumentation (including multi-frequency radars, radar-radiometer synergies, constellations of cubesat radars) and makes full use of the most recent advancements in inversion methods for the estimation of precipitation variables from primary measurements (e.g. latest ice scattering libraries, physical relationships derived by in-situ measurements). |
| Raised Peatland Ecohydrology Evaluation through Sentinel-1 InSAR data and Machine Learning – RaiPEAT_InSAR | The “Raised Peatland Ecohydrology Evaluation through Sentinel-1 InSAR data and Machine Learning” (RaiPEAT_InSAR) project will investigate linkages between ecohydrological parameters of raised peatlands and InSAR estimates to classify of [...] | UNIVERSITY COLLEGE DUBLIN (IE) | Science | living planet fellowship, SAR, Sentinel-1, terrestrial hydrosphere | The “Raised Peatland Ecohydrology Evaluation through Sentinel-1 InSAR data and Machine Learning” (RaiPEAT_InSAR) project will investigate linkages between ecohydrological parameters of raised peatlands and InSAR estimates to classify of ecohydrological dynamics of peatlands. The main objectives are as follows: Ground validation of InSAR-derived surface motions of temperate raised peatlands by using co-located soil moisture, water table and in-situ displacement measurements. Derivation of empirical relationships between soil moisture, groundwater levels, true surface displacement and InSAR-derived displacement for temperate raised peatlands. Comparison of peatland surface motion data from the new European Ground Motion Service to both the in-situ ground measurements and local area InSAR data processing. Upscaling of InSAR-derived water table fluctuation at temperate raised peatlands from site-scale to regional scales. Classification of eco-hydrological dynamics of temperate raised peatlands from InSAR data via machine learning. Raised peatlands are highly sensitive ecosystems subject to landmark European Union (EU) environmental legislation. They are also a major long-term carbon reservoir, both in Northern Europe and in many other parts of the globe. Protection and restoration of peatland is central to European policy goals for biodiversity, environment, and climate. Peatlands form by accumulation of plant and animal remains under anoxic and highly acidic groundwater conditions in areas with a high and stable groundwater table. The maintenance of the groundwater table is critical for peatlands in terms of their ecological functions, their geotechnical stability, their impact on downstream water quality and their greenhouse gas emissions. Long- and short-term water table levels are thus a key environmental variable for peatland conservation and restoration, as well as related climate change mitigation efforts. A challenge is to monitor the progress and effectiveness of peatland conservation and restoration at large scales (regional, national, or global). Remote sensing data from ESA’s Sentinel missions potentially hold the key. Recent work on temperate peatlands in Ireland and Britain indicates that Interferometry of Synthetic Aperture Radar (InSAR) data derived from Sentinel-1 imagery may enable the mapping of ground surface motions at peatlands in space and time. Furthermore, these motions may be tied to changes in groundwater level. A problem is that there has been no systematic ground validation of the satellite-derived surface motions to date. Consequently, it is unclear how exactly InSAR data for peatlands relate to the underlying ecohydrological variables. Such validation is critical for underpinning an upscaling of peatland monitoring from local in-situ data to a regional or national scale via, for instance, the Copernicus program’s European Ground Motion Service (EGMS). Additionally, a robust methodology for peatland ecohydrological classification based on InSAR needs to be developed and tested. The RaiPEAT_InSAR aims to address these scientific gaps by conducting a detailed analysis of Sentinel-1 derived InSAR time-series datasets over several well-studied and well-instrumented ‘flagship’ raised peatlands in Ireland and Britain. To ground validate the InSAR surface motion estimates, the project will take advantage of novel camera-based instruments (PeatCams) that have been specifically designed for measuring peatland surface motions at sub-mm precision. By co-locating the PeatCams for the first time with both piezometers and soil moisture sensors, the project will offer unprecedented insight into the relationship between InSAR-derived apparent ground motion, true ground motion, soil moisture and water table levels at temperate raised peatlands. The new data will be used to derive empirical relations between InSAR-estimated ground motion and water table fluctuation that can be used to upscale the in-situ data for regional or even global peatland monitoring. The data will also help to check the accuracy of the EGMS over these peatlands to evaluate its suitability for upscaling of peatland monitoring. Finally, it is aimed to develop and test a new machine learning approach for the classification of peatland water table dynamics from Sentinel-1 InSAR data to facilitate the upscaling of peatland monitoring and provide a basis for future implementation across Europe. |
| Remote sensing-based Weather Area Index Insurance (WAII) An affordable insurance solution to increase resilience of small-scale farmers | Crop insurance is a key element to increase the resilience of farmers, particularly small-scale farmers in countries highly exposed to the impact of climate change. Unlike traditional crop insurance that attempts to measure individual farm [...] | SARMAP SA (CH) | Applications | agriculture, crops and yields, open call | Crop insurance is a key element to increase the resilience of farmers, particularly small-scale farmers in countries highly exposed to the impact of climate change. Unlike traditional crop insurance that attempts to measure individual farm yields or revenues, index insurance makes use of variables exogenous to the individual policy-holder which have a strong correlation to losses. A major challenge in designing an index insurance product is minimizing basis risk, i.e., the potential mismatch between index triggered payouts and actual losses. The objective of this project is to develop, on the basis of the WII and AYII, a hybrid solution, namely the Weather Area Index Insurance (WAII), an index that on one hand will significantly improve the WII, and on the other hand will streamline the AYII. The reasons behind this new index are: WII is exclusively based on rainfall data, hence not considering when, where and how much crop area have been effectively planted and the seasonal phenological crop development. To overcome to this critical problem usually nominal cropping calendars are used, in the best case complemented by sporadic time-consuming field visits. This inefficient solution creates a high level of uncertainty in payouts and high moral hazard. AYII, as applied in RIICE, is doubtless an advanced and complete insurance index solution. However, yield estimation requires a plant growth simulation model specific to each crop (which also relies on soil conditions and agronomic practices). In essence, in those countries where RIICE is operated by the government, it acts as an incentive for the insurance industry to adopt AYII. Conversely, in new geographies, insurance companies tend to shy away from such solution because a calibration period of few years is needed. That is, an AYII solution should rather be understood as a long-term objective and not the starting point for developing insurance products for small-scale farmers when stepping into a new geography. |
| RepreSent: Non-supervised representation learning for Sentinels | The main objective of the RepreSent project is to capitalize on the potential of artificial intelligence (AI) and Earth observation (EO) by exploiting the non-supervised learning paradigms. In this context, it is essential to come up with [...] | DLR – GERMAN AEROSPACE CENTER (DE) | AI4EO | AI4EO, forestry, land cover, SAR, Sentinel-1, Sentinel-2, urban | The main objective of the RepreSent project is to capitalize on the potential of artificial intelligence (AI) and Earth observation (EO) by exploiting the non-supervised learning paradigms. In this context, it is essential to come up with non-supervised learning-based solutions for impactful use cases that use unlabeled EO data. The project started on April 1st, 2022 with the project kick-off on April 6th, 2022. The project reached successfully the milestone MS-1 in July 11th, 2022 and the milestone MS-2 in October 12th, 2022. The final review of the project took place successfully on May 11th, 2023 at ESRIN. Objectives Firstly, the consortium will investigate the non-supervised learning-based methods for EO, as one of project technical objective. Towards harnessing on the effectiveness of non-supervised learning and exploiting the multitude of unlabeled data, successful feature extractors will be built based on self-supervised learning-based pre-training and transfer learning from pre-trained networks. These techniques are grouped into three main categories: Self-supervised learning for uni-temporal tasks (e.g., Deep Clustering, Contrastive Learning, Bootstrap Your Own Latent, Meta-Learning), Change detection (e.g., Deep change vector analysis, Deep multi-temporal segmentation, Temporal contrastive learning), Time-series anomaly detection (e.g., LSTM based unsupervised approach, Graph neural networks based on a self‑supervised approach). DLR and EPFL will use their AI4EO network and they will establish contacts with other research groups addressing similar or related thematic areas in the AI/EO/NS community. Secondly, the validation of the technical objectives is fulfilled by the consortium by defining five use cases. These use cases are focus on the challenges of EO where either labelled data are scarce or the successful application of supervised methods requires many labels that are tedious or costly to collect. The validation was done on five use cases related to: UC1. Forest disturbance monitoring UC2. Automated Land Cover mapping UC3. Anomaly detection in long time series of PS-P InSAR UC4. Cloud detection, and removal UC5. Forest biomass estimation For these use cases, the required EO data is exploit the openly available Sentinel-1, Sentinel-2, and Landsat archives. The RepreSent EO use cases are tackling core business and scientific questions since they are tightly connected to e-GEOS and VTT core business areas and active projects (InSAR/ground motion and forestry, respectively). This is also ensuring a close link to users and stakeholders in the different sectors where the two partners are very well known. Finally, the non-supervised learning methods developed by the consortium were evaluated based on usual quantitative performance metrics along with qualitative analyses commenting on their generalization capability and versatility on different EO cases. AI4EOcommunity of players Each use case proposed within the project had a user target group. For example, for the use case on forestry, VTT used a wide community of academic and forestry users including forest owners via the Forestry TEP. On May 4th, 2023, an online workshop on Self-supervised learning (SSL) in Earth Observation based forest inventory was conducted by VTT and the ESA RepreSent project consortium. For the use case on anomaly detection, e-GEOS is in contact with several customers interested in the detection of anomalous points. The project partners were involved in the organization of special sessions at different conferences related to the topic of the RepreSent project. In June 2022 it was organized by EPFL and DLR the first special session at Living Planet Symposium (LPS’22) in Bonn, Germany entitled “Representation learning in remote sensing: from unsupervised to self- and meta-learning”, while in July 2022 an invited session was organized by EPFL and VTT at the ISPRS congress 2022 in Nice, France entitled “Unsupervised and weakly supervised deep learning for EO”. For 2023, the RepreSent team has organised a community invited session at IGARSS 2023 in Pasadena, USA. The session is titled “Representation learning in remote sensing” and will be composed of two sub sections (out of which of the accepted papers, two belong to the members of the consortium). Members of the team will chair the sessions in Pasadena. EPFL together with ESA are co-organiser of the EarthVision workshop at CVPR in 2022 and 2023. Finally, during the final review of the project at ESA in ESRIN, two public sessions were organised by the RepreSent consortium together with ESA under the topic AI4EO on SSL. Extension of RepreSent for Scaling-up The initial phase of the RepreSent project enabled us to delve into the field of representation learning, showcasing its vast potential in making EO data and methodologies broadly accessible without requiring extensive effort. From a technical perspective, the project has been successful, as evidenced by the positive feedback received from the academic community towards our publications and presentations, and the increasing interest in exploring, replicating, and expanding our developed methodologies. Furthermore, achieving our current TRL has initiated communication with a variety of stakeholders, including those in fields such as forest farming, environmental monitoring, and urban planning. The project extension started on February 1st, 2024 with the project kick-off on February 7th, 2024.The main objectives are Our first objective focuses on improvement of accuracy and timeliness of EO based forest mapping using multi-temporal and multi-sensor data (in contrast to studied earlier bi-temporal and single/bi-sensor approaches), leveraging self-supervised learning (SSL) methods Our second objective is to enhance our ability to detect building anomalies. Given the varied and changing nature of urban environments, we aim to expand the area of study. This expansion will allow us to better understand the patterns of anomalies across different urban landscapes. Our third objective focuses on the refinement of cloud detection methods. Recognizing the potential of self-supervised learning in cloud detection, achieving comparable accuracy as state-of-the-art supervised methods on a small-scale cloud dataset, we plan to extend our experiments to the CloudSEN12 dataset. This will provide us with a global scale of data for validating our approach Our final objective pertains to the continued and enhanced dissemination of our project’s outcomes. We aim to reach a broader scientific audience by publishing our findings in respected peer-reviewed journals. The extension consortium (DLR, VTT, and e-GEOS) considers three use cases for which a number of users have shown their interest. These use cases are: UC1. Multi-temporal and multi-sensor forest mapping UC2. Building anomaly detection UC3. Cloud detection |
| RESTORE-IT: GLOBAL SATELLITE-BASED IMPACT MONITORING TOOL FOR RESTORATION INITIATIVES | The Restore-IT project is a collaboration between academia, NGOs, and commercial satellite providers and is supported by the European Space Agency (ESA). Within the project, VanderSat , in collaboration with the University of Leicester – inspect [...] | VANDERSAT B.V. (NL) | Applications | permanently open call | The Restore-IT project is a collaboration between academia, NGOs, and commercial satellite providers and is supported by the European Space Agency (ESA). Within the project, VanderSat , in collaboration with the University of Leicester – inspect how factors such as surface temperature, soil moisture, and land cover can be combined to measure the impact of landscape restoration more accurately from space. To understand best what is needed for effective satellite monitoring, two case studies have been selected to test the new methodology (in Kenya and India) With this new way of impact monitoring, the progress of landscape restoration projects on a larger scale can be measured. |
| RIDESAT – RIver flow monitoring and Discharge Estimation by integrating multiple SATellite data | The RIDESAT Project (RIver flow monitoring and Discharge Estimation by integrating multiple SATellite data) aims at developing a new methodology for the joint exploitation of three sensors (altimeter, optical and thermal) for river flow [...] | CNR-RESEARCH INSTITUTE FOR GEO-HYDROLOGICAL PROTECTION – IRPI (IT) | Science | altimeter, permanently open call, science, water cycle and hydrology | The RIDESAT Project (RIver flow monitoring and Discharge Estimation by integrating multiple SATellite data) aims at developing a new methodology for the joint exploitation of three sensors (altimeter, optical and thermal) for river flow monitoring and discharge estimation. Even if with a number of limitations, satellite radar altimetry over surface inland water has demonstrated its potential in the estimation of water levels useful for hydrological applications. Optical sensors, thanks to their frequent revisit time (nearly daily) and large spatial coverage, are recently used to support the evaluation of the river discharge variations. Despite the moderate spatial resolution of the optical data (about 250 – 300 m), their complementary with radar altimeter data enables to benefit of the different characteristics of the satellite sensors. In particular, the combination of radar (i.e. altimeters), optical and thermal instruments (i.e., multispectral sensors), allows for a continuous monitoring of the inland water and, hence, of the river discharge. The RIDESAT Project aims at: better understanding the use of optical and thermal sensors through the study of the physical meaning behind the process and their field of applicability; and developing a procedure of merging the three different satellite data through a physically based method that uses hydraulic variables obtained by satellites (e.g. water height, slope, width, flow velocity). The goal is to provide, for the first time, an accurate satellite-based river discharge product for small to large rivers. In order to test the ability of the different sensors to retrieve the river discharge at global scale, 10 pilot sites are selected all over the world, based on the availability of in situ measurements of hydraulic and morphological variables: water level, cross section, width, surface and bottom slope, flow velocity and discharge. The selection of pilot sites is also based on the climatic area (Tropical, Arid, Temperate, Cold), flow regime (glacial, nival, pluvial and tropical pluvial) and the size of the basin (large, medium and small). The developed procedure and the results obtained in the RIDESAT project will have an impact both on the scientific and the operational communities. In this respect, the estimation of the river discharge has a large interest in the hydrology community and an efficient and productive procedure can prove an advancement for the understanding and the knowledge of the hydrological processes. Users and stakeholders potentially interested include space agencies, government agencies, basin authorities, civil protection authorities and, more in general, all the organisations interested in the sustainable management of water for people and societies. This 12 month activity will be led by CNR-IRPI (IT) with the participation of DTU (DK). The Project is now closed but the research activity is still ongoingunder the STREAMRIDE Project to explore the possibility of improving the RIDESAT algorithm andcomplementing it with a different satellite approach for riverdischarge estimation developed in the STREAM Project. |
| Road-DL: Development of a Road Pavement Condition Classifier Utilising Deep Learning Techniques Applied to SAR Data | The objective of ROAD-DL service is to provide road condition assessment based on remote sensing data. The service aims to provide up to date classification of specific features related with road condition that could trigger inspection or [...] | TELESPAZIO VEGA UK LIMITED (GB) | Enterprise | infrastructure, permanently open call, SAR, Sentinel-1 | The objective of ROAD-DL service is to provide road condition assessment based on remote sensing data. The service aims to provide up to date classification of specific features related with road condition that could trigger inspection or maintenance actions. Specifically, the service ingest Synthetic Aperture Radar (SAR) Sentinel-1 satellite images, provided by ESA through the Copernicus initiative. Telespazio UK built and tested an approach driven by Deep Learning (DL) to provide road condition assessment to National Highways (NH). The project used multi-temporal SAR Sentinel-1 satellite data and NH collected road condition parameters to train a neural network to identify damaged and degraded roads in the UK strategic road network. The DL classifiers were trained and validated with independent in-situ laser scanner measurement data, which is routinely collected by NH. The solution is easily scalable and shall act as a continuous monitoring service providing routine insights between ground-based surveys. |
| RS4EBV: Remote Sensing for Essential Biodiversity Variables (DUE Innovator III Series) | Biodiversity is facing a global crisis as evidenced by dramatic declines in species and habitats. Tracking the state of biodiversity requires operational monitoring systems underpinned by robust indicators. While these indicators convey [...] | UN WORLD CONSERVATION MONITORING CENTRE (UN-WCMC) (GB) | Applications | applications, ecosystems/vegetation | Biodiversity is facing a global crisis as evidenced by dramatic declines in species and habitats. Tracking the state of biodiversity requires operational monitoring systems underpinned by robust indicators. While these indicators convey invaluable information to policy makers on the status and trends of biodiversity, their use is hampered due to patchy geographical coverage of input data, differing measuring methodologies and insufficient time series data to track trends. These shortcomings have fuelled the development of Essential Biodiversity Variables (EBV) as an intermediate conceptual step between low-level primary observations and high-level policy-relevant indicators. The EBV conceptual framework has been conceived by a group of internationally ecologists under the lead of GEO-BON. The RS4EBV project aimed to explore, develop and test, through local-scale pilot studies, the potential of satellite remote sensing for selected EBVs such as Ecosystem Functional Diversity (FD), which is a measure of the components that influence how ecosystems operate and function. The project developed and tested remotely-sensed EBVs on biophysical variables (chlorophyll content, LAI and Land Surface Phenology) from S2 time series, and inferred information on the Functional Diversity (FD) of terrestrial ecosystems (diversity of plant community functional traits). The quality of the RS-based FD proxy was assessed, with some in-depth validation of the proposed approaches, in different terrestrial ecosystems such as natural grasslands (North Wyke, UK), Salt marshes (Schiermonnikoog Island, NL) and Temperate forests (Bavaria Forest, DE). The findings of the project have been transferred to the GEO BON working groups on Ecosystem Structure and Function, where the FD modelling approach will be further developed. |
| S14SCIENCE AMAZONAS | PROJECT GOALS The dense spatial and temporal coverage of the Amazon basin with Sentinel-1 Synthetic Aperture Radar scenes has opened vast potential for capturing the complexity in tropical forest loss and regrowth. Sentinel-1 for Science [...] | GISAT S.R.O. (CZ) | Science | carbon cycle, forestry, SAR, Sentinel-1 | PROJECT GOALS The dense spatial and temporal coverage of the Amazon basin with Sentinel-1 Synthetic Aperture Radar scenes has opened vast potential for capturing the complexity in tropical forest loss and regrowth. Sentinel-1 for Science Amazonas aims to: Develop, test and validate an operational-level Multi-temporal forest Change Detection (MCD) algorithm, Estimate carbon loss and gain from anthropogenic and natural land use changes (LUC) in the Amazonas based on the MCD outputs, and Perform scientific analysis and interpretation of the quantified carbon gain/loss, accounting for seasonal stressors such as severe droughts or fires. EO TECHNOLOGY The methods developed in Sentinel-1 for Science Amazonas integrate the current state-of-the-art research on SAR-based monitoring in the fields of not only forests, but also agriculture, wetlands and grasslands. The primary dataset used in the development of the Multi-temporal forest Change Detection (MCD) algorithm is the complex Sentinel-1 Interferometric Wide (IW) swath Single Look Complex (SLC) time series. These time-series are analysed by break-point detection, moving-window trend-fitting in the temporal and spatial domain.The algorithms are enriched with complementary data, such as L-band SAR (e.g. ALOS-2) or spaceborne LiDAR (e.g. GEDI). Forest carbon losses and gains are estimated through a rigorous statistical comparative analysis of existing datasets to the newest in-situ field data and LiDAR data, or local-scale calibration and fusion of such datasets. EXPECTED OUTCOMES The Sentinel-1 for Science Amazonas project is expected to publicly release forest loss and gain maps produced using the Multi-temporal forest Change Detection (MCD) algorithm. The maps will incorporate spatially and temporally explicit estimates of change, the type of change (e.g. deforestation, degradation, areas of natural or assisted regrowth), severity of change, forest carbon gains/losses and the associated uncertainty in estimates.The study areas of the project include pilot sites in Madre de Dios, Mato Grosso and Manaus, and will be up-scaled to the extent of the Amazon basin. |
| S2 for Land and Water, Change Detection/Multi-temporal | The project aims at defining the scientific methods and the related prototype algorithms for addressing three main challenges with the multispectral and multiresolution Sentinel 2 images: 1) change detection; 2) analysis of image time series; [...] | UNIVERSITÀ DEGLI STUDI DI TRENTO (IT) | Science | land cover, science | The project aims at defining the scientific methods and the related prototype algorithms for addressing three main challenges with the multispectral and multiresolution Sentinel 2 images: 1) change detection; 2) analysis of image time series; and 3) updating of land-cover maps. |
| S2 for Land and Water, Coastal and Inland Waters Theme | This project aims at developing and validating inland water circulation models coupled with remote sensing data to better understand the processes involved in these water bodies. It will investigate the potential of the S-2 radiometric data [...] | ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE (CH) | Science | coastal zone, land, water resources | This project aims at developing and validating inland water circulation models coupled with remote sensing data to better understand the processes involved in these water bodies. It will investigate the potential of the S-2 radiometric data products to constrain hydrodynamic and ecological models of at least three water body types covering as wide a range as possible of eutrophic levels and ecological niches. Inland waters are increasingly facing external pressures. Their adaptation and changes have to be understood and monitored efficiently to provide valuable recommendations to decision makers. Over the last decades, different research communities have focused on this problem using different approaches and information sources. The current challenge is to couple those sources, consisting of in situ measurements, remote sensing data, and data generated by three-dimensional hydrodynamic and water quality models. The goal is thereby to provide timely, scientifically credible, and policy-relevant environmental information, in order to assist stakeholders in evidence-based decision-making and sustainable management. The coupling approach envisaged in the project implies mutual feedback mechanisms between these three information sources. Model simulations are improved through the assimilation of in situ measurements and remotely sensed products. Remote sensing image processing is improved through parameterization with in situ measurements and predictions by hydrodynamic and biological models. Moreover, in situ measurements provide for an absolute system calibration standard, which achieves a better representativeness when carried out along instantaneous gradients known from remotely sensed products and model simulations. The coupling approach is validated with at least three different lakes of different size, trophic status and watershed properties. For each lake, particular attention is given to biophysical processes calling for high spatio-temporal resolution that distinguishes Sentinel-2 from other Earth observation satellites. This unprecedented spatial resolution requires dedicated high resolution process-oriented field campaigns that will allow to quantitatively estimate the benefit of the coupling approach compared to the traditional modelling scheme. Besides the high horizontal resolution, a second key coupling focus is on the effect of the vertical structure of inland water bodies. The selection of suitable inherent optical properties and the assumption of a vertically homogeneous euphotic layer traditionally causes large uncertainties in remotely-sensed water quality products, unless effectively constrained by additional complementary information. Similarly, changes in light penetration depth associated with matters and vertical density stratification typically induce large uncertainties in the heat absorption and drastically affect results predicted by coupled hydrodynamic and water quality models. The energy transfer from the atmosphere to the lake will be constrained by spatial and temporal data assimilation of lake surface temperature from medium-resolution thermal remote sensing products and light penetration from high-resolution Sentinel-2 products. Once correctly forced, output of the hydrodynamic and water quality models, such as CHL, will also be constrained through data assimilation with Sentinel-2 products and in situ observations. This multistep control of the models is a cornerstone in the development of operational water quality information systems. The development and implementation of the approach will be conducted by an interdisciplinary team of scientists with demonstrated experience in the field of system analysis by means of in situ measurements, remote sensing and modelling. Dissemination of software and instructions on how to effectively use this software at the project end will enable the adaptation of the approach for a larger, more diverse, number of water bodies. |
| SAR Altimetry Coastal & Open Ocean Performance (SCOOP) | SCOOP (SAR Altimetry Coastal & Open Ocean Performance) is a project funded under the ESA SEOM (Scientific Exploitation of Operational Missions) Programme Element, started in September 2015, to characterise the expected performance of [...] | SATELLITE OCEANOGRAPHIC CONSULTANTS LTD. (GB) | Science | altimeter, oceans | SCOOP (SAR Altimetry Coastal & Open Ocean Performance) is a project funded under the ESA SEOM (Scientific Exploitation of Operational Missions) Programme Element, started in September 2015, to characterise the expected performance of Sentinel-3 SRAL SAR mode altimeter products, in the coastal zone and open ocean, and then to develop and evaluate enhancements to the baseline processing scheme in terms of improvements to ocean measurements. Another objective is to develop and evaluate an improved Wet Troposphere correction for Sentinel-3, based on the measurements from the on-board MWR, further enhanced mostly in the coastal and polar regions using third party data, and provide recommendations for use. |
| SAR2CUBE | One of the biggest entry level hurdles for integrating SAR data into modern earth observation analysis chains, is still the complexity of the data itself. Opposed to optical or multi-spectral data, which relates much more directly to the way [...] | EURAC RESEARCH – ACCADEMIA EUROPEA (IT) | Digital Platform Services | generic platform service, SAR, Sentinel-1 | One of the biggest entry level hurdles for integrating SAR data into modern earth observation analysis chains, is still the complexity of the data itself. Opposed to optical or multi-spectral data, which relates much more directly to the way human vision works and is hence more natural to interpret, SAR registers signals that are not natural to human senses, both due to the typically sight looking geometry and to the wavelengths of the electromagnetic spectrum in which SAR typically operates. Operating in this very different spectrum, however, gives the SAR signals unique characteristics, which can be extremely beneficial in many observation scenarios. One of the most obvious and often quoted is the ability to see through clouds and hence SAR is providing a more reliable data source in areas that are frequently cloud covered. Another important domain of SAR are the interferometric observations, which allow for detection of terrain movements or the change of signal strength over time and finally polarimetry, which allows for assumptions on the scatter mechanisms in the physical path of the signal. SAR2CUBE as a project foresees the development of a processing chain and prototype implementation for organizing Sentinel-1 SLC data in efficient data cubes, both from the point of view of the data provider and from the point of view of the consumer of the data, in order to foster the uptake of SAR data into everyday processing chains. This comprises three main layers, pre-processing, data cube setup and post processing on the fly. A number of different implementation scenarios are planned to be benchmarked in a performance test suite, including necessary space requirements for hosting the data and speed of access from the user perspective. Finally, three use cases have been defined to test the suitability of the developed SAR data cubes for analysis chains, including analysis of terrain motion with PSI techniques, land cover classification based on interferometric coherence and change detection based on back scatter time series The SAR2CUBE project is defined to satisfy simultaneously two objectives. The first one is to facilitate the use of SAR products in the scientific EO community and to promote them as relevant EO assets. The Sentinel mission within the Copernicus program defines a new playground where to exploit an extraordinary and unique amount of EO information. In particular, the radar pair defined by the twins Sentinel-1A and Sentinel-1B is offering a constant stream of SAR data since they were launched, late 2014 and early 2016 respectively. However, the interferometric capabilities provided by this source are underused. The particular nature of the complex interferometric data often presents a barrier to incorporate these data within the processing chains. The obvious nature of other kinds of sensors, such as optical or multi-spectral data, facilitates the incorporation of these products into different analysis frameworks. To reduce the entry-level barrier of the InSAR-derived products the SAR2CUBE project is designed to provide both SAR and InSAR analysis-ready data (ARD) specifically defined to achieve efficiency and flexibility. Both requirements shall be jointly satisfied to create a reliable and useful framework for the community. The second objective and equally important is to reduce significantly the amount of storage space that an interferometric SAR context requires. A stack of SAR images responds to a monotonic temporal sequence of acquisitions. Each moment the platform passes by the area of interest a radar acquisition is obtained characterizing uniquely with a timestamp the acquired data. Each image in the temporal sequence is of complex nature, thus they are composed of two bands or channels, the amplitude and the phase. Moreover, if the SAR system has any polarimetric capability the complex acquisition will be obtained simultaneously for different polarisation combinations. SAR interferometry consists of combining pairs of SAR acquisitions. In general, the information contained in the interferogram product is related to the characteristics, evolution and location of the scattering mechanisms in the scene from a relative perspective, i.e. the two images considered. The generation of a useful interferometric stack, multiple pairs of SAR images combined, depends mainly on the application, but the number of possible interferometric products grows quadratically with respect the number of acquisitions, when considering all temporal baselines. To limit the required space for the interferometric context the SAR2CUBE project defines to incorporate a software prototype interface to ARD providing not only access but also on-the-fly processing capabilities. The performance is very crucial in the whole setup and a balance shall be found between the cost for storage and the cost for computation. Generally, access to analysis ready will be faster if the data is already pre-computed to a higher level, but comes with a higher storage cost, especially in the case of interferometric products. |
| SAR4URBAN: SAR for urbanisation monitoring (DUE Innovator III Series) | From the beginning of the years 2000, more than half of the world population live in cities and the overall trend of urbanization is growing at an unprecedented speed. The use of Earth Observations and their integration with other source of [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Applications | applications, urban | From the beginning of the years 2000, more than half of the world population live in cities and the overall trend of urbanization is growing at an unprecedented speed. The use of Earth Observations and their integration with other source of information into effective urban planning tools can produce a quantum leap in the capacity of countries to track progress towards and achieving international urban development goals. One of the main sources of information on urban areas that is essential to monitor precisely and with regular periodic updates is the monitoring human settlements. The importance to have up-to-date information on human settlements does not only regard urban areas but also rural and peri-urban areas where most of the un-controlled developments are taking place, hence the urgency to have regular and updated information on the evolution of human settlements worldwide . The advent of continuous streams of high quality and free of charge satellite observations such as the Sentinels of the European Copernicus program, in combination with the emergence of automated methods for big data processing and image analysis and the democratization of computing costs, have offered unprecedented opportunities to improve our capacities to efficiently monitor the changes and trends in urban development globally. The SAR4URBAN project developed an innovative approach to automatically extract built-up areas from the joint use of C-band SAR and multi-spectral optical data. The novelty of the method has been the integration of temporal statistics from SAR and optical data into large-scale urban mapping with fully automatic extraction of training samples, machine learning classification and post-classification enhancement. The main output of the SAR4URBAN project has been the World Settlement Footprint (WSF) 2015, the first global map of human settlements generated globally from the joint processing of optical and radar imagery. The WSF 2015 is available at 10m spatial resolution with a global coverage (in urban, peri-urban and rural areas) and is based on the processing of all Sentinel-1 and Landsat-8 imagery acquired in 2014 and 2015. |
| SAR4Wildfire | The objective of tge SAR4Wildfire project is to develop a novel and automatic method, using Sentinel-1 SAR time series and a deep learning framework, for near real-time wildfire progression monitoring and burn severity mapping in preselected [...] | KUNGLIGA TEKNISKA HÖGSKOLAN (SE) | Applications | carbon cycle, permanently open call, SAR, Sentinel-1 | The objective of tge SAR4Wildfire project is to develop a novel and automatic method, using Sentinel-1 SAR time series and a deep learning framework, for near real-time wildfire progression monitoring and burn severity mapping in preselected wildfire sites in Sweden and British Columbia, Canada. Whenever available, Sentinel-2 MSI data will be incorporated in the framework for active fire detection and burn severity mapping. Once validated the method will be applied to several 2017 and 2018 wildfire sites around the world such as California (e.g., Camp Fire and/or Mendocino Complex Fire), Russia (e.g., Siberia Fire) and Africa to explore its global applicability. |
| Sargassum monitoring service | The project objective is to develop and implement an innovative automated service based on Earth Observation (EO) data to monitor floating Sargassum algae in the Caribbean area, estimate their drift and eventual landings on the coasts, and [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Applications | applications, coastal zone, oceans, permanently open call | The project objective is to develop and implement an innovative automated service based on Earth Observation (EO) data to monitor floating Sargassum algae in the Caribbean area, estimate their drift and eventual landings on the coasts, and provide dedicated bulletins to the end-users. |
| Satellite Oceanographic Datasets for Acidification (OceanSODA) | Since the beginning of the industrial revolution humans have released approximately 500 billion metric tons of carbon into the atmosphere from burning fossil fuels, cement production and land-use changes. About 30% of this carbon dioxide (CO2) [...] | UNIVERSITY OF EXETER (GB) | Science | carbon cycle, carbon science cluster, climate, ocean science cluster, oceans, science, SMOS, SST | Since the beginning of the industrial revolution humans have released approximately 500 billion metric tons of carbon into the atmosphere from burning fossil fuels, cement production and land-use changes. About 30% of this carbon dioxide (CO2) has been taken up by the oceans, largely by the dissolution of this CO2 into seawater and subsequent reactions with the dissolved carbonate ions present in seawater. Anthropogenic emissions CO2 levelled out in 2016, but have since begun to increase again, rendering absolutely critical to monitor ocean carbon uptake. The long-term uptake of carbon dioxide by the oceans is reducing the ocean pH, a process commonly known as ocean acidification. The uptake is also altering the ocean chemistry and ecology, impacting marine ecosystems on which we rely. Recent work has begun to investigate the use of satellite Earth Observation, especially focusing on satellite sea surface salinity and sea surface temperature data, exploiting empirical methods to monitor surface-ocean carbonate chemistry. These techniques complement in situ approaches by enabling the first synoptic-scale observation-based assessments of the global oceans and are particularly well suited to monitoring large episodic events. The Satellite Oceanographic Datasets for Acidification (OceanSODA) project will further develop the use of satellite Earth Observation for studying and monitoring marine carbonate chemistry. Besides further developments of algorithms linking satellite variables with marine carbonate system parameters and the associated validation, a distinct focus will be on selected scientific studies and downstream impact assessment. This will include characterising and analysing how upwelling (of low pH waters) and compound events impact the carbonate system, and characterising the flow and impact on marine ecosystems of low pH waters from large river systems. The project will also work closely with the World Wide Fund for Nature (WWF), the U.S. National Oceanic and Atmospheric Administration (NOAA) and The Ocean Foundation, to support their work on coral reef conservation, the designation of marine protected areas and investigation of wild fisheries health and sustainable management. |
| SaTellite-based Run-off Evaluation And Mapping (STREAM) | The STREAM Project (SaTellite based Runoff Evaluation And Mapping), led by CNR-IRPI with the participation of the Institute of Geodesy (GIS) at University of Stuttgart, aimed at developing innovative methods able to maximize the recovery of [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | applications, permanently open call, science, water cycle and hydrology | The STREAM Project (SaTellite based Runoff Evaluation And Mapping), led by CNR-IRPI with the participation of the Institute of Geodesy (GIS) at University of Stuttgart, aimed at developing innovative methods able to maximize the recovery of information on runoff contained in current satellite observations of climatic and environmental variables (i.e., precipitation, soil moisture, terrestrial water storage anomalies). In situ observations of river discharge, used for the quantification of total runoff, typically offer little information on its spatial distribution within a watershed. Moreover, river discharge observation networks suffer from many limitations such as low station density and often incomplete temporal coverage, substantial delay in data access and large decline in monitoring capacity. Paradoxically, this issue is exacerbated in poor non-industrialized nations where the knowledge of the terrestrial water dynamics is even more important. On the other hand, land surface and hydrological models are very highly data demanding, based upon complex modelling systems and might suffer from an incorrect representation of the pre-storm condition, which is paramount for a proper runoff estimation In this context, the STREAM project aimed at: Investigate the possibility to use satellite data for the hydrological cycle modeling; and developing a conceptual hydrological model, STREAM, directly ingesting satellite observation of soil moisture (SM), precipitation (P) and terrestrial water storage anomalies (TWSA). The goal of the project was to estimate runoff and river discharge time series for large basins in the world at high spatial and temporal resolution. During the 12 months of project activity, a quality assessment of STREAM river discharge and runoff estimates was carried out over five basins (Mississippi, Amazon, Danube, Niger and Murray-Darling). In these areas, the model was able to accurately simulate continuous daily river discharge and total runoff time series for the period 2003-2016. Only for specific case studies, such as for basins with high human impact or for highly vegetated areas, unsatisfactory model performances were found. To address this issue, the project activity has been extended of 1 year through a CCN (STREAMRIDE) to explore the possibility both to improve the STREAM model and to complement the model with a different satellite approach for river discharge estimation (RIDESAT) |
| SatHound: Multi-object detection solution based on artificial intelligence for non-expert EO users | SatHound is a solution to allow non-technical users configuring and executing multi-object detection processes over satellite images, based on deep learning technologies providing the following features: Two modes of operation in a clean [...] | THALES ALENIA SPACE ESPANA (ES) | Enterprise | permanently open call, platforms | SatHound is a solution to allow non-technical users configuring and executing multi-object detection processes over satellite images, based on deep learning technologies providing the following features: Two modes of operation in a clean and powerful user interface with Web-GIS capabilities: The training mode is used for teaching the system how to recognize new objects or to improve previous trainings with new examples. No more training datasets to be shared! This is a user-driven training mode, allowing to define unlimited detection targets. The hound mode is used for searching target objects on different map areas using already acquired knowledge. Batch training lets the user to continue using the hound mode while a SatHound improves it cognitive functions in background. Training status can be consulted at any time. Models are trained incrementally providing fast trainings and the possibility to roll-back to previous knowledge status in case of a wrong training. REST API for integrating with other systems. This lets external systems to scan geographic areas using the hound mode as you would do using the user interface. On-premise, Hybrid or Cloud deployment capabilities. The scalable architecture lets you scale-out the whole application for high availability or heavy load scenarios A local catalogue for hosting the satellite data products used in the searches. |
| SDG 15.2.1 EO Pathfinder – EO for Sustainable Forest Management | The SDG Pathfinder project – EO for Sustainable Forest Management will develop and showcase in partnership with the custodian agency FAO innovative EO approaches to produce indicators on the sustainable management of natural, semi-natural and [...] | IABG MBH (DE) | Applications | applications, forestry, sustainable development | The SDG Pathfinder project – EO for Sustainable Forest Management will develop and showcase in partnership with the custodian agency FAO innovative EO approaches to produce indicators on the sustainable management of natural, semi-natural and planted forests. It will benefit from improved data availability to support the SDG 15 Life on Land with the SDG Target indicators 15.1.1 and 15.2.1 to monitor changes in global forest and make them available to a wide community. The project will propose SDG sub-indicators on forest area net change, Above Ground Biomass, Forest Protected Areas, and Forest Management. Additional indicators and metrices are planned for forest characterisation, condition monitoring, homogeneity, change in erosion/landslide risk and a landscape metrics. |
| SEA-SPARK-ADVANCED AI/ML VESSEL DETECTION AND CLASSIFICATION ON HIGH-RES SAR IMAGERY | The SEA-SPARK project aims to design, implement and experimentally evaluate deep learning based advanced algorithms for high-resolution Synthetic Aperture Radar (SAR) satellite imagery to detect and classify maritime vessels ranging from small [...] | SPACEKNOW, INC., odštěpný závod (CZ) | Enterprise | maritime spatial planning, SAR | The SEA-SPARK project aims to design, implement and experimentally evaluate deep learning based advanced algorithms for high-resolution Synthetic Aperture Radar (SAR) satellite imagery to detect and classify maritime vessels ranging from small transport and commercial vessels to large tankers and military ships. SpaceKnow will contribute to the state-of-the-art by improving performance and creating a robust and trustworthy solution, delivering better insights to customers reliant on precise and persistent maritime monitoring, vessel detection, and classification. The specific applications range from maritime and coastal law enforcement (illegal fishing, migration, embargoed goods transport, pollution monitoring, detection, and prevention), port and coastal security to complex geopolitical issues like maritime border surveillance, exclusive economic zone sovereignty, and national security. Special focus will be on exploration, recognition, and analysis of hard examples for training of deep neural networks. Hard examples are usually defined by their unique and diverse attributes or appearance, to be found very sparsely, thus creating a significant imbalance with respect to the rest of the data. The results and comparisons will be demonstrated by thorough evaluations on manually labeled testing data selected specifically to benchmark the ability of the DNN to perform well on these hard datasets. |
| SeasFire: Earth System Deep learning for Seasonal Fire Forecasting in Europe | The SeasFire project, funded by the ESA, is taking an innovative approach to predicting seasonal wildfire patterns in Europe. SeasFire uses cutting-edge technology, such as modern deep learning models and Earth Observation data, to explore the [...] | NATIONAL OBSERVATORY OF ATHENS (GR) | AI4EO | AI4EO, ecosystems/vegetation, generic platform service, sea surface topography, wildfires | The SeasFire project, funded by the ESA, is taking an innovative approach to predicting seasonal wildfire patterns in Europe. SeasFire uses cutting-edge technology, such as modern deep learning models and Earth Observation data, to explore the spatio-temporal connections between atmospheric conditions and fire regimes to gain valuable insights into predicting potential wildfires. The project aligns with the ESA’s mission to develop innovative applications of Earth Observation data to address important societal and environmental challenges. Achievements A. SeasFire Cube: a public, global, analysis-ready, cloud-friendly dataset of burned areas, fire drivers and ocean-climate indices. We propose it as a test bed for wildfire-related models at sub-seasonal to seasonal scales. SeasFire Cube, includes: 30 global variables related to fire drivers, burned areas and fire emissions. Global extent from 2001 to 2021 at 8-day x 0.25° x 0.25° resolution. B. Data Analytics and Causality: Explored seasonal and temporal patterns in fire occurrence data by analyzing the historical trends and patterns in the data on different temporal scales (monthly, annual) and areas (biomes, GFED areas). Conducted also causal analysis in timeseries of weather variables, ocean climate indices and burnt areas in Europe’s biomes, to identify causal links between those variables at different time lags, through lagged independence tests. C. Burned Area Pattern Forecasting based on Machine Learning shows good predictive skill several weeks and even months in advance. The machine learning models we developed are: (a) A segmentation-based U-Net takes as input snapshots of the fire drivers and is trained to predict the burned area patterns in the future. It demonstrates a higher predictive skill than the statistical baseline of the average seasonal cycle and motivates the use of Deep Learning for the problem. (b) Graph image-based models, can handle long-range interactions and provide explanations through the learned edge connections. Those connections could help identify similar fire regimes. (c) A Graph Neural Network with temporal attention, can leverage local, mid-range and long range spatial connections profiting from the versatility of graph-based modeling. (d) Transformer-based architecture, is the first model that combines information from local fire drivers and oceanic indices that are relevant in larger temporal scales. Importantly, it is shown that such models can enhance predictive capabilities, as they achieve the best performance. D. A. prototype application has been developed based on the U-Net model and ERA5 data, producing real-time predictions of the burned area patterns for the next 6 weeks in Europe. Though the application cannot serve yet as an operational tool, it demonstrates the road from research to production and guides future steps. |
| Semi-supervised SENtinel-2 TREE Species Detection (SENTREE) | The objective of the SENTREE (Semi-supervised SENtinel-2 TREE Species Detection) project is to detect tree species in Norwegian production forests by developing deep learning models which will combine high resolution aerial imagery with [...] | Science [&] Technology Norway (NO) | Applications | applications, forestry, permanently open call, Sentinel-2 | The objective of the SENTREE (Semi-supervised SENtinel-2 TREE Species Detection) project is to detect tree species in Norwegian production forests by developing deep learning models which will combine high resolution aerial imagery with Sentinel-2 data. A major challenge in utilizing deep learning for tree species detection is the limited amount of training labels and their quality. The SENTREE project will address these issues with semi-supervised learning, noise tolerant training schemes and with automatic label noise detection. The results will be evaluated on a large area covering multiple municipalities in Norway. Allskog SA is participating in this project as a pilot customer, providing ground truth data, aerial imagery, domain knowledge, and support on validation activities. The project is primed by Science [&] Technology AS and funded by ESA under the EO Science for Society Permanently Open Call funding mechanism |
| SEN-ET: Sentinels for Evapotranspiration | Satellite remote sensing of evapotranspiration is an essential part of the global observation system and provides inputs for agriculture, water resources management, weather forecasts, climate studies and many other applications. Easy access to [...] | DHI GRAS A/S (DK) | Science | science, water cycle and hydrology | Satellite remote sensing of evapotranspiration is an essential part of the global observation system and provides inputs for agriculture, water resources management, weather forecasts, climate studies and many other applications. Easy access to reliable estimations of Evapotranspiration (ET) is considered a key requirement within these domains, and ET holds a vast potential to assist in the current attempts of meeting several of the UN Sustainable Development Goals (SDG), in particular SDG2 – zero hunger, SDG6 – clean water and sanitation and SDG13 – Climate action. In this context, the European Space Agency (ESA) is funding the Sentinels for Evapotranspiration (SEN-ET) project. The main objective of SEN-ET is to develop an optimal methodology for estimating ET at both fine (tens of meters) and coarse (kilometre) spatial scales, based on synergistic use of Sentinel 2 and Sentinel 3 satellites’ observations. The final methodology will be implemented as an open source software available freely to all users. For further details, see the Project page or contact the consortium. |
| SEN3GCP – Sentinel for 3D Ground Control Point | SEN3GCP is conceived as a service that will provide GCPs (Ground Control Points) and precise co-registration of EO products as an automated service accessible via the web and API. The service will be based on a global database of GCPs that is [...] | Planetek Italia (IT) | Digital Platform Services | generic platform service, permanently open call, platforms, SAR | SEN3GCP is conceived as a service that will provide GCPs (Ground Control Points) and precise co-registration of EO products as an automated service accessible via the web and API. The service will be based on a global database of GCPs that is derived from SAR imagery (3D coordinates including height information) and for which corresponding image chips of multispectral data are derived and maintained. The implemented service will provide GCPs via API and other interfaces. The service will also provide a mechanism for precise co-registration of EO data enabling for example the precise co-registration of multi-spectral and SAR data. |
| Sen4CAP: Sentinels for the Common Agricultural Policy | The Sen4CAP project aims at providing to the European and national stakeholders of the European Common Agricultural Policy (CAP) validated algorithms, products and best practices for agriculture monitoring relevant for the management of the CAP. [...] | UNIVERSITY OF CATHOLIQUE DE LOUVAIN (BE) | Applications | agriculture, applications | The Sen4CAP project aims at providing to the European and national stakeholders of the European Common Agricultural Policy (CAP) validated algorithms, products and best practices for agriculture monitoring relevant for the management of the CAP. Special attention shall be given to provide evidence how Sentinel-1 and Sentinel-2 derived information can support the modernization and simplification of the CAP in the post 2020 timeframe. The Sen4CAP project will be developed in close collaboration with DG-Agri, DG-JRC, DG-Grow and in particular with 6 selected national Paying Agencies. Demonstrations and use cases in the shall be conducted in the context of the Paying Agency operations up to national scale addressing a range of monitoring aspects in the IACS cycle including the greening measures of the CAP. Sen4CAP has provided first evidence to Direct Payment Committee on the use of Copernicus for the new CAP monitoring approach which has been announced by DG-Agri in May 2018. |
| SEN4CARBON Theme 1: Terrestrial Gross Primary Production (SEN4GPP) | The objective of the Sen4GPP project is to assess time-space variability of terrestrial gross primary production (GPP) of terrestrial ecosystems by a synergistic exploitation of the complementary information provided by the Sentinel [...] | NOVELTIS SAS (FR) | Science | carbon cycle, carbon science cluster, science, Sentinel-1, Sentinel-2, Sentinel-3, Sentinel-5P | The objective of the Sen4GPP project is to assess time-space variability of terrestrial gross primary production (GPP) of terrestrial ecosystems by a synergistic exploitation of the complementary information provided by the Sentinel missions (Sentinel-2, Sentinel-3 and Sentinel-5P) at multiple spatial and temporal resolutions, as well as other Earth Observation and in situ data. |
| SEN4CARBON Theme 2: Fire Dynamics (SENSE4FIRE) | Based on the new possibilities of the Sentinel series of satellites, this project aims to develop a highly novel approach to derive global fire emissions estimates based on the characterisation of individual fires and their behaviour. These data [...] | TECHNISCHE UNIVERSITAT DRESDEN (DE) | Science | carbon cycle, carbon science cluster, science, Sentinel-1, Sentinel-2, Sentinel-3, Sentinel-5P | Based on the new possibilities of the Sentinel series of satellites, this project aims to develop a highly novel approach to derive global fire emissions estimates based on the characterisation of individual fires and their behaviour. These data will be combined with bottom-up estimates of fuel and combustion and top-down constraints on total carbon emissions and emissions factors. Furthermore, observations of atmospheric composition will be exploited to provide an uncertainty assessment from top-down emission estimation. The new approach will highlight the power of Sentinels to reduce emissions uncertainty, understand direct and indirect effects of fire on long-term changes in the carbon cycle, and highlight the linkages between fuels, fire behaviour, and emissions with the potential of improved fire predictions. |
| SEN4STAT – Sentinels For Agriculture Statistics | Agricultural monitoring at national scale is a prerequisite for assessing and analyzing the agricultural resources by mandated authorities, usually the agricultural National Statistical Offices (NSOs). NSO collect in general national [...] | UNIVERSITY OF CATHOLIQUE DE LOUVAIN (BE) | Applications | agriculture, applications, Sentinel-1, Sentinel-2, sustainable development | Agricultural monitoring at national scale is a prerequisite for assessing and analyzing the agricultural resources by mandated authorities, usually the agricultural National Statistical Offices (NSOs). NSO collect in general national agricultural monitoring data by farm and household surveys. Recognizing the limitations of the current agricultural data collection in developing, emerging as well as in industrialized countries, key international bodies and UN agencies aim to improve and enhance the current practices in agriculture data collection and have referred to the potential of satellite Earth Observation for agricultural statistics. |
| SenCYF: Sentinel-2-based estimation and forecasting of winter wheat crop yield at field scale, with national coverage | The SenCYF project proposes an innovative crop yield forecasting model based on Sentinel-2 data, validated with a France-wide in situ yield data set. It aims at addressing two core scientific questions: What are the performances of a nation-wide [...] | UNIVERSITY OF CATHOLIQUE DE LOUVAIN (BE) | Science | agriculture, permanently open call, science, Sentinel-2 | The SenCYF project proposes an innovative crop yield forecasting model based on Sentinel-2 data, validated with a France-wide in situ yield data set. It aims at addressing two core scientific questions: What are the performances of a nation-wide S2-based winter wheat yield estimation model at farm level? What are the performances of a nation-wide S2-based winter wheat yield-forecasting model at farm level one month before harvest? |
| SenSPa – Sentinels for Sustainable Pasture Management | Grasslands are a major part of the global ecosystem, covering 37 % of the earth's terrestrial area. For a variety of reasons, mostly related to overgrazing and the resulting problems of soil erosion and weed encroachment, many of the world's [...] | kartECO – Environmental and Energy (GR) | Sustainable Development | ecosystems/vegetation, permanently open call | Grasslands are a major part of the global ecosystem, covering 37 % of the earth’s terrestrial area. For a variety of reasons, mostly related to overgrazing and the resulting problems of soil erosion and weed encroachment, many of the world’s natural grasslands are in poor condition and showing signs of degradation. There is general agreement that effective management of grasslands would make a significant contribution to global food security and mitigating greenhouse gas emissions. However putting in place effective monitoring systems supporting management policies is complex. Considering only the use of grasslands for pasture, governmental authorities, policy makers, land managers and livestock farmers have to take decisions about sustainable pasture management according to the rangeland productivity and status. However, collecting field data regarding the current condition of vegetation (plant cover, forage production) is time and labour intensive. This project is developing prototype capabilities to prove systematic information at a range of scales (local, national, regional) to support estimation of the primary grassland status indicators characteristics such as sward height, biomass, quality, phenological stage, productivity level, species composition. Sentinel 2 measurement of the reflectance at visible and infrared wavelengths can enable discrimination of different grassland status at national and local scales, relying on the efficient coupling of remote sensing data with in-situ data for the development of efficient predictive models. Especially reflectance at the red edge part of the spectrum, where there is a rapid increase in reflectance from the red to NIR reflectance, has a strong correlation with the grass chlorophyll content of the canopy and the leaves. Inclusion of measurements made in a red-edge channel are expected to be a reliable indicator for grassland status, relating to foliar chlorophyll content, vegetation stress, plant chlorophyll concentration, and leaf area index. Additionally, the project will investigate the use of time series of imagery acquired through the growing season to provide maximum information on yields and management. The prototype capabilities are being developed, demonstrated and validated for grassland areas in Azerbaijan. |
| SentiCheck: Sentinel Data-Based Service for Remote Monitoring of Subsoil Use and Detection of Possible Illegal Mining | The main objective of this activity is to develop an automated Sentinel-based service for remote and regular monitoring of subsoil use in open-cast mining areas with a monthly update frequency and 0.5 ha minimum detectable area to support [...] | Institute for Environmental Solutions (LV) | Enterprise | generic platform service, mining | The main objective of this activity is to develop an automated Sentinel-based service for remote and regular monitoring of subsoil use in open-cast mining areas with a monthly update frequency and 0.5 ha minimum detectable area to support control of subsoil use and detection of possible illegal mining. The main natural resources located under the soil in Latvia are sand-gravel, sand, dolomite, clay, gypsum, limestone, quartz sand and peat which generates around 3.5 million Euro in tax revenue annually. Illegal activities, like mining without a license or inappropriate recultivation of mining sites, are intentionally concealed by the perpetrators, where expert estimates attribute the lost annual revenue from these illegal activities to 300-400 thousand Euro annually. Regular onsite monitoring of open-cast mining sites is performed by the State Environment Service (SES) and is time and resource consuming. SES are interested in the regular and remote screening approach of open-cast mining sites to optimise its onsite control process. |
| Sentinel 2/3 Synergy Products | The objective of the project is to use Data Assimilation techniques to generate land surface products combining the data from Sentinels 2 and 3. Building upon the work undertaken in OPTIRAD, this project extends the capabilities of the system [...] | ASSIMILA LTD (GB) | Science | The objective of the project is to use Data Assimilation techniques to generate land surface products combining the data from Sentinels 2 and 3. Building upon the work undertaken in OPTIRAD, this project extends the capabilities of the system to include observation operators in the thermal part of the spectrum. Components will be added to the system to incorporate the functions of the SCOPE radiative transfer model. This will allow the informal from the thermal domain from Sentinel-3 to be combined with the high spectral resolution visible and near infrared information from Sentinel-2. The project will also implement a series of efficiency improvements to the algorithms to speed up the processing, as the current version is very compute intensive. | |
| Sentinel coastal charting worldwide | The advent, with Sentinel-2, of a satellite constellation offering High Resolution (HR), high revisit time and free images has raised encouraging hopes amongst Coastal States and the Maritime community of Users who, in 2018, still suffer from [...] | ARGANS LIMITED (GB) | Applications | marine environment, permanently open call | The advent, with Sentinel-2, of a satellite constellation offering High Resolution (HR), high revisit time and free images has raised encouraging hopes amongst Coastal States and the Maritime community of Users who, in 2018, still suffer from the persistence of inaccurate nautical charts. These expectations however did not materialise because the Government agencies in charge of producing official charts still consider they do not have a reliable tool to take advantage of satellite imagery. Thirty years after it was first introduced in its national chart series with immense caveat by the French Hydrographic Office (Shom), Satellite Derived Bathymetry (SDB) is still the object of a global rejection by the International Hydrographic Organisation (IHO)’s Member States and professional users primarily concerned by Safety of navigation and the catastrophic consequences of ship groundings. Many of the contributing factors to this are well known. To address the concerns from the perspective of the hydrographic community this project is providing a structured assessment of the use of EO as a strictly hydrographic tool (ie not just an estimation of water depth). This will require a clarification of the relationship between rigorous radiation transfer equations and practical charting methods, completing radiative transfer theory to address priority gaps from the perspective of the national Hydrographic offices and adapting satellite derived bathymetry methodologies to the stringent requirements of Safety of Navigation and IHO Cartographic standards. |
| Sentinel data for the detection of naturally occurring hydrogen emanations (sen4H2) | There is considerable interest in the use of Hydrogen as an alternative to hydrocarbon energy sources. However naturally occurring sources of hydrogen are not common and historically there has been significant controversy as to mechanisms [...] | TERRADUE SRL (IT) | Enterprise | energy and natural resources, permanently open call | There is considerable interest in the use of Hydrogen as an alternative to hydrocarbon energy sources. However naturally occurring sources of hydrogen are not common and historically there has been significant controversy as to mechanisms that may be related to the generation of hydrogen. It appears that natural emanations of hydrogen have been detected in several places (e.g. Russia, USA, Brazil and Mali) with several ongoing activities to drill and recover it. As with water and oil, hydrogen comes out of the ground in various places. Even if the origin of these emanations is not yet very well understood, possible geophysical and environmental changes associated with their formation and continuous emissions were observed. These empirical observations have associated elliptic terrain depressions and vegetation changes on areas where significant hydrogen leakages are detected. Several studies are currently being conducted by the IFP Energies nouvelles (IFPEN) in partnership with ENGIE to better constrain hydrogen generation and migration in the subsurface. This project will integrate EO derived information in support of these studies to determine the potential utility of EO based approaches for the detection of areas where hydrogen may be found. The team will integrate data from Sentinels 1, 2 and 3 with available in-situ data, prototype and potentially validate novel EO-based analysis linked with in-situ data to assess the feasibility of automatically detecting areas of possible hydrogen emissions and thus enabling the development of new EO-based services in this emerging market. |
| SENTINEL FOR WHEAT RUST DISEASE (SEN4RUST) | Ethiopia is the largest wheat producer in sub–Saharan Africa, but also a hot spot for wheat rust diseases. Based on wheat rust surveillance on the ground, the Ethiopian Wheat Rust Early Warning and Advisory System (EWAS) was established by a [...] | UNIVERSITY OF CATHOLIQUE DE LOUVAIN (BE) | Applications | africa, applications, permanently open call | Ethiopia is the largest wheat producer in sub–Saharan Africa, but also a hot spot for wheat rust diseases. Based on wheat rust surveillance on the ground, the Ethiopian Wheat Rust Early Warning and Advisory System (EWAS) was established by a consortium of national and international partners including Cambridge University, UK Met Office, and CIMMYT. This project will contribute to integrate information derived from satellite Earth Observation to enhance the advanced meteorologically driven spore dispersal and epidemiological models to forecast in-season disease risk. |
| Sentinel Hub for Network of Resources | Sentinel Hub services are operational services running on several platforms (AWS EU-Frankfurt, AWS US-West, Creodias, Onda and Mundi web services), providing seamless access to various satellite missions over web service API. They are used by [...] | SINERGISE LTD. (SI) | Digital Platform Services | permanently open call, platforms, science | Sentinel Hub services are operational services running on several platforms (AWS EU-Frankfurt, AWS US-West, Creodias, Onda and Mundi web services), providing seamless access to various satellite missions over web service API. They are used by thousands of users (free and payable) all over the world and two million requests are processed on average every single day. Two freely accessible web applications are operated within Sentinel Hub suite – Sentinel Playground, easy-to-use Google Maps-like web client and EO Browser providing a more advanced access to various data-sets supported by Sentinel Hub services. Various advanced features are available as well – export to GeoTiff, statistical analysis, time-lapse generation, custom scripting, etc. This project has performed an upgrade to Sentinel Hub services to make them ready for integration in Network of Resources, including: • User management (authentication and integration with EDUGAIN to make the access available to tens of thousands of Open Science Cloud users without additional registration) • Integration of Sentinel Hub services on the back-end level (to increase system performance, availability, and efficiently exploit separate deployments) • Security • Data fusion to make it possible to combine data from different missions in the same custom script, also adding further attributes (sun angle, quality, projections, etc..) • Upgrade of Python libraries and Web clients to support all above-mentioned new features |
| Sentinel-1 – INSAR Performance Study with TOPS Data | Scientific exploitation and validation of the interferometric TOPS mode implemented on the Sentinel-1 mission.Developement and implementation of advanced algorithms for Sentinel-1 TOPS data exploitation. Confirm and document Sentinel-1 [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | SAR | Scientific exploitation and validation of the interferometric TOPS mode implemented on the Sentinel-1 mission.Developement and implementation of advanced algorithms for Sentinel-1 TOPS data exploitation. Confirm and document Sentinel-1 interferometric performance. Assess the synergy between Sentinel-1 and previous C-band SAR missions. Adapt already successful DINSAR and PSI techniques to TOPS SAR data. Provide the scientific community with the first DINSAR and PSI results over selected pilot sites. |
| Sentinel-1 – INSAR Performance Study with TOPS Data (B) | Scientific exploitation and validation of the interferometric TOPS mode implemented on the Sentinel-1 mission.Developement and implementation of advanced algorithms for Sentinel-1 TOPS data exploitation. Confirm and document Sentinel-1 [...] | NORTHERN RESEARCH INSTITUTE (NORUT) (NO) | Science | SAR | Scientific exploitation and validation of the interferometric TOPS mode implemented on the Sentinel-1 mission.Developement and implementation of advanced algorithms for Sentinel-1 TOPS data exploitation. Confirm and document Sentinel-1 interferometric performance. Assess the synergy between Sentinel-1 and previous C-band SAR missions. Adapt already successful DINSAR and PSI techniques to TOPS SAR data. Provide the scientific community with the first DINSAR and PSI results over selected pilot sites. |
| SENTINEL-1 FOR OBSERVING FORESTS IN THE TROPICS (SOFT) | The world’s forests have undergone substantial changes in the last decades. Deforestation and forest degradation in particular, contribute greatly to these changes. In certain regions and countries, the changes have been more rapid, which is the [...] | GLOBEO (FR) | Applications | applications, forestry, permanently open call, Sentinel-1 | The world’s forests have undergone substantial changes in the last decades. Deforestation and forest degradation in particular, contribute greatly to these changes. In certain regions and countries, the changes have been more rapid, which is the case in the Greater Mekong sub-region recognized as deforestation hotspot. Effective tools are thus urgently needed to survey Illegal logging operations which cause widespread concern in the region. Several research and government organizations have developed systems that provide regular updates to the public, principally based on satellite data. However, most monitoring approaches rely predominantly on optical remote sensing. Nevertheless, a major limitation for optical-based near real time applications is the presence of haze in the dry season (caused by fire) and, more importantly, of clouds persistent in the tropics during the wet season. Cloud cover free SAR images have great potential in tropical areas, but have rarely been used for forest loss monitoring compared to optical imagery. Yet, the dense time series of the Sentinel-1 constellation offer a unique opportunity to systematically monitor forests at the global scale. In addition, it has been recently demonstrated that forest losses can be monitored using Sentinel-1 dense time series based on reliable indicators that bypass environmental effects on SAR signals. In this context, the primary science objective of the SOFT project is to provide near real time forest loss maps over Vietnam, Cambodia and Laos using Sentinel-1 data to the users of public sectors to support their efforts to control logging and log trade. SAR-based Algorithms of forest loss detection were first adapted and tested over eleven test sites in the frame of the proof-of-concept (PoC) development. The forest loss detection method from Bouvet et al. (2018) was considered as the best potential candidate algorithms for the reasons detailed in the Final Report. Regarding the Sentinel-1 data processing, we used the pre-processing chain developed at CESBIO and CNES as an operational tool for Sentinel-1 GRD data processing. The chain is based on open source libraries and can be used freely. We selected an adapted forest definitions, selected the test sites and reference data for the PoC, which covered various landscapes and terrain slopes. We also selected relevant ancillary data such as a forest mask, the quality of which has a big impact on the final forest loss detection results. Using these dataset, we deeply analyzed the Sentinel-1 backscatter signal over forest loss and intact forest areas of Vietnam, Cambodia and Laos, which was needed to adapt the forest loss detection method. The quality of maps resulting from the PoC was analysed and assessed qualitatively and quantitatively. The results of the PoC were extended to the whole Vietnam, Laos and Cambodia for the years 2018 to 2020. We optimized, installed and ran the scripts (in Python) onto the high performance computing (HPC) cluster of the CNES. Then, the processing of the whole study area has been achieved. We mosaicked the resulting maps, checked their quality and manually corrected outliers. This led to the final map which is the main outcome of the SOFT project. The map provides clear hints of the spatial and temporal distribution of forest losses. For example, the difference between high forest losses currently happening in Northern Laos versus low forest losses in Northern Vietnam is clearly seen, although the whole Northern mountainous region is covered by similar forest types. We also compared the forest loss surface areas obtained from our method with the results from GFW and GLAD. Although we do not consider the maps of GFW and GLAD as a benchmark and although the use of Sentinel-1 is basically much more relevant in term of timely detection of forest losses, we quantitatively compared the statistics per year and country and qualitatively compared both maps. The results from this study and from GFW are remarkably similar, the largest difference (23%) being found for Laos in 2019. This result highlights the fact that our detection system can be used as an alert system (fast detection from sentinel-1 data) and as an annual detection system similar to GFW, used for example to compute national statistics. The final map was thoroughly validated following the recommandations from Olofsson (2014 and 2020). We chose as sampling design a stratification with stratas defined by the map classes, mainly to improve the precision of the accuracy and area estimates. We specified a target standard error for overall accuracy of 0.01 and supposed that user’s accuracies of the change class is 0.70 for forest disturbances and 0.90 for intact forest. The resulting sample size was therefore n=803 in total, which we have rounded up to 1 000 samples. We then assessed the allocation of the sample to strata so that the sample size allocation results in precise estimates of accuracy and area. We followed Olofsson’s recommendations and allocated a sample size of 100 for the forest disturbance stratum, and then allocated the remainder of the samples to the intact forest classes, i.e. 200 in the buffer areas around detected disturbances, and 700 in intact forest outside of these buffers. We used when possible freely accessible very high spatial resolution imagery online through Google Earth™, which presents low cost interpretation options. When Google Earth images were not available at the relevant dates, we instead accessed Planet’s very high-resolution analysis-ready mosaics as reference data. We then calculated the resulting confusion matrix presented in terms of the sample counts and the confusion matrix populated by estimated proportions of area, used to report accuracy results. The estimated user’s accuracy ( 95% confidence interval) is 0.95 for forest disturbances and 0.99 for intact forest (including buffer areas around disturbance) and the estimated producer’s accuracy is 0.90 for forest disturbances and 0.99 for intact forest. Finally, a quality assessment was performed by comparing the final map to existing optical-based products. The estimated area of 2018 and 2019 deforestation according to the reference data was 23 437 +/- 2 140 km2. |
| Sentinel-1 for Science Ocean | The project aims to develop synergetic wind- wave- and radial surface current retrieval from S-1 SAR data (all modes) The objective of this study is to develop improved L2 ocean product prototypes for Sentinel-1 mission fulfilling the [...] | CLS COLLECTE LOCALISATION SATELLITES (FR) | Science | oceans, SAR | The project aims to develop synergetic wind- wave- and radial surface current retrieval from S-1 SAR data (all modes) The objective of this study is to develop improved L2 ocean product prototypes for Sentinel-1 mission fulfilling the requirements of the wide ocean user community. Those prototype products will aim at: Taking benefit of the new capabilities of the S-1 mission acquisition modes in order to improve the surface ocean sea state measurements (wind, waves, swell, currents), Implementing a synergetic ocean sea state measurement strategy in order to overcome the limitation of classical measurement approaches Providing ocean sea state measurements required by the user community (both operational community and scientific community) |
| Sentinel-1 for Surface Soil Moisture | Develop, implement and test soil moisture retrieval methods using Sentinel-1 dataThe C-band Sentinel-1 (S-1) European Radar Observatory, with its two satellites (S-1A & B), is the only operating SAR mission with monitoring capabilities, [...] | CNR – INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT (IREA) (IT) | Science | science, water cycle and hydrology | Develop, implement and test soil moisture retrieval methods using Sentinel-1 dataThe C-band Sentinel-1 (S-1) European Radar Observatory, with its two satellites (S-1A & B), is the only operating SAR mission with monitoring capabilities, frequent revisit and large geographical coverage that will guarantee data continuity over the next decades. S-1 with its advanced observational capabilities opens new perspectives to SAR derived near surface soil moisture (SSM) products as, for the first time ever, they may attract a real interest in a wide user community and stimulate a synergistic interaction with SSM products at low resolution.The scope of the two-year Exploit-S-1 project is to demonstrate the capabilities of the S-1 mission to support systematic SSM product generation at high resolution (e.g. 500m-1000m) and at regional/continental scale.A suite of SSM retrieval methods will be developed, implemented and validated using S-1 data. The methods will be based on previous research into C-band soil moisture retrieval and will be selected from the great wealth of approaches proposed in the literature and tailored to S-1 data. The emphasis will be on implementing and comparing algorithms presenting the most promising trade-off among robustness, retrieval accuracy and potential matching with the requirements of different applications (e.g. Numerical Weather Prediction, hydrological forecasting, drought events …) in terms of accuracy, resolution and product frequency. In addition, the suitability of the algorithms to fully exploit the S-1 observational assets (e.g., dual polarization, spatial/temporal resolution, radiometric accuracy) in order to deliver a large scale mapping will be considered.A key component of Exploit-S-1 will be the validation activity that will include local and regional scale sites (e.g. the Mediterranean basin) in order to better assess the potential for pre-operational and operational soil moisture products and services.A further pivotal element of Exploit-S-1 will be the assessment of the optimal pre-processing of S-1 time series for SSM retrieval. This will also have the outreaching effect of consolidating standards for the generation of S-1 multi-temporal products that are well suited for other S-1 retrieval studies. |
| Sentinel-1 Interferometric Coherence for Vegetation and Mapping (SINCOHMAP) | SINCOHMAP is an ESA SEOM project with the objective of developing, analysing and validating novel methodologies for land cover & vegetation mapping using Sentinel-1 Interferometric Coherence Evolution. One of the main objectives of the [...] | DARES TECHNOLOGY (ES) | Science | ecosystems/vegetation, land cover, SAR | SINCOHMAP is an ESA SEOM project with the objective of developing, analysing and validating novel methodologies for land cover & vegetation mapping using Sentinel-1 Interferometric Coherence Evolution. One of the main objectives of the project is to quantify the impact in using S-1 InSAR (Interferometric Synthetic Aperture Radar) data relative to traditional land cover and vegetation mapping using optical data (especially Sentinel-2, hereafter named S-2) or SAR-based (Synthetic Aperture Radar) approaches. In consequence, the project is designed to clearly state this point. |
| Sentinel-2 Atmospheric Correction | This project aims to develop and validate an atmospheric corrections scheme to produce high quality surface reflectance from Sentinel-2 data for coastal waters. The objective of this study is to develop, test, implement and validate methods (or [...] | ACRI-HE SAS (FR) | Science | atmosphere, coastal zone | This project aims to develop and validate an atmospheric corrections scheme to produce high quality surface reflectance from Sentinel-2 data for coastal waters. The objective of this study is to develop, test, implement and validate methods (or combination of methods) for deriving atmospheric correction above coastal waters and over inland waters, to validate them according to the today’s best practices on a number of different sites offering variety of marine optical properties to provide their uncertainties. The proposed solution is, a priori, based on three sequential steps or modules. The first step is the cloud and cloud shadow detection and filtering – this will result in the flagging of contaminated pixels (contaminated either directly, as being hidden by the clouds or covered by their shadows, or indirectly as nearby the clouds and impacted by adjacency effects and multiple scattering). The second step consists in removing the glinted pixels over the water, this is done mainly by analyzing the SWIR band and, again, removing contaminated pixel from the analysis (this step however, depends on the Atmospheric Correction scheme that will finally selected). Lastly, the third step is the atmospheric correction for Sentinel-2 above coastal and inland waters. |
| Sentinel-2 for Agriculture (DUE) | The Sen2-Agri project is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring at national scale. The project will demonstrate the benefit of the [...] | UNIVERSITY OF CATHOLIQUE DE LOUVAIN (BE) | Applications | agriculture, applications | The Sen2-Agri project is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring at national scale. The project will demonstrate the benefit of the Sentinel-2 mission for the agriculture domain across a range of crops and agricultural practices. The project objectives are to provide validated algorithms, open source code and best practices to process Sentinel-2 data in an operational manner for major worldwide representative agriculture systems distributed all over the world. Sen2-Agri is a contribution to the GEOGLAM initiative and has been demonstrated with international and national users in 12 countries and is currently available as open source system on the project website http://www.esa-sen2agri.org/ |
| Sentinel-2 Global Land Cover | This activity aims at setting up a solid scientific basis for the development of advance land cover classification strategies to exploit the new capabilities of Sentinel-2 in view of generating future global land cover mapThis project will focus [...] | Space Research Centre, Polish Academy of Sciences (CBK-PAN) (PL) | Science | land cover, science | This activity aims at setting up a solid scientific basis for the development of advance land cover classification strategies to exploit the new capabilities of Sentinel-2 in view of generating future global land cover mapThis project will focus on the classification of Sentinel imagery for the purpose of producing a global land cover map. The first part of this study is an extensive review of the currently available Global Land Cover (GLC) maps and databases. This review, together with feedback from the community, will influence the choices in algorithms and image processing methodologies tested within the scope of this study. The second and third parts of the study are testing of the land-cover classification methodologies and validation of those methods respectively in order to produce not only the highest quality maps, e.g. accuracy >80%, but also harmonised with current GLC products. In order to achieve this complex goal, many different tests of object-oriented as well as pixel based classification approaches will be made. In parallel, advanced data collection strategies for training and validation will be investigated. While the majority of the applied land-cover classification techniques will be based on optical imagery acquired by Sentinel-2 (S2), the team understands that globally this challenge can be supported by the Sentinel-1 SAR data. The different approaches will be benchmarked in order to understand the influence of a variety of factors on the performance of the proposed methods. Factors will include feature relevancy, the impact of atmospheric correction, the selected minimal mapping unit, seasonal changes, the incompleteness of training data, image mosaicking, and multi-temporal S2 data. The final part of the project will be to make recommendations based on the research for future S2 based GLC products. |
| Sentinel-2 Radiometry Validation | Development and inter-comparison of algorithms for validating the radiometry of Sentinel-2 Level-1 products.According to the definition used by the Working Group on Calibration and Validation (WGCV) of the international Committee on Earth [...] | ACRI-ST S.A.S. (FR) | Science | science | Development and inter-comparison of algorithms for validating the radiometry of Sentinel-2 Level-1 products.According to the definition used by the Working Group on Calibration and Validation (WGCV) of the international Committee on Earth Observation Satellites (CEOS), validation is the process of assessing, by independent means, the quality of the data products derived from the system outputs. This two-year project pursues two main objectives:The development of four algorithms to validate the radiometry of Sentinel-2 products.The inter-comparison of the results obtained with these methods and the ones from other entities. |
| Sentinel-3 for Science, Land Study 1: Snow | This SEOM study is to develop, implement and validate algorithms for deriving several key snow parameters from Sentinel 3 optical satellite data, appropriate for addressing ESA’s Cryosphere challenge (Seasonal snow, lake/river ice and land ice, [...] | GEOLOGICAL SURVEY OF DENMARK AND GREENLAND (DK) | Science | cryosphere, polar science cluster, science, Sentinel-3 | This SEOM study is to develop, implement and validate algorithms for deriving several key snow parameters from Sentinel 3 optical satellite data, appropriate for addressing ESA’s Cryosphere challenge (Seasonal snow, lake/river ice and land ice, their effect on the climate system, water resources, energy and carbon cycles: the representation of terrestrial cryosphere in land surface, atmosphere and climate models). This study takes a step toward achieving GCOS snow observation goals, effectively linking snow cover and albedo essential climate variables (ECVs) while developing capacity to extend snow climate data records (CDRs). This work aims to assimilate satellite optical data in a snow model by pushing data assimilation capabilities to the near real time frame and thus serving operational models to improve hydrological and weather forecasting skill and e.g. flood and avalanche hazard management. |
| Sentinel-3 Hydrologic Altimetry Processor prototypE (SHAPE) | The SHAPE project is funded by ESA through the Scientific Exploitation of Operational Missions (SEOM) programme element to prepare the exploitation of Sentinel-3 data over the inland water domain (water heights and discharge). Objectives are to: [...] | ALONG-TRACK (FR) | Science | altimeter, water cycle and hydrology | The SHAPE project is funded by ESA through the Scientific Exploitation of Operational Missions (SEOM) programme element to prepare the exploitation of Sentinel-3 data over the inland water domain (water heights and discharge). Objectives are to: 1) Design and assess the impact of alternative and innovative techniques not implemented in the Sentinel-3 ground segment (no Inland Water dedicated processing); 2) Transpose results obtained by using Cryosat-2 data processed according to the Sentinel-3 baseline to the Sentinel-3 framework (repeat versus geodesic orbit); 3) Migrate results into an hydrological model evaluating the potential of the Sentinel-3 data to improve hydrological catchment; 4) Produce new datasets, including updated tropospheric corrections. |
| Sentinel-3 Performance Improvement for ICE Sheets (SPICE) | SPICE (Sentinel-3 Performance improvement for ICE sheets) is a 2-year study, which began in September 2015 and has been funded by ESA’s SEOM (Scientific Exploitation of Operational Missions) program. The project aims to contribute to the [...] | UNIVERSITY OF LEEDS, SCHOOL OF EARTH AND ENVIRONMENT (GB) | Science | altimeter, CryoSat, cryosphere, polar science cluster, Sentinel-3 | SPICE (Sentinel-3 Performance improvement for ICE sheets) is a 2-year study, which began in September 2015 and has been funded by ESA’s SEOM (Scientific Exploitation of Operational Missions) program. The project aims to contribute to the development and evaluation of novel SAR altimetry processing methodologies over ice sheets, primarily using dedicated CryoSat-2 SAR acquisitions made at several sites in Antarctica and in Greenland. SPICE developed novel algorithms to address four high level objectives: 1) Assess and improve Delay-Doppler altimeter processing for ice sheets; 2) Assess and develop SAR waveform retrackers for ice sheets; 3) Evaluate the performance of SAR altimetry relative to conventional pulse limited altimetry; 4) Assess the impact on SAR altimeter measurements of radar wave interaction with the snowpack. |
| Sentinel-3 Primary Production over Land (TerrA-P) | Gross primary production (GPP) and terrestrial net primary production (NPP) are fundamental quantities in the global carbon cycle, and for the production of food, fibre and biomass for human use. This project aims at exploiting Sentinel-3 data [...] | VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK VITO (BE) | Science | biosphere, carbon cycle, carbon science cluster, land, science, Sentinel-3 | Gross primary production (GPP) and terrestrial net primary production (NPP) are fundamental quantities in the global carbon cycle, and for the production of food, fibre and biomass for human use. This project aims at exploiting Sentinel-3 data to develop and validate a productive model, consistent across different regions and ecosystems.The objective of the TerrA-P project is to define, implement and validate a model to derive information on the vegetation productivity based on data from MERIS and Sentinel-3. To reach this goal, knowledge and expertise from three domains need to be combined. These domains are: the ecophysiology of the plants which is expressed in the productivity model, the EO data sets that can be used as input for this model, and the in-situ data that allow the validation of the model outcome using EO-input data. |
| SENTINEL-3 TANDEM FOR CLIMATE (S3TC) | After 2 years in orbit, the Sentinel-3A satellite from the Copernicus program was joined by Sentinel-3B. During the first six months of the mission, the two satellites will fly in close formation. Sentinel-3A and Sentinel-3B observe the same [...] | ACRI-ST S.A.S. (FR) | Science | climate, ocean science cluster, science, Sentinel-3 | After 2 years in orbit, the Sentinel-3A satellite from the Copernicus program was joined by Sentinel-3B. During the first six months of the mission, the two satellites will fly in close formation. Sentinel-3A and Sentinel-3B observe the same place on the Earth within 30 seconds. This so-called tandem phase makes it possible to inter-calibrate very accurately the two satellites in order to ensure that their measurements are consistent. In the long run, this will help to build reliable measurement records to study climate change effects such as sea level rise, increase of ocean surface temperature, or variations in the phyto-plankton distribution. The Sentinel-3 Tandem for Climate is an ESA-financed study which aims at a detailed understanding of the inter-satellite discrepancies, differences and uncertainties using data acquired during the Tandem phase. The study is performed by a consortium of companies and research institutes led by ACRI-ST. |
| SENTINEL-5P+ INNOVATION | The Sentinel-5p+ Innovation activity is motivated by potential novel scientific developments and applications that may emerge from the exploitation of the Copernicus Sentinel-5p mission data. This satellite mission is dedicated to the precise [...] | ESA EOP-SDS initiative (IT) | Science | applications, atmosphere, atmosphere science cluster, science, Sentinel-5P | The Sentinel-5p+ Innovation activity is motivated by potential novel scientific developments and applications that may emerge from the exploitation of the Copernicus Sentinel-5p mission data. This satellite mission is dedicated to the precise monitoring of the Earth’s atmosphere with a highlight on tropospheric composition. The Sentinel-5p spacecraft was launched in October 2017, where fills the gap from the past SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on ESA’s Envisat satellite, via the yet active Ozone Monitoring Instrument (OMI) carried on NASA’s Aura mission to the future Sentinel-5 The overarching objectives of this Sentinel-5p+ Innovation project are: To develop a solid scientific basis for the application of Sentinel-5p data within the context of novel scientific and operational applications; To develop a number of novel products and retrieval methods that exploit the potential of the Sentinel-5p mission’s capabilities beyond its primary objectives; To define strategic actions for fostering a transition of the target methods and models developed in this project from research to operational activities; To maximise the scientific return and benefits from the Sentinel-5p mission. The Sentinel-5p+ Innovation project addresses seven themes related to atmospheric composition and ocean colour: Theme 1: Glyoxal (CHOCHO) Theme 2: Chlorine Dioxide (OClO) Theme 3: Water Vapour Isotopologues (H2O-ISO) Theme 4: Sulphur dioxide layer height (SO2-LH) Theme 5: Aerosol Optical Depth (AOD) and Bidirectional Reflectance Distribution Function (BRDF) Theme 6: Solar Induced Chlorophyll Fluorescence (SIF) Theme 7: Ocean colour (OC) The individual project themes have been kicked-off end June/beginning of July 2019 and will run for 24 months. |
| SENTINEL-5P+ INNOVATION – GLYRETRO (GLYoxal Retrievals from TROPOMI) | Glyoxal is the most abundant dicarbonyl present in our atmosphere and is directly emitted from biomass burning and also results from the oxidation of precursor non-methane volatile organic compounds (NMVOC). It is currently estimated that about [...] | BELGIAN INSTITUTE OF SPACE AERONOMY (BIRA-IASB) (BE) | Science | applications, atmosphere, atmosphere science cluster, science, Sentinel-5P, Sentinel-5P+ Innovation, TROPOMI | Glyoxal is the most abundant dicarbonyl present in our atmosphere and is directly emitted from biomass burning and also results from the oxidation of precursor non-methane volatile organic compounds (NMVOC). It is currently estimated that about 70% of its production originate from natural sources and fires, while the remaining 30% come from human activities. With a short lifetime (~3 hours), elevated glyoxal concentrations are observed near emission sources. Measurements of atmospheric glyoxal concentrations therefore provide quantitative information on VOC emission and can help to better assess the quality of current inventories. In addition, glyoxal is also known to contribute significantly to the total budget of secondary organic aerosols, which impact both air quality and climate forcing. The GLYRETRO (GLYoxal Retrievals from TROPOMI) activity is one of the seven themes from the ESA S5p innovation (S5p+I) project, which aims at further exploiting the capability of the S5p/TROPOMI instrument with the development of a number of new scientific products. The GLYRETRO project, proposed by both the Royal Belgian Institute for Space Aeronomy and the Institute of Environmental Physics at the University of Bremen, has been successfully kicked-off on July, 1st 2019 and will last two years. The objectives are manifold and can be listed as To develop a scientific glyoxal (CHOCHO) tropospheric column product To collect independent data sets in order to validate the satellite observations To pave the way towards an operationalization of the developed S5p glyoxal product To demonstrate the added-value of the S5p glyoxal product for the user community. For more information on the project, contact Christophe Lerot (christophe.lerot at aeronomie.be). |
| SENTINEL-5P+ INNOVATION – SO2 Layer Height Project | The ESA Sentinel-5p+ Innovation project (S5p+I) has been initiated to develop novel scientific and operational applications, products and retrieval methods that exploit the potential of the Sentinel-5p mission’s capabilities beyond its primary [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Science | applications, atmosphere, atmosphere science cluster, science, Sentinel-5P, Sentinel-5P+ Innovation, TROPOMI | The ESA Sentinel-5p+ Innovation project (S5p+I) has been initiated to develop novel scientific and operational applications, products and retrieval methods that exploit the potential of the Sentinel-5p mission’s capabilities beyond its primary objective. Accurate determination of the location, height and loading of SO2 plumes emitted by volcanic eruptions is essential for aviation safety. The SO2 layer height is furthermore one of the most critical parameters that determine the impact on the climate. The height of volcanic ash columns are often estimated by local observers with mostly unknown accuracy. The plume height can also be determined using aircraft, ground-based radar or LIDAR but such observations are often not available and many volcanic eruptions in remote areas remain not observed. In addition, volcanic plumes containing SO2 but not ash cannot be seen directly. SO2 in the atmosphere has important impacts on chemistry and climate at both local and global levels. Natural sources account for ~30% of SO2 emissions. Next to contributions from volcanic activity, these include emissions from marine phytoplankton and a small contribution from soil and vegetation decay. However, by far the largest contributions in global SO2 production are from anthropogenic sources. These account for the remaining 70% of global emissions and primarily relate to fossil fuel burning, with smaller contributions from smelting and biomass burning. While satellite instruments, in principle, provide global products e.g. from SEVIRI (Second Generation Spin-stabilised Enhanced Visible and Infra-Red Imager) or AIRS (Atmospheric Infra-Red Sounder), they have no or little vertical resolution. SO2 height retrievals have been developed for IR sensors like the scanning IASI (Infrared Atmospheric Sounding Interferometer). This can provide information on the vertical distribution of SO2 in a volcanic plume but only at a horizontal resolution of 12 km. Although retrievals of SO2 plume height have been carried out using satellite UV backscatter measurements from e.g. OMI (Ozone Monitoring Instrument) or GOME-2, until now such algorithms are up to now very time-consuming, since the spectral information content and its characterization require computationally demanding radiative transfer modelling. Due to the high spatial resolution of TROPOMI (Tropospheric Ozone Measurement Instrument) aboard S5p(Sentinel-5p) and consequent large amount of data, an SO2 layer height algorithm has to be very fast. The SO2 Layer Height (SO2LH) theme is dedicated to the generation of an SO2 layer height product for Sentinel-5p taking into account data production timeliness requirements. The S5p+I: SO2LH project is funded by the European Space Agency ESA The coordination of the project is under the responsibility of the German Aerospace Center DLR. The objectives of the SO2 LH project are: • Development of an SO2 layer height product for Sentinel-5p; • Assessment of the performance of the new algorithm specifically with respect to timeliness requirements in operational processing frameworks; • Assessment of the applicability of various algorithms based on e.g. EISF or a LUT approach; • Assessment of the errors in the presence of absorbing and non-absorbing aerosols; • Assessment of retrieval results based on observation conditions, e.g. inhomogeneous scene; • Demonstration of the new retrieval on a number of cases of volcanic eruptions, including intercomparisons to SO2 height levels for volcanic eruptions with available OMI and GOME2 SO2 height level retrievals; • Discussion on how the effect of layer altitude change can be distinguished from a change of vertical column; • Assessment of the contribution of the new LH algorithm to the independent operational SO2 column retrieval • Discussion of mechanisms of adding the LH product to the SO2 operational column product (e.g. inclusion into the existing SO2 total column product), or justification for a standalone product. The S5P+I: SO2LH project had its official kick-off on 3 July 2019 The project duration is 24 month |
| SENTINEL-5P+ INNOVATION – THEME 5, AEROSOL OPTICAL DEPTH (AOD) + BRDF | The capability of Sentinel-5p for aerosol monitoring is currently not used to its full potential. However, satellite observations in the spectral range from approximately 340 to 400 nm are known to have unique sensitivity to elevation and [...] | GRASP-SAS (FR) | Science | atmosphere, atmosphere science cluster, science, Sentinel-5P, Sentinel-5P+ Innovation, TROPOMI | The capability of Sentinel-5p for aerosol monitoring is currently not used to its full potential. However, satellite observations in the spectral range from approximately 340 to 400 nm are known to have unique sensitivity to elevation and absorption of tropospheric aerosols. Traditionally, this sensitivity is used in many ozone monitoring instruments such as TOMS, GOME-1, SCIAMACHY, OMI and GOME-2 for deriving UV Aerosol Index (UVAI) that provides very valuable qualitative information about aerosol distribution. However, UVAI does not have explicit geophysical quantitative meaning and, therefore, it is not fully appropriate for utilization in validation of aerosol transport models and other climate applications. The reflectivity of the Earth’s surface is an important input parameter for many satellite retrievals of atmospheric composition. Examples are the retrieval of trace gases such as ozone, NO2, BrO, CH2O, H2O, CO2, CO, and CH4, and of cloud information and aerosol optical depth (AOD). Recent developments in atmospheric remote sensing have focused strongly on deriving and implementing angular-dependent surface BRDF information (as opposed to using traditional, non-directional Lambertian surface reflectivity information), and on obtaining this information on a much higher spatial resolution than before. ESA S5P+I AOD/BRDF project is focused on aerosol and surface reflectance characterisation using capabilities of Sentinel-5p (TROPOMI) measurements. One objective of the project is to achieve quantitative characterization of aerosol properties from Sentinel-5p. Specifically, the objective is to develop the algorithm capable to provide Aerosol Optical Depth (AOD), i.e. aerosol load in the atmosphere as well as to provide information about absorption and type of the aerosol. Another objective of the RFP/ITT is the development of a product of spectral surface BRDF information from (and for) the TROPOMI instrument. |
| SENTINEL-5P+ INNOVATION – WATER VAPOUR ISOTOPOLOGUES (H2O-ISO) | Atmospheric moisture is a key factor for the redistribution of heat in the atmosphere and there is strong coupling between atmospheric circulation and moisture pathways which is responsible for most climate feedback mechanisms. Water [...] | UNIVERSITY OF LEICESTER (GB) | Science | applications, atmosphere, atmosphere science cluster, science, Sentinel-5P, Sentinel-5P+ Innovation | Atmospheric moisture is a key factor for the redistribution of heat in the atmosphere and there is strong coupling between atmospheric circulation and moisture pathways which is responsible for most climate feedback mechanisms. Water isotopologues can make a unique contribution for better understanding this coupling. In recent years, water vapour isotopologue observations from satellites have become available from thermal nadir infrared measurements (TES, AIRS, IASI) which are sensitive above the boundary layer and from shortwave-infrared (SWIR) sensors (GOSAT, SCIAMACHY) that provide column averaged concentrations including sensitivity to the boundary layer. Sentinel 5P (S5P) measures SWIR radiance spectra that allow retrieval of water isotopologue columns but with much improved spatial and temporal coverage compared to other SWIR sensors thus promising an unique dataset with larger potential for scientific and operational applications. The aim of this proposal is to develop and evaluate a prototype dataset from Sentinel 5P for water isotopologues. This will be addressed by a team of experts from University of Leicester, Karlsruhe Institute of Technology and University of Bergen bringing together expertise in atmospheric measurement (EO and in-situ), and modelling with scientific end-users. Objectives: During this project we will demonstrate the feasibility of measuring stable water isotopologues for S5P, specifically ratios of HDO/H2O by: Optimizing the retrieval method making use of the University of Leicester Full Physics (UoL-FP) retrieval algorithm. Examining and characterize the retrieval performance by validation of retrieved waterisotopologues against reference data sets (MUSICA NDACC data and TCCON) and satellite data from IASI and GOSAT. Assess the impact of the S5P datasets using two different models for defined regions of interest. The findings and recommendations of this project will be delivered through a scientific roadmap, in order to further develop the methods and their application including a transition to operational activities. This will benefit from the strong links of the team with relevant international activities, projects and initiatives. |
| SENTINEL-5P+ INNOVATION CHLORINE DIOXIDE (OCLO) | The S5PI+ OClO project is one of the seven themes of ESA's Sentinel-5p+ Innovation activity, which aims at developing products for the TROPOMI instrument on the Sentinel-5 Precursor satellite which are not yet part of the operational processor. [...] | UNIVERSITY OF BREMEN (DE) | Science | atmosphere, atmosphere science cluster, science, Sentinel-5P, Sentinel-5P+ Innovation, TROPOMI | The S5PI+ OClO project is one of the seven themes of ESA’s Sentinel-5p+ Innovation activity, which aims at developing products for the TROPOMI instrument on the Sentinel-5 Precursor satellite which are not yet part of the operational processor. The Copernicus Sentinel-5P satellite was launched in October 2017 and provides operational data since July 2018. This mission is intended as a gap-filler between the time series of the former instruments GOME and SCIAMACHY, the still operating OMI and the future Copernicus S5 instruments. The stratospheric ozone layer plays an important role for life on Earth as it absorbs a large part of the harmful UV radiation coming from the sun. The amount and vertical distribution of ozone in the stratosphere is determined by transport and by an equilibrium between chemical ozone production on the one hand and catalytic ozone destruction cycles on the other hand. Anthropogenic emissions of long-lived halogen containing substances such as CFCs and halons have disturbed this equilibrium as additional reactive halogens have been released in the stratosphere. This lead to global reductions in ozone columns and the annual appearance of the ozone hole over Antarcica in austral winter / spring. Strong ozone depleteion is also observed in Arctic winter / spring but only in years where the stratosphere is cold enough to facilitate formation of Polar Stratospheric Clouds (PSCs). As a reaction on the rapid loss of stratospheric ozone, the Montreal Protocol was signed in 1987, phasing out the emissions of many long-lived halogen containing substances. Several amendments to this protocol have in the last decades lead to further and more rapid decreases in emissions of of ozone depleting substances, and stratospheric halogen levels are already decreasing. Because of the long lifetimes of the emitted substances, it is expected that return to the ozone levels of the 1980s will take at least until 2050. Stratospheric chlorine activation can be monitored directly by measuring ClO with microwave radiometry. In the UV/visible spectral range, the OClO molecule can be retrieved as it has a structured absorption spectrum. As the only known formation of OClO is by reaction of ClO and BrO, the amounts of OClO are proportional to the concentrations of these two species. With BrO concentrations being much less variable than those of ClO, OClO can be used as a quantitative measure of chlorine activation at least at solar zenith angles around twilight. Retrievals of OClO have been performed for all UV/vis heritage instruments (GOME, SCIAMACHY, GOME2, OMI) and the S5P OClO product will act as a continuation of these timeseries. Atmospheric profiles of OClO have also been retrieved from SCIAMACHY, OSIRIS and GOMOS measurements, providing additional information on the vertical distribution of OClO. For the validation of the S5P OClO product, ground-based observations of OClO from instruments in the NDACC network can be used. |
| SENTINEL-5P+ INNOVATION OCEAN COLOUR (S5P+-I-OC) | The S5P+I-OC project will explore the capacity of the Sentinel-5p TROPOMI data to provide novel Ocean Colour (OC) products. More specifically, the objectives of this S5P+ Innovation activity are to: develop a solid scientific basis for the [...] | ALFRED WEGENER INSTITUTE (DE) | Science | atmosphere science cluster, carbon cycle, carbon science cluster, ocean science cluster, oceans, science, Sentinel-3, Sentinel-5P, Sentinel-5P+ Innovation, TROPOMI | The S5P+I-OC project will explore the capacity of the Sentinel-5p TROPOMI data to provide novel Ocean Colour (OC) products. More specifically, the objectives of this S5P+ Innovation activity are to: develop a solid scientific basis for the application of S5P data within the context of novel scientific and operational OC products applications; assess existing algorithms which have been used for OC product retrievals from SCanning Imaging Absorption Spectro-Meter for Atmospheric CHartographY (SCIAMACHY), Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME-2); develop novel OC products and retrieval methods that exploit the potential of the S5P mission’s capabilities beyond its primary objectives, in particular, the chlorophyll-a concentration (CHL) of important phytoplankton groups (PFT-CHL), the underwater light attenuation coefficients (Kd) for the ultraviolet (UV) and the blue spectral region separately (KdUV, KdBlue), and the sun-induced marine chlorophyll-a fluorescence signal (SIF-marine) from TROPOMI S5P level-1 data; explore the potential of the UV range of S5P for ocean biology; use complementary products from Sentinel-3 (S3) and S5P for exploring the UV measurements of TROPOMI for assessing sources of coloured dissolved organic matter (CDOM) and the amount of UV-absorbing pigments in the ocean; validate with established reference in situ datasets and perform intercomparison to other satellite OC data; define strategic actions for fostering a transition of the methods from research to operational activities; maximize the scientific return and benefits from the S5P mission for surface ocean research and services (e.g. CMEMS) by assessing the synergies with other satellite sensors, in particular explore the synergistic use of S5P and S3. |
| SENTINEL-5P+ INNOVATION SOLAR INDUCED CHLOROPHYLL FLUORESCENCE (SIF) | The ESA –TROPOSIF project is one of the seven themes from the Sentinel-5p+ Innovation (S5p+I) activity funded by ESA, which aims at developing novel scientific products / retrieval methods from the data acquired by the TROPOMI (TROPOspheric [...] | NOVELTIS SAS (FR) | Science | atmosphere science cluster, biosphere, carbon cycle, carbon science cluster, land, science, Sentinel-5P, Sentinel-5P+ Innovation, TROPOMI | The ESA –TROPOSIF project is one of the seven themes from the Sentinel-5p+ Innovation (S5p+I) activity funded by ESA, which aims at developing novel scientific products / retrieval methods from the data acquired by the TROPOMI (TROPOspheric Monitoring Instrument) instrument aboard the Copernicus Sentinel-5 Precursor mission launched in October 2017. Although the Sentinel-5P mission was designed to monitor the Earth’s atmosphere, TROPOMI’s spectral and radiometric performance enable to also monitor terrestrial Solar Induced Fluorescence (SIF) with an unprecedented spatial and temporal resolution. What is SIF? Solar induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by the chlorophyll a of assimilating plants: part of the energy absorbed by chlorophyll a is not used for photosynthesis, but emitted at longer wavelengths as a two-peak spectrum roughly covering the 650–850 nm spectral range. The SIF signal responds instantaneously to perturbations in environmental conditions such as light and water stress, which makes it a direct proxy for photosynthetic activity. However, SIF emission constitutes only a small fraction (typically 0.5%-2%) of the radiance at the top of the canopy, which is mostly composed of reflected sunlight, and its estimation from space-borne spectrometers requires both high spectral resolution and advanced retrieval schemes. Why should we care about SIF? Over the last few years, solar-induced chlorophyll fluorescence (SIF) observations from space have emerged as a promising resource for evaluating the spatio-temporal distribution of gross carbon uptake (GPP = gross primary productivitt) by terrestrial ecosystems, the characterization of which still remains uncertain to date. In the particular case of climate studies, our ability to anticipate the evolution of net and gross carbon fluxes over the globe under a changing climate largely relies on global terrestrial biosphere models (TBMs). Their parameterization remains largely uncertain and it is anticipated that satellite SIF products will provide a significant constraint (reduction in uncertainty) on the projections of the terrestrial carbon updake. |
| SentinelNamib | Living Planet Fellowship research project carried out by Cassandra Normandin. In the context of the ESA BIOMASS Earth Explorer mission, the Namib Desert was selected as a test site to assess the performance of P-band SAR for subsurface [...] | UNIVERSITE DE BORDEAUX (FR) | Science | living planet fellowship, science, Sentinel-1, Sentinel-2, Sentinel-3, water cycle and hydrology | Living Planet Fellowship research project carried out by Cassandra Normandin. In the context of the ESA BIOMASS Earth Explorer mission, the Namib Desert was selected as a test site to assess the performance of P-band SAR for subsurface imaging in arid environments. In cooperation with the Gobabeb Research and Training Centre, a study of the paleo-hydrology of the Kuiseb River was started, combining field work measurements (soil properties, ground penetrating radar, scatterometry, drone imaging, GNSS reflectometry) and airborne radar sensors (L- and P-band polarimetric and interferometric SAR). The Kuiseb River is one of the major ephemeral rivers of western Namibia, marking the northern limit of the Namib Sand Sea and outflowing in the Atlantic Ocean. This research project aims to develop novel methods for the monitoring of ephemeral rivers in arid environments, based of the combined use of Sentinel 1, 2 and 3 sensors. We shall process and analyse time series acquired by the Sentinel missions from 2016 to 2020, in order to study the dynamics of the Kuiseb River over years. SAR data provided by Sentinel 1 will be used to produce interferograms, to track changes in soil moisture due to the aquifer level dynamics. Multispectral data provided by Sentinel 2 will allow to map the river floods and the vegetation change related to the aquifer changes. Finally, we shall monitor the variations of the river bed surface and subsurface properties thanks to the altimeter data provided by Sentinel 3. We expect to demonstrate that the combined use of datasets provided by the Sentinel missions allows to monitor the dynamics of ephemeral rivers in arid regions. Sentinel data, combined to the subsurface imaging capabilities of L- band (ALOS-2) and P-band (BIOMASS) SAR and to field work investigations, will then allow to better understand the ephemeral rivers related processes at the surface – subsurface interface. Such studies are of highest importance for countries in arid regions, since they are both relevant to recent past climatic conditions and to potential fossil water resources. |
| SENTINELS FOR LAND DEGRADATION NEUTRALITY (SEN4LDN) | To address the need for higher spatial resolution datasets to monitor Land Degradation Neutrality (LDN). The SEN4LDN consortium aims to develop, demonstrate and validate robust and automated EO methods to map land cover changes and land [...] | VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK VITO (BE) | Applications | land, Sentinel-1, Sentinel-2 | To address the need for higher spatial resolution datasets to monitor Land Degradation Neutrality (LDN). The SEN4LDN consortium aims to develop, demonstrate and validate robust and automated EO methods to map land cover changes and land productivity dynamics that exploit the high frequency and spatial resolution of Sentinel-1 and 2. Land degradation affects the livelihoods of millions of people worldwide. Diminished overall productivity and reduced resilience in the face of climate and environmental change, have made addressing land degradation a global priority formalized by the United Nations Convention to Combat Desertification (UNCCD) and the Sustainable Development Goals (SDGs), in particular Target SDG 15.3 on Land Degradation Neutrality (LDN). The SDG indicator 15.3.1 is the key measurement to monitor country progresses on SDG target 15.3, and is expressed as the spatial extent of degraded land. Current monitoring focuses primarily on the use of 3 sub-indicators (land cover changes; trends in land productivity/functioning; and trends in carbon stocks above and below ground) using global datasets at a resolution between 250 m and 8 km. However, these datasets are often considered too coarse in many areas in order to accurately assess the complexities of degradation processes. SEN4LDN targets to increase the spatial details of national assessments of land degradation and restoration, and provide synoptic information for countries to plan LDN interventions at appropriate scale. Within VITO Remote Sensing, we will mainly focus on the development of robust mapping of land cover changes and the integration of the different sub-indicators into an open source and operational workflow to monitor SDG indicator 15.3.1 at high resolution.ESA’s SEN4LDN project will run over a course of 2 years until October 2024. |
| SEOM Sen2Coral | Sen2Coral aims to develop and validate new algorithms relevant for coral reef monitoring based on Sentinel-2 observations, including benthic mapping, coral reef health and mortality as well as bathymetry. The activity will develop open source [...] | ARGANS LIMITED (GB) | Science | biodiversity flagship, ecosystems/vegetation, science, water resources | Sen2Coral aims to develop and validate new algorithms relevant for coral reef monitoring based on Sentinel-2 observations, including benthic mapping, coral reef health and mortality as well as bathymetry. The activity will develop open source algorithms for mapping (habitat, bathymetry, and water quality) and detection change for coral reef health assessment and monitoring as well as a roadmap to a global coral reef observatory based on the scientific exploitation and validation of the Sentinel-2 Multispectral Instrument (MSI). |
| SHRED: Sentinel-1 for High REsolution monitoring of vegetation Dynamics | Living Planet Fellowship research project carried out by Mariette Vreugdenhil. Through its role in the global water-, carbon- and energy cycles, vegetation is a key control in land surface processes and land-atmosphere interactions. [...] | TECHNISCHE UNIVERSITAT WIEN (TU WIEN) (AT) | Science | biosphere, carbon cycle, carbon science cluster, land, living planet fellowship, science, Sentinel-1, SMOS | Living Planet Fellowship research project carried out by Mariette Vreugdenhil. Through its role in the global water-, carbon- and energy cycles, vegetation is a key control in land surface processes and land-atmosphere interactions. Vegetation is strongly affected by variability in climate drivers like temperature, radiation and water availability. Vegetation phenology, the timing of vegetation phases, is a sensitive indicator of terrestrial ecosystem response to climate change, and changes herein, e.g. lengthening of the growing season, can influence terrestrial carbon uptake and thus, depending on the net effect, either exacerbate or dampen global warming. The effect of moisture availability on vegetation dynamics is still debated. While some studies found no relation between precipitation and vegetation dynamics when using visible-infrared (VI) remote sensing (RS), others attributed reductions in vegetation water, productivity and carbon uptake to droughts. Thus, the effects of water availability on vegetation dynamics and the subsequent feedbacks are still not fully understood. Nevertheless, understanding these effects are essential since droughts are expected to become more frequent with global warming and demand of agricultural food production increases to ensure global food security. To identify the processes involved in interactions between climate drivers and vegetation dynamics long-term high-resolution Earth Observation (EO) datasets are needed. Microwave RS, with the advantage that it’s not hindered by clouds, smoke or illumination, provides complementary information on vegetation compared to VI RS. Vegetation Optical Depth (VOD), which describes the attenuation of microwave radiance by vegetation, is sensitive to the water content in the above ground biomass. Global VOD datasets are available from active and passive microwave observations, and have been successfully used to study trends and inter-annual variability in vegetation. However, to date the use of microwave observations has always been a trade-off between coarse spatial and high temporal resolution. With the Copernicus Sentinel-1 series, for the first time high temporal and spatial resolution backscatter time series have become available. Studies have demonstrated the sensitivity of the VH/VV Cross Ratio (CR) to vegetation. Here I will optimally combine the Sentinel-1 CR with VOD retrieved from EEUMETSAT Metop ASCAT backscatter observations to develop a global 1 km VOD product. The novel high-resolution VOD will be evaluated using Leaf Area Index from Copernicus Global Land Service (CGLS), ESA’s SMOS VOD and VOD from AMSR2. Subsequently, I will use novel machine learning approaches to quantify the impact of water availability on vegetation dynamics. The high-resolution VOD will allow the analysis of variations in impact of water availability on vegetation dynamics between land cover types, e.g. differences between natural and agricultural lands. |
| SIEMIC: Swarm Investigation of the Energetics of Magnetosphere-Ionosphere Coupling | Living Planet Fellowship research project carried out by Ivan Pakhotin. Ivan's recent published work in magnetosphere-ionosphere coupling (MIC) using the unprecedented Swarm dataset has revealed that Alfven waves play a key role in MIC [...] | UNIVERSITY OF ALBERTA (CA) | Science | ionosphere and magnetosphere, living planet fellowship, science | Living Planet Fellowship research project carried out by Ivan Pakhotin. Ivan’s recent published work in magnetosphere-ionosphere coupling (MIC) using the unprecedented Swarm dataset has revealed that Alfven waves play a key role in MIC dynamics, with small scales carrying very significant amounts of energy. His recent preliminary work has further indicated that in fact most of the Poynting flux carried from the magnetosphere into the ionosphere appears to be carried by small-scale and mesoscale electromagnetic disturbances. This is in contrast to the state-of-the-art in the community, where low-pass filtering methods are routinely used to deliberately attenuate small and mesoscale FACs in an attempt to remove Alfven wave influence. This systematic exclusion of smaller scales leads to chronic underestimations of the energetics of MIC, which translates into uncertainty in the estimations of Joule heating when calculating magnetosphere-ionosphere-thermosphere (MIT) energy transport. Indeed modern MIT models have been found to contain significant uncertainties, particularly in the area of Joule heating and Poynting flux, which is hampering modelling efforts to establish the energy budget for the MIT system for space weather forecasting. This project is a direct continuation of Ivan’s latest work, aiming to answer a single question: how much energy flows from the magnetosphere to the ionosphere at which scales into each hemisphere? His preliminary research has shown that, not only are Alfven waves and small scales extremely important for the energetics of MIC, but also it appears that energy input into the ionosphere may not be symmetric across hemispheres. A statistical study using Swarm electric and magnetic field data has shown consistently higher Poynting flux energy flow on the sunlit hemisphere if the spacecraft is in noon-midnight orbit. This contradicts the hypothesis that the ionosphere is a passive load where the only changes are due to conductivity differences. The interhemispheric asymmetry has been alluded to in recent modelling papers, but to the best of Ivan’s knowledge there has not been a thorough statistical study on this based on spacecraft observations. Such a result would be a significant milestone in understanding MIT energy transfer as it would elucidate the physical nature of key processes which as of now are not well understood. The improved energy calculations considering smaller scales will serve as a valuable input to ionosphere-thermosphere models and studies, and will facilitate high-quality research in that field. |
| Small Satellite Exploitation Accelerator: Video and Fast Update Imaging | Among the innovative data collection capabilities being developed in Europe, video and fast update imaging is widely considered to be enabling for a range of application domains. The “Small Satellite Exploitation Accelerator” project will • [...] | Earth-i Ltd (GB) | Enterprise | Among the innovative data collection capabilities being developed in Europe, video and fast update imaging is widely considered to be enabling for a range of application domains. The “Small Satellite Exploitation Accelerator” project will • Set up, deliver and demonstrate the capability to support a target set of operational applications that integrate video/fast update imagery from small satellites with other operational satellite and conventional datasets and analytic processes. • Test the various working approaches with respect to their suitability for small satellite developers and for fostering cooperation between small satellite developers/operators and existing actors in the EO and geographic information domain A set of use cases will be co-developed in partnership with selected users with the objective to accelerate integration of new data sources into European public sector operational applications and deliver “capability gap filling” of existing and planned Copernicus services. The project will also explore and address needs for advanced EO applications within private sector users and other international users that could not otherwise be met by conventional EO and non-EO systems. In addition, this activity is aimed to advance information requirements collection for applications based on advanced VHR sensors (high resolution, high revisit, now casting, 3D mapping etc). | |
| SMART-CH4 | Methane (CH4) is a potent greenhouse gas contributing significantly to climate change. Due to its relatively short lifetime mitigation efforts on CH4 emissions could rapidly and efficiently pay-off to limit climate change. Targetted mitigation [...] | CEA – Commissariat a l Energie Atom (FR) | Science | atmosphere, atmosphere science cluster, atmospheric chemistry, IASI, Metop, science, Sentinel-5P | Methane (CH4) is a potent greenhouse gas contributing significantly to climate change. Due to its relatively short lifetime mitigation efforts on CH4 emissions could rapidly and efficiently pay-off to limit climate change. Targetted mitigation efforts should rely on a solid understanding of sources and sink of CH4 at all scales, from the global scale to local scales. Dedicated monitoring and modelling efforts are on-going to improve our understanding of the methane budget, including satellite platforms. The main satellite instruments contributing to the current understanding of the methane budget are TANSO on-board GOSAT, TROPOMI on-board Sentinel 5P, and IASI on-board METOP-B and METOP-C. Another category of satellite has recently been added to the existing constellation of CH4-monitoring platforms. These satellites (e.g., GHGSat, PRISMA, MethaneSat) provide very high-resolution data focusing on specific areas. The ESA initiative SMART-CH4 (Satellite Monitoring of Atmospheric Methane) builds upon previous experience and projects in satellite-based methane quantification, aiming to enhance emission products derived from satellites. The key objectives and tasks of SMART-CH4 include: Enhancing TROPOMI retrievals and multi-sensor products, incorporating SWIR/TIR data from IASI and TROPOMI. Advancing fine-scale emission detection using mid-resolution mappers like TROPOMI and high-resolution imagers such as GHGSat, MethaneSAT, EnMAP, or PRISMA. These improvements will lower detection thresholds, enabling the identification of smaller emitters like landfills, wetlands, and agricultural sources. Utilizing improved products to deepen our understanding of regional methane budgets, focusing on three key target regions: (i) Bucharest, Romania, for its landfill super-emitters; (ii) the Arctic, with its scientific interest in peatland and wetland emissions, alongside technical detection challenges arising from Arctic night and albedo effects (from snow and cloud cover); and (iii) South America, concerning tropical wetlands, forest fires, and anthropogenic emissions from landfills and agriculture. Contributing to the attribution of recent trends in CH4 concentrations to specific sectors on a global scale. |
| SMELLS (DUE Innovator III Series) | SMELLS will implement an innovative approach to combine Sentinel-1 SAR data with thermal disaggregated SMOS-derived soil moisture to derive a soil moisture product at both high-spatial and high-temporal resolution to provide a new tool for [...] | ISARDSAT LTD. (GB) | Applications | applications | SMELLS will implement an innovative approach to combine Sentinel-1 SAR data with thermal disaggregated SMOS-derived soil moisture to derive a soil moisture product at both high-spatial and high-temporal resolution to provide a new tool for decision-makers in the Desert locust preventive control system. SMELLS has been developed and demonstrated together with FAO and several national locust entities in West Africa. |
| SMOS+ Med: Sea Surface Salinity in the Mediterranean | Ocean salinity reflects precipitation and evaporation rates, river runoff and ice formation and melting. It is an essential variable for the Earth's climate, because it influences ocean circulation, convection and mixing, through its effect on [...] | UNIVERSITY OF LIEGE (BE) | Science | oceans, science | Ocean salinity reflects precipitation and evaporation rates, river runoff and ice formation and melting. It is an essential variable for the Earth’s climate, because it influences ocean circulation, convection and mixing, through its effect on water density, playing an important role in the global heat exchange between ocean and atmosphere (Lagerloef and Font, 2010), a mechanism that regulates the climate. Through its role in ocean circulation, salinity also impacts primary productivity, making nutrients accessible or not to the food web, having an influence in e.g. fisheries. Salinity also influences, through the thermohaline circulation, the rate of atmospheric CO 2 uptake.This project aims at calculating a sea surface salinity (SSS) field over the north Atlantic Ocean and the Mediterranean Sea for the past 6 years, using a combination of techniques developed by the partners of the project, GEHR (Belgium) and BEC (Spain). This approach combined a debiased non-Bayesian retrieval of the SSS, the use of DINEOF (Data Interpolating Empirical Orthogonal Functions) to correct for systematic errors, and multifractal fusion to obtain a L4 dataset.The resulting dataset has been compared to in situ data, demonstrating that the new methodology reduces by half the error with respect to previous estimates of SSS in the Mediterranean Sea. The dataset is available for download at http://bec.icm.csic.es/thredds/BECEXPMED.html |
| SMOS+ Rainfall Land | Quantitative precipitation estimate is one vital input to meteorologists, hydrologic scientists, water resources managers, and environmental legislators. Yet, accurate measurement of precipitation over the relevant space and time scales remains [...] | CNRS, DELEGATION REGIONALE ALPES (FR) | Science | land, science, SMOS, water cycle and hydrology | Quantitative precipitation estimate is one vital input to meteorologists, hydrologic scientists, water resources managers, and environmental legislators. Yet, accurate measurement of precipitation over the relevant space and time scales remains a challenge. Soil moisture can be seen as the trace of the precipitation and, consequently, can be useful for providing a way to estimate rainfall accumulation or at least a new constrain to rainfall algorithms. In this context, the objective of the ‘SMOS+RAINFALL’ project is to ingest satellite soil moisture information derived from ASCAT, SMOS and SMAP into the latest state-of-the-art satellite precipitation products like those derived from the Global Precipitation Measurement mission (GPM) to enhance rainfall observation accuracy over land. Two main approaches are considered in the project: 1) the Soil Moisture to Rain (SM2RAIN) approach which retrieves rainfall information from satellite soil moisture by inverting the soil water balance equation and then merge it with the Integrated Multi-satellitE Retrievals for GPM (IMERG) Early Run version via an Optimal Linear Interpolation approach and 2) Precipitation Inferred from Soil Moisture (PrISM) approach which is based on a particle filter data assimilation. Key features Potentially availability of enhanced rainfall observations in near real time with a latency of about 1 to 3 days No use of ground-based observations which over data scarce regions can be very uncertain due to interpolation errors. Use complementary microwave-based satellite soil moisture observations as to obtain always best rainfall correction in space and time. |
| SMOS+ Rainfall Ocean | Several recent studies have concluded that climate change causes major changes in the global water cycle. There is increasing evidence that part of the multi-decadal trends observed on the sea surface salinity (SSS) are due to changes in the [...] | ARGANS LIMITED (GB) | Science | oceans, science, SMOS, water cycle and hydrology | Several recent studies have concluded that climate change causes major changes in the global water cycle. There is increasing evidence that part of the multi-decadal trends observed on the sea surface salinity (SSS) are due to changes in the global water cycle, e.g. the western tropical Pacific has become fresher and the subtropical North Atlantic has become saltier. Given that most of the evaporation and precipitations occur over the ocean, a main challenge for studying the global water cycle is the monitoring of freshwater fluxes over the ocean. However monitoring these fluxes is difficult, in large part because precipitation is a very variable and intermittent process. Hence, it has been shown that the measure of sea surface salinity (SSS) provides an indirect but integrated information on air-sea freshwater flux that might be powerful for monitoring changes in the water cycle. This was one of the major motivations for observing SSS from space and two satellite salinity missions: the Soil Moisture and Ocean Salinity (SMOS) and the Aquarius missions, which now have provided global SSS fields over the last several years. STSE SMOS+ Rainfall aims to exploit potential offered by SMOS L1 and L2 measurements to infer or enhance rainfall information over the global ocean, as well as define the potential contribution of SMOS to current efforts to retrieve rainfall information from satellites. The project has developed a suitable and scientifically sound methodological approach to exploit SMOS observations to retrieve or enhance existing rainfall information, by estimating the SSS anomalies caused by rainfall and calibrating a model that relates such anomalies to rainfall rates. The novel methodology relies only in SMOS data to obtain rainfall estimations, if well additional satellite-derived rainfall data has been used for both calibration and evaluation of the product, namely SSMI and IMERG. The project has also defined the range of validity, error structure and uncertainty of these retrievals and created a roadmap towards their improvement and integration into other existing rainfall products. Current results show that SMOS-derived rainfall performs better over ocean than some of the existing radiometer-derived products, and it has consistent results when comparing with IMERG. A global algorithm is currently under development to extend the current processor to a larger scale than the ones contemplated in the study previously. This study proves that SMOS can contribute to the increase of knowledge about the water cycle and that L-band missions can play a significant role in the acquisition of rainfall data at global scale. |
| SMOS+ VEGETATION | ESA’s SMOS mission is part of ESA’s Living Planet Programme and carries the first-ever, polar-orbiting, space-borne, 2-D interferometric radiometer providing observations at 1.4 GHz. From the Level 1 brightness temperatures we derive the Level-2 [...] | THE INVERSION LAB THOMAS KAMINSKI CONSULTING (DE) | Science | biosphere, carbon cycle, carbon science cluster, land, science, SMOS | ESA’s SMOS mission is part of ESA’s Living Planet Programme and carries the first-ever, polar-orbiting, space-borne, 2-D interferometric radiometer providing observations at 1.4 GHz. From the Level 1 brightness temperatures we derive the Level-2 data products, namely surface soil moisture and vegetation optical depth (VOD) (over land) and sea surface salinity (over oceans). SMOS not only contributes towards our understanding of the global water cycle, but also has the potential to improve our understanding of the global carbon cycle. The assimilation of SMOS soil moisture into a carbon assimilation scheme built around a terrestrial biosphere model was found to improve global CO2 flux estimates. Similarly, assimilating SMOS soil moisture and AMSR-E C-band VOD data into an evapotranspiration (ET) model was found to improve ET and root-zone soil moisture estimates over Australia.However, there is still a lack of in-depth understanding of the VOD product, and its potential to monitor vegetation properties and processes has not yet been satisfactorily explored. In this context, this activity aims to increase the scientific return of the SMOS VOD data product by preparing and promoting its use for vegetation applications in the fields of agriculture, drought monitoring and land surface modeling. |
| SMOWS: Satellite Mode Waters Salinity, in synergy with Temperature and Sea Level | Living Planet Fellowship research project carried out by Audrey Hasson. Mode waters (MWs) transport a large volume of heat, carbon and other properties across basins at seasonal to longer time-scales and thus play a major role in the [...] | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) (FR) | Science | living planet fellowship, ocean science cluster, oceans, science | Living Planet Fellowship research project carried out by Audrey Hasson. Mode waters (MWs) transport a large volume of heat, carbon and other properties across basins at seasonal to longer time-scales and thus play a major role in the modulation of the Earth climate. In the context of anthropogenic global warming, unlocking the understanding of the MWs transport and characteristics is critical. MWs in the South Pacific Ocean are of particular interest because of their likely interaction with the El Nino Southern Oscillation (ENSO). Variations in the MWs, their relation with the observed long-term changes and possible implication for ENSO remain unknown. This proposal offers to investigate the MWs characteristics in surface salinity (SSS), temperature (SST) and sea level (SL), which are all Essential Climate Variables (ECV) emphasized by three European Climate Change Initiatives (CCIs). Their link with interannual to longer time scale variability of the Pacific Ocean also need further examination. MWs are subducted from the subtropical and sub-Antarctic Pacific mixed layers and subsequently flow equatorward at the subsurface or intermediate depth. They export the characteristics acquired at the surface into the subtropical gyre and the equatorial region. Surface observations can in consequence give us insight of the future characteristics found at depth at lower latitudes. According to IPCC (2013), it is likely that both the subduction of SSS anomalies and the movement of density surfaces due to warming have contributed to the observed changes in subsurface salinity. We will investigate properties of the formation areas and associated variations that will drive the volume and characteristics of the MWs. As MWs shoal, they modify the equatorial mixed layer characteristics, and could affect ENSO events. Studies indeed have shown that western equatorial Pacific SST and SSS modulate ENSO through vertical stratification. We will therefore to characterize the mean MWs pathways, properties and associated variations. In conclusion, the South Pacific Ocean is at the forefront of interannual variability to long-term modifications associated with climate change. It is therefore essential to study the observed SSS changes as they impact ENSO and SL variations. Satellite observations associated with in situ and modelling would ultimately enable us to unlock our understanding of the role of MWs SSS signature on interannual to longer timescale variability of the South Pacific Ocean. |
| SOLFEO – Spaceborne Observations over Latin America For Emission Optimization applications | South America hosts the Amazon rain forest, the largest source of natural hydrocarbons (HC) emitted into the atmosphere. However, the forest undergoes continuous pressure due to increasing needs for pasture and agricultural land. Next to this, [...] | KNMI (NL) | Science | applications, atmosphere, atmosphere science cluster, permanently open call, science | South America hosts the Amazon rain forest, the largest source of natural hydrocarbons (HC) emitted into the atmosphere. However, the forest undergoes continuous pressure due to increasing needs for pasture and agricultural land. Next to this, large urban centers of South America face acute air quality problems. In this tense situation, it is important to closely monitor both the natural emissions released by the rainforest (hydrocarbons) and the rapidly changing anthropogenic emissions from agricultural activities (NH3 and NOx) and fossil fuel burning (NOx). By using satellite observations combined with a state-of-the-art model representation of the relevant processes, we develop advanced inversion algorithms for the estimation of emissions of ammonia(NH3), NOx and hydrocarbons, providing both qualitative and quantitative biogenic and anthropogenic emissions. SOLFEO takes advantage of the fine spatial resolution of OMI (AURA), IASI (METOP) and TROPOMI (Sentinel 5p) data to improve emission estimates over a largely understudied region. |
| Southern Ocean Freshwater (SO Fresh) | Southern Ocean Freshwater (SO Fresh) is a recent ESA funded project (2021-2023) included in the Polar Cluster Initiative. Polar Cluster aims at establishing collaboration with the existing projects in polar areas to put into value of unique, [...] | ARGANS LIMITED (GB) | Science | Antarctica, ocean, polar science cluster, science, SMOS, SST | Southern Ocean Freshwater (SO Fresh) is a recent ESA funded project (2021-2023) included in the Polar Cluster Initiative. Polar Cluster aims at establishing collaboration with the existing projects in polar areas to put into value of unique, added-value capabilities from ESA missions and remote sensing missions in general. SO FRESH goals are to improve our understanding of the different processes governed or affected by freshwater fluxes taking place at the Southern Ocean. SO Fresh scientific objectives are based in four specific case studies aiming at: to improve our understanding on the changes in Sea Ice; to characterize the drivers of the formation of the Weddell Polynya in 2016-2017; to assess the impact on Sea Ice melting due to changes in coastal processes; to analyse the formation of deep water via remote sensing variables. Sea Surface Salinity (SSS) is a key ocean variable for the four case studies. SO Fresh will explore the potential of using SSS in combination with other ocean variables (i.e. Sea Surface Temperature, Sea Surface Height Anomalies) to enhance the state of the art of SO freshwater fluxes, Sea Surface Density variability and Water Mass Transformation Rates. With lessons learned in most recent advancements in SSS processing in the context of ESA SMOS Mission, SO Fresh will produce a dedicated SSS product Southern Ocean. Some of the methodologies to improve SSS data around the Antarctic peninsula may include nodal sampling, Brightness temperature fusion and enhanced debiased non-Bayesian retrievals. SO Fresh started in May 2021, and the first set of data is expected to be available for distribution by the beginning of 2022.To keep in touch with SO Fresh Team, follow the link or send email to sofresh@argans.co.uk. |
| Southern Ocean-Ice Shelf Interactions (SO-ICE) | The European Space Agency (ESA) Southern Ocean-Ice Shelf Interactions (SO-ICE) project is a collaborative research project bringing together the ESA Polar+ Ice Shelves and 4D Antarctica projects, and the European Commission Southern Ocean Carbon [...] | UNIVERSITY OF LEEDS, SCHOOL OF EARTH AND ENVIRONMENT (GB) | climate, Glaciers and Ice Sheets, polar science cluster, science, snow and ice | The European Space Agency (ESA) Southern Ocean-Ice Shelf Interactions (SO-ICE) project is a collaborative research project bringing together the ESA Polar+ Ice Shelves and 4D Antarctica projects, and the European Commission Southern Ocean Carbon and Heat Impact on Climate (SO-CHIC) project, in order to improve understanding of the processes controlling ice-ocean interactions in Antarctica. This project will use state-of-the-art Earth Observation techniques to measure the flow and thickness of ice shelves in the Weddell Sea region of Antarctica. Observations and modelling of ocean circulation will then be used investigate how the ocean is both driving and responding to these ice shelf changes. By bringing together these ocean and ice systems, this project will lead to substantial improvements in our understanding of ice shelf-ocean interactions across a range of spatial and temporal scales, which is critical to understanding and predicting the response of the ice sheet to a changing climate. | |
| Space4SafeSea | The ocean surface circulation with all its time-space complexity is the open-air limb of the oceanic mass transport. Surface currents carry heat (climate), plankton (marine biology), plastic (pollution). As well wave-current interactions lead to [...] | e-Odyn (FR) | Applications | altimeter, applications, marine environment, oceans, science, sea surface topography, security, water resources | The ocean surface circulation with all its time-space complexity is the open-air limb of the oceanic mass transport. Surface currents carry heat (climate), plankton (marine biology), plastic (pollution). As well wave-current interactions lead to significant sea state variability and strong wave height gradients inside relatively small geographic zones. The complex behaviour of the coupled wave-current system represents challenging risks for socio-economic activity at sea: merchant shipping, renewable energy production, oil & gas operations, fishing activities, and tourism. In addition, the intensification of sea fluxes as the result of global climate changes even complicates marine safety challenges and increases the number of risks related to unfavourable ocean. Accurate, high-resolution estimate of ocean surface currents is both a challenging issue and a growing end-user requirement. Yet, the global circulation is only indirectly monitored through satellite remote sensing; to benefit the end-user community (science, shipping, fishing, trading, insurance, offshore energy, defence), current information must be accurately constructed and validated from all relevant available resources. The objective of the Space4SafeSea project is to develop and validate for maritime safety applications an ocean state product based on synergetic use of a new merged ocean current and surface wave data in the Great Agulhas region, an area synonymous of hazardous sea state and rogue waves due to the interaction between the wave and the current. The new merged ocean current will be derived from Altimeter data and AIS-based current using the Multiscale Inversion for Ocean Surface Topography (MIOST) variational tool. The directional spectrum of sea surface waves from SWIM will be used in conjunction with a wave-model output and swell ray propagation model. The resulting data processing methodology and implemented algorithms will provide robust estimations for spatial distribution of complicated ship navigation zones due to sea-state conditions. An initial version of this product will be followed by evaluation and feedback from end-users who have directly experienced ground truth situations, leading to further methodology and technical development cycles to successively refine the final product output. |
| SPATIAL – Soybean Price forecAsting based on saTellite-derIved services and Artificial intelligence | The main objective of SPATIAL is to provide a proof-of-concept (PoC) prototype for forecasting soybean futures contracts price moves using Artificial Intelligence models based on financial & macroeconomic features and Earth Observation [...] | HYPERTECH S.A. (GR) | Digital Platform Services | agriculture, AI4EO, applications, permanently open call | The main objective of SPATIAL is to provide a proof-of-concept (PoC) prototype for forecasting soybean futures contracts price moves using Artificial Intelligence models based on financial & macroeconomic features and Earth Observation products. SPATIAL is realizing two distinct Machine Learning (ML) models, one for soybean crop yield forecasting and one for prediction of soybeans futures contracts price moves, to demonstrate the feasibility of the method, the benefits of integrating Copernicus EO products and to showcase the potential of such approach. Predictability of soybeans futures contract price moves is particularly important to agricultural organizations, food companies or even to traders. The SPATIAL solution builds upon a) the expertise of the prime contractor, HYPERTECH S.A. (www.hypertech.gr), in financial assets price forecasting through machine learning and predictive analytics models for financial asset prices prediction based on traditional and alternative data sources along with its multi-year expertise on financial markets dynamics and deep knowledge on the key factors affecting commodities prices b) the expertise on the development and deployment of Space-based applications of NOA (www.noa.gr) for estimating soybeans crop yields and production. |
| Spatiotemporal SEN2VHR: Enhanced Spatiotemporal Land Change Monitoring Based on Sentinel-2 Time Series and VHR Images | This project is building on the results of a precursor ESA activity ("Feasibility Study on Enhanced Land Resources Monitoring Based on Synergy use of Sentinel-2 TimeSeries and VHR Images" (SEN2VHR)."). The precursor proved the technical [...] | Mapradix s.r.o. (CZ) | Enterprise | Sentinel-2 | This project is building on the results of a precursor ESA activity (“Feasibility Study on Enhanced Land Resources Monitoring Based on Synergy use of Sentinel-2 TimeSeries and VHR Images” (SEN2VHR).”). The precursor proved the technical feasibility of combining Sentinel-2 time series with VHR images. An initial SEN2VHR value added product was designed and verified in ‘laboratory’ environment. The present activity will enhance the robustness of the developed SEN2VHR prototype system, by true spatiotemporal modelling, and verify it against current state-of-the-art operational services, at the two spatial scales simultaneously (High Resolution and Very High Resolution), by taking the Copernicus land products as a reference baseline. Two types of thematic use cases are planned: forest change monitoring and urbanexpansion monitoring. |
| Stratospheric ozone from limb observations: validation of the profiles, evaluation of trends and their dynamical and chemical drivers (SOLVE) | Living Planet Fellowship research project carried out by Carlo Arosio. The stratospheric ozone layer suffered a significant decline at the end of the 20th century as a consequence of anthropogenic emissions of halogenated substances. An ozone [...] | UNIVERSITY OF BREMEN (DE) | Science | atmosphere, living planet fellowship, science | Living Planet Fellowship research project carried out by Carlo Arosio. The stratospheric ozone layer suffered a significant decline at the end of the 20th century as a consequence of anthropogenic emissions of halogenated substances. An ozone recovery has been predicted for the current century in response to the actions taken under the Montreal Protocol and its amendments. The onset of this ozone recovery has been detected over the last decade and analysed using satellite measurements. The observed ozone changes show a complex structure as a function of altitude and latitude, which is related to the interplay between atmospheric transport and chemistry, both affected by climate change. The driving mechanisms responsible for the observed behaviour of stratospheric ozone are still insufficiently investigated. Limb observations are an optimal tool to globally monitor the vertically-resolved composition of the stratosphere at high temporal and spatial resolution. While some limb-viewing NASA instruments are still in operation, no ESA limb sensors are currently operating, after the loss of communication with the Envisat satellite in 2012. The start of the next European – ALTIUS limb mission is not planned before 2022. This project aims at investigating long-term ozone changes over the last two decades, by exploiting ESA and NASA limb satellite instruments. In particular, we build on the expertise at the University of Bremen acquired with SCIAMACHY data and use OMPS-LP satellite measurements to bridge the gap in limb observations before the ALTIUS launch. All these instruments exploit the same measurement technique, i.e. they collect scattered solar light in limb geometry. |
| STREAM-NEXT | This project is a proposal extension of the ESA STREAM project (SaTellite based Runoff Evaluation And Mapping, Contract Number 4000126745/19/I-NB) and it is addressed to investigate the possibility to extend at global scale the estimation of [...] | CNR-RESEARCH INSTITUTE FOR GEO-HYDROLOGICAL PROTECTION – IRPI (IT) | Science | applications, permanently open call, science, water cycle and hydrology | This project is a proposal extension of the ESA STREAM project (SaTellite based Runoff Evaluation And Mapping, Contract Number 4000126745/19/I-NB) and it is addressed to investigate the possibility to extend at global scale the estimation of runoff and river discharge by using satellite observations. In particular the project will explore the feasibility to: provide long-term independent global-scale gridded runoff and river discharge estimates from solely satellite observations (i.e., satellite precipitation, soil moisture, water level and and Terrestrial Water Storage Anomalies) without the need for exploiting ground-based observations. These estimates will be compared against land surface model runoff estimates to establish the added value of satellite data above all over highly anthropized areas were modelling the processes could be a limiting factor; understand how much the spatial and temporal resolution of satellite data and specifically the spatial resolution of the gravimetry data affect the model results. This aspect would be important for assessing the benefit of the future gravimetry “NGGM-MAGIC” mission; analyze standardized runoff anomalies to evaluate the impact of climate change on runoff and river discharge trend and to reconstruct past flood or drought events relevant for water resources management. The activity is led by CNR-IRPI with the participation of the Institute of Geodesy (GIS) at University of Stuttgart and the Technical University of Denmark (DTU). The duration activity is of 24 months, until November 2025. |
| Streamride | This project is a proposal extension of the ESA STREAM (SaTellite based Runoff Evaluation And Mapping, Contract Number 4000126745/19/I-NB, ) project and it is addressed to investigate the possibility to improve river discharge estimates by [...] | CNR-RESEARCH INSTITUTE FOR GEO-HYDROLOGICAL PROTECTION – IRPI (IT) | Science | applications, permanently open call, science, water cycle and hydrology | This project is a proposal extension of the ESA STREAM (SaTellite based Runoff Evaluation And Mapping, Contract Number 4000126745/19/I-NB, ) project and it is addressed to investigate the possibility to improve river discharge estimates by merging STREAM approach with the one developed within the ESA RIDESAT (River flow monitoring and discharge estimation by integrating multiple SATellite data, Contract Number 4000125543/18/I-NB, ) project. In particular the project will explore the feasibility to: refine the satellite-based approaches developed into STREAM and RIDESAT projects. New modules and formulations will be added to the original approaches to include elements which allow to overcome the limitations highlighted within the two projects. integrate the two approaches to enhance the river discharge estimation. For the specific case studies, a merging configuration will be selected to optimally integrate the river discharge estimates obtained by STREAM and RIDESAT. The impact of the integration will be established through the comparison with in situ observations and the evaluation of the river discharge accuracy. The activity is led by CNR-IRPI with the participation of the Institute of Geodesy (GIS) at University of Stuttgart and the Technical University of Denmark (DTU). The duration activity is of 12 months, until February 2022. |
| STSE CryoSat+ CryoTop Evolution | The aim of the CryoTop Evolution is to generate L2, L3 and L4 products over the Greenland and Antarctic ice sheets from swath processing of CryoSat SARIn mode data. The CryoTop datasets contain surface elevation generated from swath [...] | UNIVERSITY OF EDINBURGH (GB) | Science | CryoSat, cryosphere, polar science cluster, science | The aim of the CryoTop Evolution is to generate L2, L3 and L4 products over the Greenland and Antarctic ice sheets from swath processing of CryoSat SARIn mode data. The CryoTop datasets contain surface elevation generated from swath processing of CryoSat-2 measurement. The CryoTop datasets also contain gridded products generated from the swath derived elevation, these are 2 Digital elevation models (500 m and 1 km posting) and 2 maps of rates of surface elevation change (500 m and 1 km posting) as well as associated errors. The swath elevation data are provided as NetCDF files following the naming convention of the original CryoSat-2 datafiles provided by the European Space Agency, the gridded products are provided as GeoTIFF files. The methodology and data format are described in the dataset user manual. In particular the CryoTop project has produced swath dataset elevation from baseline C data (2010 – 2016) over the Greenland ice sheet and DEM and rates of surface elevation change at 1 km and over the Antarctica ice sheet and DEM and DH/DT at 1 km. |
| STSE-ARCTIC+ THEME 5 – CONTRIBUTIONS TO THE YEAR OF POLAR PREDICTIONS (YOPP) | The A+5 study belongs to the STSE ARCTIC+ cluster of projects and specifically contributes to the Year of Polar Prediction (YoPP). A+5 is constructing a flexible system for Arctic Mission Benefit Analysis (ArcMBA) that evaluates in a [...] | THE INVERSION LAB THOMAS KAMINSKI CONSULTING (DE) | Science | polar science cluster, science, snow and ice | The A+5 study belongs to the STSE ARCTIC+ cluster of projects and specifically contributes to the Year of Polar Prediction (YoPP). A+5 is constructing a flexible system for Arctic Mission Benefit Analysis (ArcMBA) that evaluates in a mathematically rigorous fashion the observational constraints imposed by individual and groups of EO (and in situ) data products in using the quantitative network design (QND) approach. The assessment of the observation impact (added value) is performed in terms of the uncertainty reduction in seasonal predictions of sea ice area, sea ice and snow volume. Response functions for observations and target quantities are computed by the sea ice-ocean model of the Max Planck Institute (MPIOM) in a global setup with focus over the Arctic. The project started in June 2016 and has a duration of 18 months. First, preliminary assessments address CryoSat-2 sea ice thickness and sea ice freeboard products provided by AWI. The observation impact is quantified through reduction in the uncertainty for predicted sea ice conditions over three regions along the Northern Sea Route (see Figure). The study further plans a systematic assessment of the impact that characteristics of a synthetic snow depth product (sampling frequency and accuracy) will have on the performance of sea ice predictions. |
| SUMO4RAIL | SUMO4Rail aims at a concise evaluation of the German ground motion service (Boden-Bewegungs Dienst – BBD) deformation products with dedicated consideration of the requirements of the Eisenbahn-Bundesamt (German Federal Railway Authority, Germany [...] | GAF AG (DE) | Digital Platform Services | permanently open call | SUMO4Rail aims at a concise evaluation of the German ground motion service (Boden-Bewegungs Dienst – BBD) deformation products with dedicated consideration of the requirements of the Eisenbahn-Bundesamt (German Federal Railway Authority, Germany – EBA) including the valorization of these deformation products for the EBAs monitoring and decision support system. This include: Performing post-processing of BBD base information to “harmonized”/comparable deformation maps. Specification and prototyping of robust procedures and processes, designed to be highly automatable. Validation of processes. User validation of generated information and technical results. Specification and conceptualization of any additionally identified value-added or support services or VHR-monitoring. |
| SUNLIT – Synergy of Using Nadir and Limb Instruments for Tropospheric ozone monitoring | The SUNLIT project aimed at developing new global tropospheric ozone datasets using combination of total ozone column from OMI and TROPOMI with stratospheric ozone column dataset from several available limb-viewing instruments (MLS, OSIRIS, [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | atmosphere, atmosphere science cluster, permanently open call, science | The SUNLIT project aimed at developing new global tropospheric ozone datasets using combination of total ozone column from OMI and TROPOMI with stratospheric ozone column dataset from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The novelty of the SUNLIT approach is using measurements from several satellite instruments in limb-viewing geometry for deriving the stratospheric ozone column dataset. Several methodological developments have been made within the project. The main datasets developed in the SUNLIT project are: Monthly 1°x1° global tropospheric ozone column dataset using OMI and limb instruments Monthly 1°x1° global tropospheric ozone column dataset using TROPOMI and limb instruments Daily 1°x1° interpolated stratospheric ozone column from limb instruments. The data are in open access at Sodankylä National Satellite Data centre https://nsdc.fmi.fi/data/data_sunlit.php Other datasets, which are created as an intermediate step of creating the tropospheric ozone column data, have their own value. These datasets are daily gridded with 1°x1° horizonal resolution and include (i) homogenized and interpolated dataset of ozone profiles from limb instruments, (ii) stratospheric ozone column from limb instruments, and (iii) clear-sky and total ozone columns from nadir instruments. |
| SUPER-RESOLUTION ENHANCED DATA FOR EO APPLICATIONS AND SERVICES – VIDEO DATA SUPER-RESOLUTION | The "New Space" sector remodels the space industry. The multiplication of disruptive innovation methods has increased the possibilities offered in various fields: observation, telecommunication, bugging, navigation assistance, etc. Thus, video [...] | MAGELLIUM (FR) | Enterprise | applications, generic platform service, security | The “New Space” sector remodels the space industry. The multiplication of disruptive innovation methods has increased the possibilities offered in various fields: observation, telecommunication, bugging, navigation assistance, etc. Thus, video acquisition from space offers exciting perspectives of uses. The number of use cases could be numerous if the promises in terms of resolution, acquisition time or revisit are kept. On one hand, the market of still video from space is embryonic but presents a potential of development as soon as operational systems offering satisfactory resolution and revisit capacities are available. On the other hand, Deep Learning algorithms provide performances never reached before by conventional algorithms. The possibility to improve spatial video data by these means allows to address new uses or new markets. Indeed, these last few years, the Super Resolution topic on EO images has been tackled by Deep Learning techniques. The industrialization of these academic studies would allow to enhance even more the value of low-resolution and low-cost EO data, and thus to address new applications. These emerging EO approaches have a tremendous potential, reaching a wide range of stakeholders, be they State, public or private. In order to validate the results of the study on real use cases, we have integrated in our consortium this wide panel of end users: DGA (French MOD) is interested in measuring the improvement in Detection, Recognition and Identification (DRI) metrics brought by SR, CEREMA, a public research centre focused on environment, mobility and land use, is interested to know if SR algorithms on space videos can facilitate illegal maritime activities detection, CEREMA is also interested in measuring port flows activities, HAROPA PORT, the leading port complex, is interested in how SR techniques on space videos can facilitate ship tracking in port areas to facilitate crisis management, implying ships involved in a collision, grounding or stranding on their way to the port, And ERAMET, a French multinational mining and metallurgy company having its own railway network, would like to know if SR algorithms on space videos can provide assessment on damages after a railway incident. This study focuses on the implementation of these disruptive algorithms on the data provided by these new EO services. In order to assess the TRL of these techniques, the following work should be conducted: To carry out a state of the art review on the Super-Resolution methods addressed by Deep Learning techniques, To select and benchmark relevant SR algorithms, To prototype some solutions for the considered satellite dataset, To assess the results on concrete uses cases brought by real end users, To identify issues and to make recommendations for an operational implementation. |
| Super-Resolution Enhanced Data for EO Applications and Services – Topic A: Sentinel-2 Super-Resolution | The one-year ESA project “Super-Resolution Enhanced Sentinel-2 Data for EO Applications and Services” is part of the “EO for Civil Security Applications” activity line of the “Development and Exploitation Component” of ESA’s FutureEO-1 programme [...] | THALES SERVICES NUMERIQUES S.A.S (FR) | The one-year ESA project “Super-Resolution Enhanced Sentinel-2 Data for EO Applications and Services” is part of the “EO for Civil Security Applications” activity line of the “Development and Exploitation Component” of ESA’s FutureEO-1 programme (Segment-1) with the main objective to expand uptake of civilian EO capabilities within the wider law enforcement community and civil security stakeholders in particular using super-resolution of Sentinel-2 imagery. The project primarily objective is to extend the use of Sentinel-2 data for EO Applications and Services through the enhancement of spatial resolution of Sentinel-2 products with Deep Learning techniques. Technical objectives are to identify, develop and validate efficient Deep Learning algorithms for resolution enhancement, to assess the performance of super-resolution and the impacts on the considered existing applications of Earth monitoring from satellite imagery with respect to operational constraints in end users application chains. The consortium gathers recognised experts from the relevant fields of expertise to address the different issues in a consistent way: 1) Thales Services Numériques (France, prime contractor): knowledge of operational uptake for space programs with its rich experience on satellite imagery and Deep Learning techniques; 2) MEOSS (France): Expertise of EO applications and services, strengthening the exploitation of Sentinel-2 for representative use cases from the SCOT de Gascogne and the PETRs of the Pays d´Armagnac, Portes de Gascogne and Pays d´Auch; 3) CESBIO (France): Expertise of EO image data: S2, Venµs, Pleiades. For this project, the following use cases have been selected to evaluate the contribution of the super resolution: Mapping and monitoring of water surfaces, related to agricultural activities. The challenge here is to be able to have spatially resolved information with an intra-annual recurrence to trace the spatio-temporal changes in water surfaces and ultimately to have data on the volumes of water available. Agriculture: hedges and grass strips characterisation. The improvement in level of detail linked to the Super-Resolution of Sentinel-2 could allow better detection of linear landscape elements such as hedges, ditches, grass strips which act as barriers against the risks of erosion, pollution and leaching. Urban areas: semi-urban land cover. The challenge in this case is to be able to replace the Very High-Resolution data by Super-Resolution Sentinel-2 data while keeping the accuracy and geometry for small object detection or even that of long-shaped objects such as roads, alignments of roads and trees. In practice, all of these potential use cases will be implemented in pilot territories in France South-Western providing various range of landscapes and natural features to be fully representative at European level. The added value of the Sentinel-2 Super-Resolution will be assessed both from a qualitative and operational points of views. The methodology and technical approach used for this project is as follows: Reference Data for Training. Two types of sensor perfectly suited to this study will be used: Venµs and Pleiades. Deep Learning Networks. State-of-the-art deep learning solutions dedicated to Super Resolution will be tested and deployed with the collaboration of image processing experts. Test Cases. Each network at each resolution will be assessed in regards to the project and use cases objectives. | ||
| Super-Resolution Enhanced Data for EO Applications and Services – Topic C: Hyperspectral Data Super-Resolution | This activity implements and validates SR algorithms for hyperspectral imagery (HSI). With respect to the input data presented for reconstruction, these considered algorithms will be either 1) fusing of HSI (PRISMA) with an auxiliary [...] | KP Labs Sp. z o.o. (PL) | Enterprise | air quality, coastal zone, hyperspectral | This activity implements and validates SR algorithms for hyperspectral imagery (HSI). With respect to the input data presented for reconstruction, these considered algorithms will be either 1) fusing of HSI (PRISMA) with an auxiliary panchromatic image of higher spatial resolution; or 2) fusing of a HSI without any additional data, exploiting the spatial-spectral fusion of multiple bands within a single HSI; or 3) fusing multiple HSIs (captured at different times) that will realise fusion of spatial, spectral, and temporal information. Application and validation test cases will be carried out for three scenarios: air pollution, precision farming and inland/coastal waters. |
| Super-Resolution for Land Market | The objective of this activity is to prototype a service offering global Earth coverage of satellite images with approximately 2 m resolution in near-realtime at a reduced cost and shorter revisit intervals with respect to VHR (very [...] | Capgemini Technology Services (FR) | Enterprise | The objective of this activity is to prototype a service offering global Earth coverage of satellite images with approximately 2 m resolution in near-realtime at a reduced cost and shorter revisit intervals with respect to VHR (very high-resolution) commercial optical data. Based on a new scientific approach that enhances ground resolution of satellite images via innovative deep learning methods with GAN (Generative Adversarial Neural Networks), the activity will prototype an automatic solution that will increase Sentinel-2 spatial resolution of several spectral bands (RGB, IR). The method is intended to preserve spectral band properties, allowing the use of any standard EO algorithm such as NDVI, LAI etc. on the resulting super-resolution output images. | |
| SuperIce | SuperIce aims to develop a simulator of high-resolution sea ice thickness in the Arctic to address critical questions related to sea ice predictability at seasonal timescales and its role in the Earth's climate system. Current satellite-based [...] | NANSEN ENVIRONMENTAL AND REMOTE SENSING CENTER (NO) | AI4EO | AI4EO, Arctic, snow and ice | SuperIce aims to develop a simulator of high-resolution sea ice thickness in the Arctic to address critical questions related to sea ice predictability at seasonal timescales and its role in the Earth’s climate system. Current satellite-based observations of sea ice thickness provide valuable data but are limited by their spatial resolution. High-resolution information is crucial for accurate predictions and understanding small-scale features such as ice leads and thin ice, which significantly impact seasonal forecasting and heat flux calculations. To overcome these limitations, this project proposes a multi-step approach. First, a physically based sea ice model, neXtSIM, is employed to generate high-resolution synthetic sea ice thickness datasets. These synthetic datasets are then filtered to mimic the resolution of satellite products. An AI-based diffusion model is trained to super-resolve the low-resolution SIT data. Finally, the AI-based model is applied to real Earth observation (EO) data, and its results are validated against high-resolution satellite data. The project aims to achieve several objectives: Exploiting the potential of high-resolution sea ice modeling and AI-based super-resolution techniques to create synthetic datasets for improved seasonal forecasting and climate impact assessment. Quantifying the impact of using synthetic datasets in enhancing EO data. Fostering collaboration between the AI, sea-ice modeling, and remote sensing communities through conferences, seminars, and workshops, promoting diversity and inclusivity in the scientific community. |
| Swarm for Ocean Dynamics | Satellite magnetic field observations have the potential to provide information on dynamics, heat content and salinity throughout the ocean. It is well established that the ocean generates a time-varying magnetic field that depends on its [...] | Technical University of Denmark (DK) | Science | ionosphere and magnetosphere, Ocean Circulation, Ocean Indicators, ocean science cluster, oceans, swarm | Satellite magnetic field observations have the potential to provide information on dynamics, heat content and salinity throughout the ocean. It is well established that the ocean generates a time-varying magnetic field that depends on its motions and electrical conductivity structure. With ten years of high quality observations available from the Swarm satellite trio, and with recent advances in geomagnetic field modelling and data processing strategies, there are now new possibilities for extracting this signal of interest. The Swarm for Ocean dynamics project aims to retrieve the Ocean-Induced Magnetic Field (OIMF) signal, going beyond previously identified tidal signals, and to interpret it with the help of advanced numerical simulations using the latest oceanographic information. The project involves (i) a dedicated scheme for processing Swarm satellite data including corrections for known signals of magnetospheric and ionospheric origin, (ii) high resolution global modelling of the time-dependent internal field at Earth’s surface (iii) spatio-temporal filtering to isolate the time-varying OIMF signal, and (iv) analysis of high resolution numerical simulations based on 4D oceanic flows and conductivities. |
| Swarm Space Weather: Variability, Irregularities, and Predictive capabilities for the Dynamic ionosphere (Swarm-VIP-Dynamic) | The research project aims at providing advanced models of the dynamic ionosphere, which will address plasma irregularities, allow for studies of turbulent structuring, ionospheric plasma dynamics, and will also contribute to the development of [...] | UNIVERSITY OF OSLO (NO) | Science | ionosphere and magnetosphere, swarm | The research project aims at providing advanced models of the dynamic ionosphere, which will address plasma irregularities, allow for studies of turbulent structuring, ionospheric plasma dynamics, and will also contribute to the development of forecasting of space weather effects based on in-situ satellite data. The team aims at using novel modelling approaches as well as approaches that have already proven to be successful in developing models based on in-situ satellite measurements. This proposal should be understood in a broader context of providing a framework that would include advanced dynamic models of the Earth’s ionosphere, including ionospheric interactions with the magnetosphere and lower atmosphere. The work will be within a larger Science Cluster (ESA Solid and Magnetic Earth Science Cluster), and it is envisioned that during the project, active collaboration with teams working on other topics within the given ITT will take place. The primary objective of the new Swarm-VIP-Dynamic project is to provide a suite of dynamic models of the topside ionosphere able to predict key-quantities and demonstrate the operation of such models to operate in a real-time environment. The attainment of this primary objective is based on an ambitious programme of model development, which is only possible due to the lengthy time series of Swarm observations which are now available, the suite of instruments available, the data products which have been generated from these observations and the orbital configuration, which samples all latitudinal regions at all local times. This overall objective will be accomplished through the pursuit of the following specific objectives: An improved modelling method and a new model formulation. Including the ability to include the thermospheric contribution and to model small-scale irregularities. Including the ability to model the interhemispheric variability of ionospheric irregularities. Realizing a thorough validation and performance assessment of the model capabilities. Testing the feasibility of a prototype for a Space Weather nowcasting and forecasting services. Create interactive visual representations of the models and data in the timeline viewer Provide recommendations for future development of the models towards operations and future forecasting services exploiting LEO satellites. |
| SWARM+ 4D DEEP EARTH: CORE project | The goal of the 4D-Earth-Swarm project, supported by ESA, is to improve our understanding of the rapid (interannual) changes in the geomagnetic field, as recorded by the three satellites of the Swarm mission of ESA - as well as earlier [...] | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) (FR) | Science | ionosphere and magnetosphere, science, solid earth, swarm | The goal of the 4D-Earth-Swarm project, supported by ESA, is to improve our understanding of the rapid (interannual) changes in the geomagnetic field, as recorded by the three satellites of the Swarm mission of ESA – as well as earlier satellite missions such as CHAMP and Oersted, and ground-based observatories. The project is planned for 2.5 years, starting in Sept. 2019. It gathers partners from 5 institutes (ISTerre Grenoble; ETH Zurich; Leeds University; IPG Paris, DTU Copenhagen). It involves in particular formatting of geomagnetic records, and their cleaning from external (magnetospheric and ionospheric) sources; numerical simulations of the geodynamo at extreme parameters; modeling of rapid field changes by means of reduced quasi-geostrophic equations; re-analysis of magnetic changes with a stochastic data assimilation algorithm; a specific analysis of the topographic coupling between the core and the mantle; a focus on high latitude jets and the physics on the cylinder tangent to the inner core and aligned with the Earth’s rotation axis. |
| Swarm+ Coupling High-Low Atmosphere Interactions: Ion Outflow | The Swarm+ Coupling: High-Low Atmosphere Interactions ITT Statement of Work (SoW) has highlighted the “compelling scientific problem” of “the least-understood causes of planetary winds,” namely planetary outflows induced by “non-thermal (e.g., [...] | UNIVERSITY OF BERGEN (NO) | Science | atmosphere, ionosphere and magnetosphere, science | The Swarm+ Coupling: High-Low Atmosphere Interactions ITT Statement of Work (SoW) has highlighted the “compelling scientific problem” of “the least-understood causes of planetary winds,” namely planetary outflows induced by “non-thermal (e.g., frictional heating, particle precipitation, wave-particle acceleration) processes.” The Swarm+ Coupling High-Low Atmosphere Interactions: Ion Outflow (“Swarm+ Outflow”) project, which began in May 2019, centers on using Swarm spacecraft to tackle unanswered questions around non-thermal processes that lead to ion outflow. The project approach is as follows: (i) Determine the conditions (eg., local time, solar wind/interplanetary magnetic field, hemisphere, season) under which 50-Hz magnetic field measurements and electron and ion density, temperature, and flow measurements made by Swarm spacecraft may be applicable for the study of energetic ion outflows; (ii) Determine possible statistical relationships between magnetic field perturbations measured by Swarm magnetometers and ion upflows/outflows measured at altitudes above, near, and below those of Swarm spacecraft; (iii) Validate and generalize previously published (e.g., Strangeway et al., 2005; Brambles et al., 2011) empirical relationships between electromagnetic perturbations and ion upflows in the Northern Hemisphere cusp region; (iv) Pending positive statistical results, produce a roadmap for development and refining of a Swarm-based ionospheric outflow product. This approach involves combining Swarm plasma and field measurements with measurements from a host of other instruments, including European Incoherent SCATter (EISCAT) radars, the Cluster satellites, and University of Oslo all-sky camera measurements. |
| SWARM+ COUPLING: HIGH-LOW ATMOSPHERE INTERACTIONS: VERtical coupling in Earth’s Atmosphere at mid and high latitudes (VERA) | As described in the Statement of Work (SoW) document for the Swarm+ Coupling: High-Low Atmosphere Interactions, recent studies have revealed "a clear response of the low-latitude ionosphere to the large-scale meteorological events in the [...] | HELMHOLTZ-ZENTRUM POTSDAM – DEUTSCHES GEOFORSCHUNGZENTRUM (GFZ) (DE) | Science | atmosphere, science | As described in the Statement of Work (SoW) document for the Swarm+ Coupling: High-Low Atmosphere Interactions, recent studies have revealed “a clear response of the low-latitude ionosphere to the large-scale meteorological events in the stratosphere called Sudden Stratospheric Warming events (SSW)”. In response to ESA ‘s Invitation to Tender (ITT), VERtical coupling in Earth’s Atmosphere at mid and high latitudes (VERA) investigates the SSW influence on the upper atmosphere based on Swarm observations, with special focus on the middle- and high-latitude regions. Swarm’s high precision magnetometers and its dedicated constellation for geospace research enable monitoring of inter-hemispheric field-aligned currents (IHFACs). The exploration of the Swarm IHFAC data, and comparisons with state-of-the-art numerical models can reveal how the inter-hemispheric coupling of the ionosphere can be disturbed by atmospheric forcing during SSWs. Also, the pole-to-pole measurements of the electron density by Swarm, along with the ionospheric data from ground-based radars and numerical simulations, will be explored for the possible influence of SSWs on the high-latitude ionosphere. The project was launched in June 2019 under the partnership of the GFZ (DE), CAS (CZ), UNB (CA). The scientific activity will continue until September 2020. |
| SWARM+ INNOVATION – SwArm For Earthquake study (SAFE) | SAFE, SwArm For Earthquake study, is a project coordinated by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and funded by the European Space Agency (ESA), to investigate, by means of data collected from satellites and from [...] | ISTITUTO NAZIONALE DI GEOFISICA E VULCANOLOGIA (IT) | Science | science, solid earth | SAFE, SwArm For Earthquake study, is a project coordinated by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and funded by the European Space Agency (ESA), to investigate, by means of data collected from satellites and from ground-based instruments, the phase preceding the great earthquakes with the aim to identify any electromagnetic signal from space. Flyer of the project is available on this link. |
| SwellStats – Unfolding the Sea State Bias: Isolating a physical mechanism causing swell dependence of SAR altimeters | The Unfolding the Sea State Bias: Isolating a physical mechanism causing swell dependence of SAR altimeters (SwellStats) project is a project funded by ESA aiming at improving the reliability of the estimates of the sea surface’s geophysical [...] | ISARDSAT S.L. (ES) | Science | altimeter, oceans, permanently open call, science | The Unfolding the Sea State Bias: Isolating a physical mechanism causing swell dependence of SAR altimeters (SwellStats) project is a project funded by ESA aiming at improving the reliability of the estimates of the sea surface’s geophysical parameters made by SAR altimetry processing, increasing its value to assess informed climate-related decisions. Estimates of the geophysical parameters of sea surface can be obtained from satellite-based altimetric measurements by interpreting the way in which the surface shapes the reflected pulses of the radar. To do so, the state-of-the-art model used in conventional altimeters considers three significant parameters: the mean surface height, the standard deviation of the sea surface and the backscatter cross-section of the surface. However, with SAR altimetry, the picture is not so clear. When there is a distinct swell in addition to the local wind waves, these three parameters are not sufficient to adequately determine the backscattered waveform. In these cases, using the state-of-the-art model to interpret the returned pulse will give biased estimations of the geophysical parameters. This bias depends on swell, which is variable over the oceans. SwellStats will develop a specific physical mechanism that causes swell dependence of the backscattered waveform, and a method to test this hypothesised mechanism. This method will be a practical means of determining the swell sea directly from SAR altimetric data and avoiding the swell induced bias. The project kicked-off in June 2023 and will last for one year. |
| Synergetic Retrieval from GROund based and SATellite measurements for surface characterization and validation (GROSAT) | Reflectance of the Earth surface is one of the natural major components affecting climate. Surface interaction with incoming solar radiation and the atmosphere has a substantial impact on the Earth’s energy budget. Moreover, the accurate [...] | GRASP-SAS (FR) | Science | Aerosols, Altitude, atmosphere, atmosphere science cluster, permanently open call, science, Sentinel-2, Sentinel-3, Sentinel-5P | Reflectance of the Earth surface is one of the natural major components affecting climate. Surface interaction with incoming solar radiation and the atmosphere has a substantial impact on the Earth’s energy budget. Moreover, the accurate description of the surface reflection is crucial for different atmospheric studies including aerosol and trace gases characterization. One of the grand science challenges in remote sensing and climate studies is the accurate separation of surface and atmosphere contributions to the satellite signal. This separation is a crucial requirement of any algorithm for the accurate retrieval of atmosphere and surface properties from remote sensing measurements (Dubovik et al., 2011, 2021; Hasekamp et al., 2011). Despite the evident need for the universal and robust reference dataset for surface reflectance, BRDF (Bidirectional Distribution Function) and BPDF (Bidirectional Polarization Distribution Function) retrieval validation, it still does not exist. In this project it is proposed to perform a simultaneous synergistic retrieval of aerosol and surface properties using combined ground-based (for example, AERONET) and satellite measurements for obtaining the surface reflectance product with enhanced accuracy (Figure 1). In such approach the main information about aerosol comes from AERONET direct sun and diffuse sky-radiance measurements, whereas the information about surface reflection properties originates from satellite observations. The synergetic AERONET + satellite retrieval approach has already been prototyped within GRASP algorithm in the frame of ESA S5P+Innovative AOD/BRDF (Litvinov et al., 2020; https://eo4society.esa.int/projects/sentinel-5pinnovation). Figur1.. Schematic representation of the GROSAT approach based on synergetic retrieval from satellite and AERONET measurements. Further adjustment of GRASP algorithm to the synergistic retrieval from the combined ground-based (AERONET) and satellite measurements provides new possibilities for aerosol and surface characterization. This GRASP synergetic approach promises to become a rather robust and universal tool that can be applied to any space-borne instruments independently of spatial resolution or information content: for any spectral bands, radiance only or polarimetric measurements, single or multiple view instruments. |
| Synergetic retrieval from multi-mission space-borne measurements for enhancement of aerosol characterization (SYREMIS) | Atmospheric aerosol is one of the main drivers of climate changes. Importance of accurate global aerosol characterization for climate studies and air pollution monitoring is a well recognized problem (e.g., see IPCC AR5 by Boucher et al.2013). [...] | GRASP-SAS (FR) | Science | Aerosols, air quality, Altitude, atmosphere, atmosphere science cluster, permanently open call, science, Sentinel-2, Sentinel-3, Sentinel-5P | Atmospheric aerosol is one of the main drivers of climate changes. Importance of accurate global aerosol characterization for climate studies and air pollution monitoring is a well recognized problem (e.g., see IPCC AR5 by Boucher et al.2013). In addition to the traditional spectral Aerosol Optical Depth (AOD) such characterization should also include such extended aerosol information asaerosol size and type. The global information about aerosol can be obtained from space-borne measurements only. Therefore, climate studies are becoming more and more relying on high quality aerosol characterization from space. At present time there are a number of different satellites on Earth orbit dedicated to aerosol studies. However, due to limited information content, the main aerosol products of the most of satellite missions is AOD while the accuracy of aerosol size and type retrieval from space-borne remote sensing still requires essential improvement. The problem of accurate extended aerosol characterization from satellite measurements is strongly affected by the complexity of reliable separation of atmosphere and surface signals. In addition to this, the information content of the measurements should be enough for aerosol characterization itself. Since the end of the POLDER/PARASOL mission in 2013, no single currently operating satellite satisfies completely the requirements for extended aerosol characterisation. At the same time, different satellites dedicated to atmospheric studies may overpass the same area on Earth surface during the same day but at different times or different relative positions. As a result, being properly collocated, such combined measurements can provide multi-angular,multi-temporal measurements in extended spectral range. More independent satellite measurements with different complementary capabilities are combined,the richer the information content of combined measurements becomes. Thetreatment of these data seems to be beyond the capacity of most of the existent traditional algorithms since the processing of multi-instrument observations is not commonly used. In contrast, such retrieval algorithms of the new generation like GRASP (Generalized Retrieval of Atmosphere and Surface Properties) were specifically designed for synergetic processing of diverse observations and can be highly useful for multi-instrument data processing (Dubovik et al. 2011,2021). The GRASP multi-pixel retrieval concept has already been successfully applied to the observations of different single space-borne instruments: polar-orbiting like POLDER/PARASOL, MERIS, AATSR/ENVISAT, OLCI/Sentinel-3, TROPOMI/S-5p and geostationary, for example, Himawari, satellites. Moreover, the synergetic approaches were successfully approved on the synergy of MERIS and AATSR measurements (ESA CAWA-2 project) as well as on the synergy of the ground-based and satellite (AERONET+OLCI, AERONET+ TROPOMI/Sentinel-5p etc retrieval) measurements (ESA GROSAT project (Litvinov et al., 2021), https://www.graspsas.com/projects/grosat/). In the SYREMIS project we develop the prototyped synergetic retrieval with GRASP algorithm of combined measurements from diverse satellite instruments to bring the accuracy and scope of space-borne aerosol characterization to a new level required for climate studies and air-quality monitoring. In particular, these developments are expected to enhance the accuracy of traditional spectral AOD retrieval and allow the characterization of such aerosol properties as particle size, absorption, and chemical composition. Moreover, the proposed synergetic retrieval is expected to increase essentially the spatial and temporal coverage of the available aerosol product, which is absolutely required to identify aerosol sources and monitor aerosol transport. In this regard, the enhanced synergetic aerosol product is projected to have a significant impact on regional and global climate models (for example, CAMS and MERRA-2 global models). It is also expected to achieve the monitoring of natural or anthropogenic aerosol emissions which is crucial for air quality monitoring. The synergetic retrieval in SYREMIS project is planned to be tested on the currently operating polar-orbiting (TROPOMI/Sentinel-5p, OLCI/Sentinel-3, SLSTR/Sentinel-3) and geostationary (Himawari) satellites. Moreover, the constellation of these multi-mission satellites is expected to be extended in future by the new generation of satellites like Sentinel-5, 3MI/EPS-SG, Sentinel-4, etc. The input for the synergetic retrieval may be diverse measurements from different satellites. Themain attention in this project will be played on the operating polar orbiting and geostationary satellites to enhance current state of aerosol characterization and to test the developments on the actual aerosol events. In particular,the multi-mission constellation in this project includes measurements from such polar-orbiting satellites like OLCI/Sentinel-3 A and B, TROPOMI/Sentinel-5p as well as the geostationary Himawari. On one hand such a constellation will extend the spectral range of the measurements. On another hand it will provide unprecedented spatial and temporal coverage which is crucial for global climate studies and air-quality monitoring. Moreover, the synergetic retrieval tested on this constellation can be easily adapted for future instruments like 3MI, Sentinel-5, Sentinel-4 etc. The brief description of the selected satellites for the prototyped synergetic retrievalis summarized in Table 1. Satellites Description OLCI/Sentinel-3A and OLCI/Sentinel-3B – Polar-orbiting, global coverage – One observation per grid point (4 by 4 pixels) – Moderate spatial resolution – Radiance measurements in VIS and NIR spectral range TROPOMI/Sentinel-5p – Polar-orbiting, global coverage – Hyperspectral measurements in UV, VIS, NIR, SWIR spectral range Himawari – Geostationary. Coverage area: Asia – Every 10 min daily measurements – Radiance measurements in VIS, NIR and SWIR spectral range Table 1.Multi-mission constellation for prototyped synergetic retrieval INNOVATION ASPECTS The synergetic multi-mission retrieval developed in SYREMIS is expected to enhance essentially the characterization of such aerosol produced from space-borne measurements as spectral AOD, SSA, and aerosol size characteristics etc. The proposed synergetic retrievals are expected both to improve accuracy of the retrievals and increase spatial and temporal coverage of the aerosol dataset. As a result, the enhanced synergetic aerosol product is expected to be of particularly high value for global climate studies and aerosol data assimilation in global aerosol models such as CAMS and MERRA-2. RELATED PUBLICATIONS 1. Climate Modelling UserGroup (CMUG), User Requirement Document, version 0.6,2015, 2. Dubovik O. et al.,“Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations“ 2011 : Atmospheric Measurement Techniques, 3. O. Dubovik, D, Fuertes, P. Litvinov at al. “A Comprehensive Description of Multi-Term LSM for Applying Multiple a PrioriConstraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm,Concept, and Applications” Front. Remote Sens., 19 October 2021 4. Litvinov P., O. Dubovik, Ch. Cheng, B. Torres,I. Dubovik et al. “Combined Retrieval from Ground Based and Space-borneMeasurements: New Possibilities for Surface Validation and Beyond.” AGU, 1-17December, 2020. |
| Synergetic use of SMOS L1 Data in Sun Flare detection and analysis (SMOS-FLARES) | The aim of the project is to develop a systematic retrieval of Sun Brightness Temperature in L-Band as measured by the SMOS Mission and analyse its correlation with measurements of solar flares currently used in Space Weather, as GOES X-ray [...] | DEIMOS SPACE s.r.l. (RO) | Science | permanently open call, science | The aim of the project is to develop a systematic retrieval of Sun Brightness Temperature in L-Band as measured by the SMOS Mission and analyse its correlation with measurements of solar flares currently used in Space Weather, as GOES X-ray flux. The analysis will also focus on dedicated re-processing activities on selected dates with new Sun retrieval algorithms recently developed for the SMOS Mission, to assess the suitability of these new techniques and explore further evolutions. The full set of available SMOS Mission Data will be used to perform a systematic timing analysis of Sun L-band brightness temperature measurements with soft X-ray flux at different channels from GOES during flare events. Complementary data sources, as the Stokes polarization parameters from SMOS/MIRAS, hard X-ray flux from HESSI or Extreme UV emission from Proba-2/Lyra will also be analysed for additional correlation insight. The analysis of the results will allow us to relate the relative timing of solar flares observed at different wavelengths to physical processes in flares. X-class flares are the initial objective, but M flare may be included in the sample. The project will also issue recommendations (based on the findings of the analysis part) for the operational use of SMOS data as an asset to SWE monitoring and the possibility of continuing missions in this regard. The Sun Brightness Temperature in L-Band data to be extracted in the scope of this project will be deployed in an online data portal which aims at providing the SWE community with a source of usable data for further analysis than the one performed in this contract. The service will be based on an online portal that will contain SMOS Sun Brightness temperature data for the complete mission, additional reprocessing campaigns and ad-hoc processing data can also be accessed by the users of the service. The data shall be also accessible through dedicated web services, in order to be exposed to other existing systems. The end users of the service would be able to access the Sun BT data by login in into the web portal and selecting the respective dates and processor version. The service can be continuously improved in operation by providing feedback loops, where the quality of its data is compared to other Ground based sources. |
| SYNTHETIC DATA FOR EARTH OBSERVATION (SD4EO) | SD4EO is a study project that aims to demonstrate the benefit of using physically-based simulation data and Artificial Intelligence-based data generation tools in key thematic applications with Earth Observation data and Artificial Intelligence [...] | GMV NSL LTD (GB) | AI4EO | AI4EO, crops and yields, energy and natural resources, human settlements | SD4EO is a study project that aims to demonstrate the benefit of using physically-based simulation data and Artificial Intelligence-based data generation tools in key thematic applications with Earth Observation data and Artificial Intelligence (AI) analytics. The project started in October 2023 and is being led by GMV NSL Ltd (UK), in partnership with the Spanish-based company GMV SGI and the University of Valencia, Spain. In the Earth Observation domain, Artificial Intelligence techniques have the potential to automate complex analyses without human intervention, enhancing sensitivity to specific patterns of interest. However, achieving significant performance with AI-driven analytics necessitates a training phase involving the processing of a large, diverse, balanced, and curated set of images, cross-checked against matching reference labels. In practice, acquiring and meticulously annotating such a vast number of images for all required observation conditions is challenging and typically requires substantial resources. Simulation data, capable of realistically replicating physical conditions, can serve as a valuable and complementary data source in this context. This data can indeed provide synthetic images that mimic real imagery acquisitions, thereby enabling the reproduction of the sensing performance of different types of sensors. Simulated data can be particularly beneficial in Earth Observation thematic domains related to target categorisation. The large number of images required to train any analytic module is difficult to obtain through real sensors, limiting the ability to characterise targets of interest through relevant and accurate image-related attributes. Furthermore, target categorisation is often hampered by a lack of useful, accurate, and verified reference labels. The resources required are considerable, as specialised in-field campaigns typically need to be organised, involving the deployment of advanced equipment and trained data collectors. The present study seeks to establish foundational elements for the ambitious goal of incorporating simulation data into the AI-driven Earth Observation analytic pipelines (AI4EO), and to explore whether this additional data source can supplement the real measurements obtained by EO sensors. With sufficiently realistic simulations, AI analytics could be designed, developed, and implemented with performance levels that match or exceed those that could be achieved with a vast quantity of real images. To achieve this, the study makes use of the most recent technical and technological advancements in the domain of real scene simulation and analyses two main theoretical rationales: Physically-based simulation, which employs configurable mathematical models to characterise a scenario. AI-driven simulation, which utilises training datasets to learn about certain predefined characteristics and applies this knowledge to synthesise simulated data. The project aims to demonstrate the benefit of using synthetic data and simulation-to-reality techniques with AI4EO by targeting the following 3 use cases: Categorisation of crop fields for resource monitoring and management. Categorisation of human settlements for energy consumption monitoring and management. Monitoring of photovoltaic panels status to evaluate the level of self-consumption power generation. During the project, the team will also engage the AI and EO communities to raise awareness about the use of physically-based synthetic data for Earth Observation applications and to disseminate the results. |
| TAVAP: Timing and Variable Application of Plant Growth Regulators | Variable application of fertilizers based on remote sensing data analysis has become popular among farmers focussing on smart agriculture. Some farmers and companies are in similar manner using variable seeding strategies, in order to save costs [...] | World from Space (CZ) | Enterprise | agriculture, crops and yields | Variable application of fertilizers based on remote sensing data analysis has become popular among farmers focussing on smart agriculture. Some farmers and companies are in similar manner using variable seeding strategies, in order to save costs and improve yields. Variable application of plant growth regulators is a promising step towards precision agriculture. A growth regulator, plant growth regulator, or PGR, is a natural or synthetic chemical that is sprayed or otherwise applied to a seed or a plant in order to optimize plant growth and achieve higher yields. PGRs are typically used in row crops to support shoot growth or to prevent lodging. The main objective of the project is to develop a new service, TAVAP, that will optimise the usage of plant growth regulators. The service builds on World from Space’s existing product DynaCrop API which can be integrated into clients’ software. TAVAP is an extension of the current API capabilities based on requirements from end users (farmers) and potential clients (farm management software companies). The main benefit of the service lies in the precise scheduling of applications and variable rate application of PGRs, resulting in simplified decision-making, higher crop yields and savings in PGR consumption, thus making PGR applications more effective while reducing environmental impacts. The service will provide PGR recommendations for selected crops in Europe. Recommendations on the usage of plant growth regulators will be delivered in two perspectives: Time alert and prioritisation – the service will predict ideal time dates for PGR applications based on satellite and weather data. The service will point out the right time for the application of PGR for each field enabling prioritisation and optimised scheduling for all fields within the farm. The notification system will provide up-to-date information to the farmer. Variable rate application – the service will provide maps for variable rate application based on crop spatial variability using the latest satellite imagery, making the PGR applications more effective with minimal waste. The service will provide the information in a simple, task-specific and standardised form through the DynaCrop API service, a satellite crop monitoring system run by World from Space. |
| Technology and atmospheric mission platform – OPerations (TOP) | The atmospheric mission platform has demonstrated that (1) multiple data sources (the "data triangle" namely satellite-based products, numerical model output, and ground measurements) can be simultaneously exploited by users (mainly scientists), [...] | SISTEMA GMBH (AT) | Digital Platform Services | atmosphere science cluster, permanently open call, platforms, science | The atmospheric mission platform has demonstrated that (1) multiple data sources (the “data triangle” namely satellite-based products, numerical model output, and ground measurements) can be simultaneously exploited by users (mainly scientists), and (2) a fully Virtual Research Environment that allows avoiding the download of all data locally, and retrieving only the processing results is the optimal solution. |
| TEMITH – Total Ecosystem Management of the InterTidal Habitat | Intertidal habitats are highly productive areas; they provide bird habitat and feeding areas, commercial fish nursery grounds as well as the ecosystem services of nutrient cycling and coastal protection. Globally, these habitats are in decline [...] | DEIMOS SPACE UK LTD (GB) | Applications | coastal zone, permanently open call | Intertidal habitats are highly productive areas; they provide bird habitat and feeding areas, commercial fish nursery grounds as well as the ecosystem services of nutrient cycling and coastal protection. Globally, these habitats are in decline due to overexploitation, direct damage and numerous other stressors. Achieving total ecosystem management (TEM) to support conservation and sustainable exploitation of the intertidal ecosystem requires extensive habitat monitoring and assessment of pressures. However, budgets for conservation and management are often limited and relevant data may not be collected or may be difficult to access or visualise in a holistic way. The Total Ecosystem Management of the InterTidal Habitat (TEMITH) project aimed to design and prototype a solution to monitor pressures in the intertidal habitat in the Solent region, on the south coast of England, using EO data in addition to existing sources of information. From a proposed four pressures (algal mats, litter, sediment disturbance, wastewater plumes), two became the primary focus for model development as the project progressed. Six U-Net convolutional neural network models were trained to achieve detections of three key sediment disturbance activities (bait digging, shellfish dredging, and boating) from drone and aerial imagery and from high resolution satellite imagery. Three ResU-Net models were developed for detection of algal mats, which can indicate nutrient enrichment, as well as seagrass and saltmarsh (intertidal vegetation of conservation importance), from high resolution satellite imagery. One Random Forest model was developed for their detection from Sentinel-2 imagery. TEMITH was an inter-disciplinary collaboration between Deimos Space UK and the University of Portsmouth, combining expertise in EO and Deep Learning for feature extraction and ecology, respectively. With a statutory duty to protect and conserve intertidal habitats, Natural England and the Southern Inshore Fisheries and Conservation Authority were key partners associated with the project and provided valuable input on data needs and user requirements. Feedback from these and other prospective end users in an Evaluation Workshop highlighted the relevance of the TEMITH outputs and the potential to achieve a more holistic overview (spatial/temporal) of the detected intertidal activities and features with further development of the TEMITH services. |
| Testbed for Brain in Space | Brain in Space is an on-the-ground test environment replicating Spire’s “Low Earth Multi-Use Receiver” (LEMUR) satellite that replicates the functionality and performance of a nanosatellite in space, including the latest and most powerful [...] | Spire Global Luxembourg S.a r.l. (LU) | AI4EO | AI4EO | Brain in Space is an on-the-ground test environment replicating Spire’s “Low Earth Multi-Use Receiver” (LEMUR) satellite that replicates the functionality and performance of a nanosatellite in space, including the latest and most powerful Artificial Intelligence / Machine Learning modules. The Brain in Space testbed is a major step in the development of AI-assisted processing of space sensor data and assessing the potential of using AI for on-board processing on a proven sensor platform. It also provides a test environment to trial different AI frameworks and algorithms for space applications to create new markets and products. And in the same way that Spire satellites are accessed remotely, so is Brain in Space, which is accessible from anywhere in the world, via modern APIs. The ability to recognize patterns and spot anomalies is valuable in any sector but there are some where it is business critical, such as maritime industry or weather predictions. Using the AI computing platforms to enhance data processing capabilities onboard small satellites would make it easier to i.e. detect illegal shipping activities, distress signals from planes and vessels or autonomously detect and assess the probability of a hurricane or tsunami, immediately tasking data collection from the right location and sensor, and initiating direct download to the ground to deliver the warning. Interest has been raised from companies developing space-based applications such as data processing, image recognition, secured transactions, etc. …Across different geographies notably Europe and Asia. The Brain in Space test bed offers a variety of benefits to accelerate the new services development and innovate with smart data processing, including: Smart processing of payload data to increase productivity and make efficient use of satellite resources Stress – testing new applications ahead of the launch into space Enabling edge computing directly on-board of small satellites Accelerating the innovations roadmap of a space-based software applications enabled by AI / ML capabilities onboard a nanosatellite Accelerating the developments of novel space-based services without the high expense and delay of launching a test satellite(s) Empowering AI / ML – driven advances in operations and management of small satellites’ constellation to serve new space-based applications and sensor data analytics |
| The DeepESDL AI-Ready Earth System Data Lab | The Deep Earth System Data Lab (DeepESDL) delivers a service to the Earth Science community. The lab provides convenient access to relevant data sets, many of them generated in ESA’s science projects, in an analysis-ready format. Moreover, [...] | BROCKMANN CONSULT GMBH (DE) | AI4EO | AI4EO, AI4Science, platforms, training and education, virtual labs | The Deep Earth System Data Lab (DeepESDL) delivers a service to the Earth Science community. The lab provides convenient access to relevant data sets, many of them generated in ESA’s science projects, in an analysis-ready format. Moreover, DeepESDL comprises a powerful data science environment with a focus on machine-learning and artificial intelligence workflows. We are committed to open science and encourage and support research users in sharing and publishing products and workflows according to FAIR principles, thus fostering transparency and reproducibility in research. We invite interested users in joining us in this exciting endeavour! |
| The ionospheric signature of auroral and subauroral fast flows | Living Planet Fellowship research project carried out by William Edward Archer. The European Space Agency Swarm satellite mission is advancing the cutting edge of ionospheric space physics. Combined high-resolution measurements of electron [...] | UNIVERSITY OF SASKATCHEWAN (CA) | Science | ionosphere and magnetosphere, living planet fellowship, science | Living Planet Fellowship research project carried out by William Edward Archer. The European Space Agency Swarm satellite mission is advancing the cutting edge of ionospheric space physics. Combined high-resolution measurements of electron density, electron temperature, and electric and magnetic fields provide a robust picture of the electrodynamics of this energetic region. We will leverage the high-quality measurements of the Swarm satellites to advance our understanding of narrow regions of fast flow in the auroral and subauroral regions. These flows often exceed 1 km/s, span less than 100 km in latitude, persisting for several hours. The Swarm mission has already contributed significantly to the study of subauroral ion drifts (SAID) and Birkeland current boundary flows (BCBF). Both phenomena are scientifically relevant topics that are not fully understood. With this proposal, we will continue the study of these phenomena by leveraging newly available Swarm data products. |
| The Marine Atmosphere eXtreme Satellite Synergy – MAXSS | The general objectives of this activity is to foster the scientific exploitation of EO-based products to improve the observation, understanding and prediction of extreme wind events and their interaction with the ocean and the earth system. In [...] | IFREMER (FR) | Science | ocean science cluster, oceans, science, SMOS | The general objectives of this activity is to foster the scientific exploitation of EO-based products to improve the observation, understanding and prediction of extreme wind events and their interaction with the ocean and the earth system. In particular, the required activities include (1) the development, implementation and validation of new methods allowing to fully exploit and optimally combine the wind information obtained in extreme wind conditions (>35 m/s) from different spaceborne sensors, mainly SMOS and S-1 but also other mission data (e.g., Radarsat-2, AMSR-2, Aquarius, SMAP, CYGNSS, radar altimeters…) in order to build a long time series (at least 10 years) of global multi-mission synergy wind products in high to extreme wind conditions (>35 m/s), (2) the production of an atlas of extreme wind events collocated with measurements of the underlying ocean environment as measured from satellite sensors (Sea Surface Height, Sea Surface Temperature, Ocean Colour, Sea Surface Salinity, Wave height) or from auxiliary datasets from in-situ and/or models (ex. Mixed Layer Depth), (3) the exploitation of this reference database to foster new scientific results on how extreme wind events impact the ocean in term of ocean physics, ocean biology and air-sea fluxes, including feedback processes, and how this impacts major Earth System cycles from synoptic to interannual and decadal time scales and (4) the exploitation of this reference database to support the operational user community. |
| Towards the retrieval of lake ice thickness from satellite altimetry missions (LIAM) | Lakes that form a seasonal ice cover are a major component of the terrestrial landscape. They cover approximately 2% of the Earth’s land surface, with the majority of them located in the Northern Hemisphere. The presence (or absence) of ice [...] | H2O GEOMATICS INC. (CA) | Science | altimeter, permanently open call, science, snow and ice, Surface Radiative Properties | Lakes that form a seasonal ice cover are a major component of the terrestrial landscape. They cover approximately 2% of the Earth’s land surface, with the majority of them located in the Northern Hemisphere. The presence (or absence) of ice cover on lakes during the winter months affects both regional climate and weather events, such as lake-effect snowfall. Monitoring of lake ice is critical to our skill at forecasting high-latitude weather, climate, and river runoff as well as for ship navigation and transportation on winter ice roads. Lake ice cover (extent) and ice thickness have been identified as two ECVs by GCOS (2016). However, ground-based measurements of lake ice thickness are sparse in both space and time, and the number of sites where such measurements are made has dramatically decreased over the last two to three decades in many northern countries. In light of this and in support of GCOS, there is an urgent need to develop ice thickness products from satellite observations. Altimetry missions could play an important role in this respect, allowing for systematic measurements of ice thickness for many lakes of the globe. The goal of this 12-month study is to pave the way for the eventual retrieval of lake ice thickness from satellite altimetry missions, supported by a thermodynamics lake ice model (CLIMo; Duguay et al., 2003) and a microwave radiative transfer snow model (SMRT; Picard et al., 2018). SMRT has recently been revised to include lake ice. The study will investigate the sensitivity of backscatter (σ0) and brightness temperature (TB) data collected by satellite altimetry missions to lake ice and on-ice snow properties. To meet this goal, the study will be divided into four main tasks: 1) review of the state-of-the-art in lake ice thickness retrieval as well as an analysis of requirements; 2) forward simulations of σ0 and TB using the latest active/passive version of the SMRT model; 3) comparison of SMRT model simulations with measurements from altimetry missions for a selection of North American and European lakes; and 4) formulation of conclusions and recommendations for future work (a roadmap), including the provision of various options for the development of retrieval framework. The framework could be applied, at a later stage (beyond the scope of this short study), to retrieve lake ice thickness from past, current and, eventually future altimetry missions such as Sentinel-6 and CRISTAL. |
| TRIDENT SERVICE FOR SHIP RECYCLING REGULATION SATEO MONITORING | The TRIDENT project pursued rapid prototyping of a Satellite Earth Observation (SatEO) pre-operational application dedicated to the monitoring of ship recycling laws (and notably the EU Ship Recycling Regulation). During the first phase of the [...] | CybELE LAWGICAL LDA (PT) | Enterprise | generic platform service | The TRIDENT project pursued rapid prototyping of a Satellite Earth Observation (SatEO) pre-operational application dedicated to the monitoring of ship recycling laws (and notably the EU Ship Recycling Regulation). During the first phase of the project the needs and requirements of the ship recycling community have been collected and, accordingly, a prototype architecture has been designed to create an application responding to the needs of this sector. The processes and models tested and validated have been integrated into the final TRIDENT Service prototype to support (i) the monitoring of ship recycling facilities and/or (ii) the monitoring of vessels required to comply with ship recycling legislation. Besides technological development, a Business Viability Analysis has been implemented to ensure the future development and deployment of the service in the next five years. The analysis includes (i) a market segmentation study of the addressable market for TRIDENT Services, (ii) an assessment of the market size and growth potential, (iii) a summary of the service value proposition offered to the community of user, (iv) a summary of the service value chain for the two approaches taken and (v) Service Cost Assessment (SCA). Based on the Business Viability Analysis, a roadmap has been defined including a deployment strategy that aims to smoothly and progressively train the community in charge of monitoring ship recycling activities to use SatEO data in their daily operations. The project involved a wide community of end users: INTERPOL-Environmental Crimes Unit, Human Environment and Transport Inspectorate (ILET), Swedish Police, NGO Shipbreaking Platform, the International Ship Recycling Association (ISRA). |
| Triple-A For Exploitation Platforms | The project has provided a pre-operational demonstration of a Triple-A system (Authentication, Authorization and Accounting) for Exploitation Platforms using modern standards such as Open ID Connect (OIDC) and User Managed Access (UMA) based on [...] | DEIMOS SPACE S.L.U (ES) | Digital Platform Services | permanently open call, platforms | The project has provided a pre-operational demonstration of a Triple-A system (Authentication, Authorization and Accounting) for Exploitation Platforms using modern standards such as Open ID Connect (OIDC) and User Managed Access (UMA) based on open source technologies.The proposed solution addresses significant gaps on current Authentication, Authorization and Accounting services made available to science users and application developers on exploitation platforms. The projeect results are operationally offered as support services to the “Network of Resources” to integrate platfrom services with federeated identity management. |
| Tropical Peat View | Indonesia counts more than 16 million ha of peatland, and a substantial part of these have been converted into plantations (in particular oil palm and acacia) or have been degraded. Both plantations and degraded peatlands are generally drained, [...] | SARVISION BV (NL) | Applications | carbon cycle, permanently open call | Indonesia counts more than 16 million ha of peatland, and a substantial part of these have been converted into plantations (in particular oil palm and acacia) or have been degraded. Both plantations and degraded peatlands are generally drained, primarily through networks of canals. Canal/road mapping on peat. Forest: green, non-forest: white; canal gaps: yellow The Indonesian government is committed to improve peatland management and has established the Peat Restoration Agency (BRG) to coordinate its efforts. This commitment includes the rehabilitation of 3 million ha of degraded peatland, blocking 10,000 km of canals and construction of 10,000 dams in the next few years. SarVision and Wageningen University have developed under the Tropical Peat View project a peat monitoring system to address this large environmental challenge. The system is based on radar imagery and is called the Tropical Peat View monitoring system (TPV). Testing and development were done for the provinces Central Kalimantan and Riau (Sumatra) in Indonesia with the goal to provide support to peat conservation and restoration in Indonesia. TPV provides information to the Indonesian Space Agency LAPAN, BRG, Ministry of Environment and Forestry (KLHK) and other national and international users and stakeholders. Information is provided on deforestation, forest degradation, development of drainage canals, changes in hydrology, fire and fire damage, through innovative use and integration of multiple Earth observation data sources from the European Copernicus Programme (Sentinel-1 C-band radar, Sentinel-2 optical imagery) and other missions (PALSAR L-band radar, Landsat optical, MODIS thermal imagery). |
| UAV OBSERVATIONS OF BRDF AND ALBEDO OVER SEA ICE AND SNOW – UAV-OBASIS | Surface albedo controls the absorption of sunlight and its reflection back to the atmosphere and space. The bright, highly reflecting surfaces such as seasonal snow cover and sea ice cover that expand to cover large areas during winter and [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | Arctic, living planet fellowship, science, snow and ice | Surface albedo controls the absorption of sunlight and its reflection back to the atmosphere and space. The bright, highly reflecting surfaces such as seasonal snow cover and sea ice cover that expand to cover large areas during winter and shrink in coverage during summer have high impact on the surface energy balance of the Earth. Surface albedo estimates with global coverage can be quantified from satellite-based reflectance via complex algorithms. In-situ measurements are needed to develop the albedo retrieval algorithms and validate satellite-derived albedo estimates. In-situ measurements of spectral albedo and, in particular, of the bi-directional reflectance distribution function (BRDF) for satellite validation are rare. In cases where such measurements are available, direct comparison is hampered by scale differences. This challenge is amplified over heterogeneous environments where surface types with high contrast in albedo exist at a spatial resolution higher than that of the satellite sensor. Arctic sea ice during summer months and melt/freeze-up periods, snow-covered and snow-free patterns of Antarctic sea ice, and snow-covered boreal landscape all represent heterogeneous environments. These environments also cover vast areas that are often inaccessible by in-situ measurements. This project aims to fill current gaps in the ground truth albedo and BRDF measurements over heterogeneous polar environments. This will be implemented by state-of-the-art unmanned aerial vehicle (UAV) equipment that enable measurements of spectral and broadband albedo as well as BRDF of the surface and characterization of the different surface types and their spatial proportions with co-located photo-mosaics. UAVs allow us to cover both scales of typical point-scale ground measurements and scales represented by a satellite sensor (10-300 m). With these novel observations, collected by the applicant and her collaborators during recent and upcoming field campaigns, the project aims to characterize the spatial heterogeneity of surface spectral and broadband albedo as well as surface BRDF over Arctic sea ice, Antarctic sea ice and boreal snow-covered landscape (mixture of snow-covered open areas and sparse coniferous forests). These UAV-based measurements of albedo and BRDF will be used to validate and improve surface albedo estimates from Sentinel-2/3 and Landsat-8/9 satellite observations. The proposed project enables the candidate to focus on the BRDF and albedo scale and heterogeneity effects over sea ice and boreal snowy landscape – the critical aspects of research otherwise unfulfilled within current project activities. |
| Understand and mitigate impacts of 3D clouds on UV-VIS NO2 trace gas retrievals by AI exploration of synthetic and real data (MIT3D) | Operational retrievals of trace gas column amounts assume (near) cloud free conditions. However, the large pixel size of the satellite instruments (for example the TROPOspheric Monitoring Instrument on Sentinel 5P, TROPOMI-S5P, is 5.5 km by 3.5 [...] | NILU – NORWEGIAN INSTITUTE FOR AIR RESEARCH (NO) | Science | atmosphere, atmosphere science cluster, permanently open call, science, Sentinel-5P, SUOMI-NPP, TROPOMI | Operational retrievals of trace gas column amounts assume (near) cloud free conditions. However, the large pixel size of the satellite instruments (for example the TROPOspheric Monitoring Instrument on Sentinel 5P, TROPOMI-S5P, is 5.5 km by 3.5 km at nadir) imply that pixels may be contaminated by sub-pixel sized cloud(s). Furthermore, clouds in neighbour pixels may lead to in-scattering of radiation or cloud shadow effects, both which are three-dimensional (3D) radiative transfer effects that may both decrease (cloud shadow) and increase (in-scattering) the retrieved trace gas amount. The goal of the ESA MIT3D project is to understand and mitigate impacts of 3D clouds on UV-VIS NO 2 trace gas retrievals by AI (artifical intelligence) exploration of synthetic and real data. The main objectives of the activity are to: Use AI to find parameters that affect NO2 retrievals using a unique synthetic TROPOMI-S5P data set based on 3D Monte Carlo simulations which includes realistic clouds from large eddy scale simulations. Identify associations between TROPOMI-S5P NO2 and Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) products using maximal information-based nonparametrix exploration statistics. Improve standard 1D NO2 cloud correction. The MIT3D activity thus aims to reduce errors due to the impact of 3D clouds. The achievement of the main objectives will be demonstrated by analysis of cloud affected synthetic and real TROPOMI-S5P data and the quantitative comparison of the MIT3D improved NO2 cloud correction and the standard NO2 cloud correction. |
| Urban Thematic Exploitation Platform | The Urban TEP project has delivered a fully operated environment demonstrating enabling platform techniology for the following aspects: - Technical: Linking big data, IT-infrastructures, processing and analysis solutions; - [...] | DLR – GERMAN AEROSPACE CENTER (DE) | Digital Platform Services | applications, platforms, urban | The Urban TEP project has delivered a fully operated environment demonstrating enabling platform techniology for the following aspects: – Technical: Linking big data, IT-infrastructures, processing and analysis solutions; – Thematic: Provision of standardised, new, and tailored products and services for urban environments; – Societal: Improving access to and distribution of data, methods and information. – Instrument to gain of knowledge on the urban system: – Contribution to close gaps in earth system science; – Increased efficiency, effectiveness and sustainability of functions and services in policy, planning, economy, and science). – Market place of ideas and driver of innovation; – Access point for and network of stakeholders and experts; – Seed point for the animation of new user communities outside EO/geo-sector. |
| Using deep learning with CryoSat radar altimetry to adjust elevations and map SURFace penetration (CryoSURF) | Using CryoSat-2 interferometric synthetic aperture radar (SARIn) altimetry together with NASA’s operation IceBridge and IceSat-2 Lidar data in a multi-layer neural network (NN) in order to enhance CryoSat-2 SARIn swath measurements. Further [...] | UNIVERSITY OF EDINBURGH (GB) | Science | altimeter, CryoSat, permanently open call, polar science cluster, science, snow and ice | Using CryoSat-2 interferometric synthetic aperture radar (SARIn) altimetry together with NASA’s operation IceBridge and IceSat-2 Lidar data in a multi-layer neural network (NN) in order to enhance CryoSat-2 SARIn swath measurements. Further investigation will be carried out into the use of these corrections to derive surface condition state and change. The European Space Agency (ESA), Earthwave and The University of Edinburgh (UoE) have made significant progress with the completeness and accuracy of CryoSat-2 SAR-In Swath elevation models. However the scientific perfectionists in all of us strive for the next level using the latest technological tool set. Ice-sheets are a current contributor to sea-level rise and the fresh water they bring into the oceans can impact global oceanic circulation with global consequences (Vaughan et al., 2013). It is thus very important to monitor ice-sheet elevation and elevation change. Spaceborne Radar and Lidar sensors have revolutionised our ability to monitor the mass imbalance of the cryosphere globally and its contribution to sea level change (Shepherd et al., 2012). Lidar (NASA, 2018) is often used in local airborne campaigns to obtain precise elevation measurements however these campaigns have limited spatial and temporal coverage and are impacted by by weather. Radar performs in all weather conditions but suffers from uncertainties due to time-variable penetration into snow and firn (McMillan et al., 2016; Nilsson et al., 2015). This project uses CryoSat-2 radar altimetry elevation and NASA’s operation IceBridge local airborne Lidar together in a multi layer neural network (NN) to create a timeseries of maps of penetration of CryoSat-2 Swath radar altimetry into the snow and firn. The map will be across large regions of the Greenland margins where CryoSat-2 is in SARIn mode going back to CryoSat-2’s launch in 2010. In addition, IceSat-2 data will be added to the framework for the period post its launch in 2018 enabling maps across a wider range of months beyond the operating window of Operation IceBridge. As the penetration of the Ku microwave signal into the snow and firn relates to the condition of the surface, the maps generated during this project have the potential to be used to inform about surface conditions and change in surface conditions. Additionaly, the maps of penetration can be used to explore the impact of change in surface condition on Lidar and microwave signals and its impact on the use of radar and laser altimetry for the study of ice sheet mass balance and processes. |
| VAD3EMECUM. Vegetation and drought: towards improved data-driven estimated of ecosystem carbon fluxes under moisture stress | Living Planet Fellowship research project carried out by Sophia Walther. Variations of water availability drive plant growth and vegetation carbon uptake from the atmosphere. At present, this induces substantial fluctuations in the global [...] | MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY (DE) | Science | biosphere, carbon cycle, climate adaptation flagship, living planet fellowship, science | Living Planet Fellowship research project carried out by Sophia Walther. Variations of water availability drive plant growth and vegetation carbon uptake from the atmosphere. At present, this induces substantial fluctuations in the global carbon balance and in year-to-year accumulation of atmospheric carbon. Under climate change, water stress is likely to be amplified by more frequent and intense droughts. The integration of global land surface remote sensing and in-situ measured ecosystem carbon fluxes through machine learning offers a unique data-driven perspective to diagnose the carbon cycle response to climate change. However, current approaches like `FLUXCOM’ cannot capture drought effects reliably which strongly limits our capability of assessing interactions between global change and biogeochemical cycles. This limitation is due to insufficient information in the traditionally used Earth observation data on (a) the moisture status, and (b) the individual and highly complex responses of ecosystems to dryness. The adequate representation of these two aspects are key challenges that have been hampering breakthroughs in our ability to model and monitor the biosphere with data-driven and process-based approaches. The above limitations will be tackled by integrating data streams of the sun-induced chlorophyll fluorescence, land surface temperature and vegetation optical depth into data-driven flux models for a better diagnosis vegetative stress reactions as well as completementary information on soil moisture. |
| Verification of Small Satellite Market Development Concepts for Commercial Transportable Ground Station Operators | The aim of this activity is two-fold: firstly, to establish and test implementation approaches for companies operating transportable ground stations to collaborate with small satellite operators in addressing commercial markets for EO data. [...] | Centre of Excellence for Space Sciences and Technologies (SPACE-SI) (SI) | Enterprise | The aim of this activity is two-fold: firstly, to establish and test implementation approaches for companies operating transportable ground stations to collaborate with small satellite operators in addressing commercial markets for EO data. Secondly, the activity will identify outstanding issues constraining the expansion of the prototype approaches and elaborate a road map to support European entities to benefit from the new EO market opportunities. Work has started by establishing relationships with at least one small satellite operator and two downstream EO data providers in order to elaborate efficient interfaces for data downlink and data delivery that will lead to customized ground station capabilities for low-latency access to EO data. As a baseline, NEMO-HD data will be used, but also data from UK-DMC-2 and Carbonite-2 are under consideration. Other potential data providers could include ICEYE, Hyperscout, SFL, GomSpace and ISISPACE. Sinergise and Earth-i are proposed in the baseline scenario as downstream data provider partners. Others could GeoVille, Cosine or C-Astral. A set of verification exercises will be specified and executed in order to identify and mitigate outstanding issues in acquisition and storage of datasets, rapid tasking of the ground stations and planning of downlinks from satellite constellations. The verification results will form a base for elaborating a roadmap for operationalisation. The project consists of the following technical tasks: Task 1 – Consolidate agreements with small satellite and downstream partners Task 2 – Elaborate interface and performance specifications for data downlink Task 3 – Elaborate interface and performance specifications for data delivery Task 4 – Customize ground station capabilities Task 5 – Specify Verification Exercises Task 8 – Management and reporting Task 6 – Execute verification exercises Task 7 – Elaborate roadmap for operationalisation | |
| Vine irrigation from earth observation data – WineEO | Optimizing water resources is a real issue in some geographical area. Temperature have increased by 0,85°C on average between 1880 and 2012 and couldreach 4.8°C by 2100 compared to the period from 1986 to 2005, according to the last IPCC report. [...] | TERRANIS SAS (FR) | Enterprise | agriculture, climate, permanently open call, platforms, Sentinel-2, water resources | Optimizing water resources is a real issue in some geographical area. Temperature have increased by 0,85°C on average between 1880 and 2012 and couldreach 4.8°C by 2100 compared to the period from 1986 to 2005, according to the last IPCC report. As a result, agriculture and viticulture are facing an increasing water scarcity at the same time as a growing demand. This growing pressure leads to the necessity to optimize available water resources without losing neither yield production nor quality. Vine irrigation has been used for a very long time in the so-called “new world” vineyards (Australia, Argentina, United States (California) and Chile) and is widely practiced there. Its adoption in Mediterranean regions is much more recent and is one of the first adaptations of wine growers to the consequences of climate change (Ojeda and Saurin, 2014). Irrigation and water stress management of grapevines is essential in arid and semi-arid areas with limited water supplies to maintain both the quality and quantity of the harvest. This has led the scientific community and companies to develop new technologies for irrigation control, allowing to rationalize the inputs according to the needs of the crop. WineEO project is a step in this direction with the objective of developing an operational irrigation scheduling service for winegrowers. This service, named Wago, is based on a water balance model (named Sa’irr) mixing three data sources: satellite imagery with optical images coming from the Copernicus program (Sentinel-2), in situ data and meteorological data. It provides farmers with irrigation recommendations (when, where and how much water amount apply over the vineyard to optimize water inputs). Two main challenges are identified in this project: Adapting the existing water balance model developed by the Cesbio to vine specificities. Indeed, in contrast to annual crops, vines are characterized by a cover sparsity and a large variability of geometry (rows, inter-rows, vegetation height). Sat’irr model has been mostly developed for one dimensional crops such as wheat and maize. To adapt the model to the vine, it is mandatory to take into account the geometry of the crop. Sentinel-2 optical images are used to determine the growth stage of vineyard. Nonetheless, the spatial resolution of Sentinel-2 bands is one of the limitations for their use in precision viticulture due to the intra-variability of the plots. Advances in Deep Learning in the field of Computer Vision allows enhancing the spatial resolution of these images by using single image super-resolution (SISR) techniques. In the WineEO project, a deep learning SISR was developed to recover a super-resolved Sentinel-2 image at 2.5m in the visible and near-infrared part of the spectrum from its low resolution counterpart. Developing a user friendly platform to allow winegrowers to access Wago products. Wago is a decision-making tool developed to help farmers manage their irrigations by providing irrigation recommandations. The tool is based on Sat’irr model and optical images and calculates the water balance on a daily-basis. The project is led by TerraNIS, which is in charge of the industrialization and commercialization of the service. The Cesbio, a French laboratory, will adapt the Sat’irr water balance model embedded in Wago. Finally, four end-users are targeted in four different countries – Portugal, Italy, Spain and Chile – to test the application in different agronomic conditions (soil, climate, agricultural practices, etc.). |
| VINESAT- SATELLITE – UAV DATA FUSION FOR EARLY ANOMALY DETECTION IN ROW – CROPS | Satellite-UAV Data Fusion for Early Anomaly Detection in Row Crops - Application to Vineyards and Olive Groves" (VINESAT). The project develops Data Fusion of Sentinel-2 and UAV data to obtain high-frequency, high-resolution imagery in both time [...] | SPINWORKS (PT) | Enterprise | crops and yields, permanently open call | Satellite-UAV Data Fusion for Early Anomaly Detection in Row Crops – Application to Vineyards and Olive Groves” (VINESAT). The project develops Data Fusion of Sentinel-2 and UAV data to obtain high-frequency, high-resolution imagery in both time and space. |
| VMDL: Volcano Monitoring using Deep Learning | Living Planet Fellowship research project carried out by Matthew Gaddes. The Earth’s subaerial volcanoes pose a variety of threats to humanity, yet the vast majority remain unmonitored. However, with the advent of the latest synthetic aperture [...] | UNIVERSITY OF LEEDS, SCHOOL OF EARTH AND ENVIRONMENT (GB) | Science | AI4EO, AI4Science, living planet fellowship, natural hazards and disaster risk, SAR, science, Sentinel-1, solid earth | Living Planet Fellowship research project carried out by Matthew Gaddes. The Earth’s subaerial volcanoes pose a variety of threats to humanity, yet the vast majority remain unmonitored. However, with the advent of the latest synthetic aperture radar (SAR) satellites, interferometric SAR (InSAR) has evolved into a tool that can be used to monitor the majority of these volcanoes. Whilst challenges such as the automatic and timely creation of interferograms have been addressed, further developments are required to construct a comprehensive monitoring algorithm, that is able to automate the interpretation of these data. This project will seek to develop a deep learning based model that is able to monitor the majority of the world’s subaerial volcanoes using satellite based measurements. This algorithm will incorporate a model that is trained solely on time series of SAR data, and so does not require pre-training on databases of natural images (e.g. ImageNet). Additionally, the model will feature complementary and diverse inputs, such as phase, coherence, and amplitude. |
| Volcanic monItoring using SenTinel sensors by an integrated Approach (VISTA) | Volcanic monItoring using SenTinel sensors by an integrated Approach (VISTA) project is aimed at developing a novel ensemble of algorithms to completely characterized the effects of volcanic emissions on land and atmosphere. Volcanic activity is [...] | GEO-K SRL (IT) | Science | atmosphere, atmosphere science cluster, land, permanently open call, science, Sentinel-5P | Volcanic monItoring using SenTinel sensors by an integrated Approach (VISTA) project is aimed at developing a novel ensemble of algorithms to completely characterized the effects of volcanic emissions on land and atmosphere. Volcanic activity is observed worldwide with a variety of remote sensing instruments, each one with advantages and drawbacks. Because a single remote sensing instrument able to furnish a comprehensive description of a given phenomenon doesn’t exist, a multi-sensor approach is required. In particular, the aim of this study is the definition of a new generation of integrated methods which aim at exploiting the information of the COPERNICUS Sentinels data (from Visible-VIS to Thermal Infrared-TIR) by means of already consolidated retrieval algorithms and novel ML procedures. The increasing availability of Sentinel’s data allows an innovative perspective to achieve the objective of a complete monitoring of the eruptions effects by a unique satellite mission. Currently the possibilities offered by the COPERNICUS Sentinel missions are only partially explored to provide new consistent and statistically reliable information about volcanic cloud quantification and dispersion in the atmosphere and ash deposits on the ground. Such information is crucial for aviation safety and civil protection purposes therefore new tools to exploit satellite observations are required. The project will develop specific methodologies integrating inverse modeling techniques (based on radiative transfer models) with dedicated machine learning (ML) approaches to formulate a set of novel integrated methods. The expected outcomes of the project are improvements in satellite volcanic ash/ice/water vapour particles/SO2 cloud detection and retrievals (altitude, extension, mass, concentration, aerosol optical depth and effective radius), the development of a specific ML based algorithm to map the presence of ash deposits over land and the generation of new satellite-based prototypal services to mitigate the effect of volcanic eruption on health, environment, aviation and to better understand volcanic processes. |
| W4Repp: Wind for Renewable Energy Production Prediction | The objective of this project is to improve short-term wind forecast by regional-scale numerical weather prediction (NWP) models, through innovative assimilation of spaceborne observations, which at the moment are underutilised. Although an [...] | Verisk Analytics GmbH (DE) | Enterprise | atmospheric winds, hyperspectral | The objective of this project is to improve short-term wind forecast by regional-scale numerical weather prediction (NWP) models, through innovative assimilation of spaceborne observations, which at the moment are underutilised. Although an accurate wind forecast is important for large number of applications, the project will focus on short-range prediction of wind and solar energy production (the latter through the characterisation and prediction of cloud movements). The project aims to improve the use of satellite observations by NWP systems, with focus on the effect of Aeolus and hyperspectral infrared sounder observations on regional-scale performance. The approach will be based on a comprehensive state-of-the-art analysis of the 4D-wind field is generated at regular times during the day. |
| WACMOS Irrigation | Irrigation is one of the greatest human intervention in the hydrological cycle. The knowledge of the distribution, the extent of irrigated areas and the amount of water used by irrigation is needed for different purposes: 1) modelling irrigation [...] | CNR-RESEARCH INSTITUTE FOR GEO-HYDROLOGICAL PROTECTION – IRPI (IT) | Science | science, water cycle and hydrology | Irrigation is one of the greatest human intervention in the hydrological cycle. The knowledge of the distribution, the extent of irrigated areas and the amount of water used by irrigation is needed for different purposes: 1) modelling irrigation water requirements at the global scale, 2) assessing irrigated food production, 3) quantifying the impact of irrigation on climate, river discharge and groundwater depletion. Notwithstanding its recognized importance, to obtain high-quality information about the actual irrigated areas worldwide is nontrivial and the problem is much more pronounced in terms of the quantification of the water actually used for irrigation. In this context, the objective of the WACMOS-MED project is to understand the potential of satellite soil moisture data in detecting and quantifying irrigation at global scale. |
| Water cycle changes characterised from atmospheric moisture recycling (WEATHER) | Living Planet Fellowship research project carried out by Tim Trent. Water vapour is an essential greenhouse gas in the Earth climate system, acting as a natural feedback mechanism for carbon dioxide forcing. Critical to the development of [...] | UNIVERSITY OF LEICESTER (GB) | Science | africa, atmosphere, atmospheric water vapor, carbon cycle, climate, living planet fellowship, Sentinel-5P, water cycle and hydrology | Living Planet Fellowship research project carried out by Tim Trent. Water vapour is an essential greenhouse gas in the Earth climate system, acting as a natural feedback mechanism for carbon dioxide forcing. Critical to the development of cloud and precipitation, water vapour also has a significant influence and impact on surface fluxes and radiative balance. Water vapour is considered to be under natural control as it is sufficiently abundant and short‐lived. On global scales the mean residency time (the time between evaporation and precipitation) of water vapour is roughly 10 days. Under climate change, water vapour is expected to increase at a rate of 6%/K/decade (under constant relative humidity) in line with the Clausius-Clapeyron relationship. However, when it comes to precipitation, there is no simple global correlation with changes in temperature. Therefore, understanding the links between the residence time of water vapour in relationship to trends in global precipitation has great importance for climate studies. The work proposed in this fellowship looks to address this gap by bringing together satellite and reanalysis datasets that represent water in different phases or stages within the hydrological cycle. Through the combination of multiple datasets, I will investigate how well satellite datasets capture the moisture recycling process and the surface-atmosphere interactions relative to modern reanalysis. From a climate perspective, these data can also then be used to asses/Test model data from the recent Coupled Model Intercomparison Project Phase 6 (CMIP6). From the long-term climate perspective, I will also use state-of-the-art measurements of stable water vapour isotopologues from ESA’s TROPOMI instrument to investigate significant events where I detect changes in atmospheric moisture pathways. Water isotopologues allow for extra understanding between the coupling of atmospheric circulation and moisture pathways. Focusing on the African Monsson region, case studies examined in this fellowship will help to bring insight into how transient climate signals manifest on synoptic scales. Using the Monsoon brings a human context to this work due to societal vulnerability to these types of events. |
| Water vapour Isotopologue Flask sampling for the Validation Of Satellite data (WIFVOS) | Atmospheric moisture strongly controls Earth’s radiative budget and transports energy through latent heat. Uncertainties in the atmospheric moisture transport pathways have large effects on climate modelling and prediction. Isotopologues of [...] | FINNISH METEOROLOGICAL INSTITUTE (FI) | Science | atmosphere, atmosphere science cluster, atmospheric water vapor, open call, science | Atmospheric moisture strongly controls Earth’s radiative budget and transports energy through latent heat. Uncertainties in the atmospheric moisture transport pathways have large effects on climate modelling and prediction. Isotopologues of water offer further insights into the water cycle due to fractionation processes on phase changes. High-quality measurements of the vertical distribution of water vapour isotopologues are urgently needed, e.g. to investigate the relative importance of different vertical moisture transport mechanisms, to improve models, and to validate remote sensing observations by satellite borne instruments, including the TROPOMI instrument onboard ESA’s Sentinel 5P satellite. To date, profile measurements are costly and thus sparse. In this project, a novel instrument to measure profiles of water vapour isotopologues from ground to the upper troposphere on a small (<20kg payload) balloon-borne platform will be developed. The system will sample air in flasks at different altitudes, which will be analysed with a cavity ringdown spectroscopy instrument after landing and recovery. The flask sampler will be based on an existing and proven flask sampling technology currently used on drones, which will be adapted to lower pressures and lower water vapour mixing ratios present at higher altitudes up to the tropopause. The new instrument will be much more flexible and cost-effective than current instruments for profiles of water vapour isotopologues on aircraft or large balloons. The instrument will be deployed in a field campaign at Sodankylä with concurrent measurements by the Fourier transform spectrometer within the Total Carbon Column Observing Network (TCCON). Based on these measurements, comparisons with TCCON HDO data product will be made. |
| WIDE-AREA SENTINEL-1 DEFORMATION CLASSIFICATION FOR ADVANCED DATA EXPLOITATION | The WISE (Wide-Area Sentinel-1 Deformation Classification for Advanced Data Exploitation) project focuses on developing advanced tools to exploit the large amount of satellite-borne Synthetic Aperture Radar (SAR) data. The main data source [...] | CENTRE TECNOLÒGIC DE TELECOMUNICACI (ES) | Science | land, living planet fellowship, SAR, Sentinel-1 | The WISE (Wide-Area Sentinel-1 Deformation Classification for Advanced Data Exploitation) project focuses on developing advanced tools to exploit the large amount of satellite-borne Synthetic Aperture Radar (SAR) data. The main data source will be the Sentinel-1 SAR data: this Copernicus mission provides, with its fast revisit time, high-resolution and multi-polarization, an unprecedented amount of data, which need to be fully exploited.The thematic area covered by this project is the study of the ground displacements induced by different phenomena, affecting the natural and the built environment. The deformation will be derived using Persistent Scatterer Interferometry (PSI). The project shall produce maps of labelled deformation areas, geo-located and categorized by their type. This is key to perform a systematic and comprehensive exploitation of deformation datasets over wide areas. The project will exploit the PSI data containing the displacement time series of radar scatterers distributed all over Europe. A relevant data source that will be processed in this project is the re cently-launched European Ground Motion Service (EGMS) as part of the Copernicus Land Monitoring Services, based on Sentinel-1 PSI data. The European Environment Agency, deputing entity for the Service management, is intended as a fundamental stakeholder. The data analysis proposed in WISE unfolds following a rigorous processing chain. First, active deformation areas (ADAs), such as landslides, subsidence, infrastructure stability, will be detected employing a statistical hypothesis test. This operation allows preliminary data selection and removal of noisy pixels, yielding clusters of pixels whose deformation time series are correlated in both space and time. Second, the project shall develop automatic classification methods for the ADAs detected. A first method will identify the features necessary to uniquely define a deformation class, then traditional classifiers will yield the first set of labelled deformation areas. Machine Learning techniques will be adopted to derive more advanced classifiers. An accurate deformation classification technique cannot leave aside the temporal information associated to the persistent scatterers, hence classifiers using one or more memory layer will be employed to underpin this information. The novelty of such methods will be manifold, as they have been little utilised in the Earth Observation domain, and certainly not over an area as wide as Europe. The developed algorithms will be tested on SAR data collected over smaller areas of interest by different sensors, such as COSMO-SkyMed and TerraSAR-X, enabling the evaluation of frequency-diverse data. The labelled ADAs will be associated with metrics quantifying the effective likelihood of the classification performed, supporting potential users of the producedmethods and datasets. The produced maps will be validated using inventories and in-situ data of known deformation phenomena, by selecting representative test sites.The main output will be a database containing labelled deformation areas: a useful product for several end users of ground motion data, e.g. Civil Protection actors and risk management entities. Such a product will support the exploitation of theproducts of EGMS, Sentinel-1 and other SAR mission. The developed software will be freely available with different versions depending on the users’ experience in processing EO data. |
| WIDGEON – Waterborne Infectious Diseases and Global Earth Observation in the Nearshore | Plymouth Marine Laboratory (GB) | Enterprise | Atlantic, health, Sentinel-1, Sentinel-2, urban, water resources | ||
| WIFT: Water vapour Isotopologues From TROPOMI | Living Planet Fellowship research project carried out by Andreas Schneider. The role of atmospheric water vapour in the hydrological cycle, the atmospheric circulation, and the radiation and energy budgets is largely uncertain. Improving [...] | Netherlands Institute for Space Research (NWO-I) (NL) | Science | atmosphere, living planet fellowship, science | Living Planet Fellowship research project carried out by Andreas Schneider. The role of atmospheric water vapour in the hydrological cycle, the atmospheric circulation, and the radiation and energy budgets is largely uncertain. Improving knowledge on these is one of the key challenges in atmospheric sciences and of great importance for projections of climate change. Measurements of water isotopologues provide information about the history of a sampled air parcel due to isotopic fractionation during evaporation and condensation and so give significant constraints for the processes involved. Global observations are especially useful for constraining general circulation models, but to date no satellite data set with high sensitivity in the lowermost troposphere (where most water vapour resides) and decent spatial and temporal resolution and data quality is available. The new Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel 5 Precursor satellite is expected to be a ‘game-changer’, as it measures sunlight reflected by Earth’s atmosphere in the shortwave infrared spectral range with unprecedented spatial resolution up to 7 km × 7 km, daily global coverage, and high radiometric performance. The subject of this project is to exploit these measurements to retrieve the water vapour isotopologues H216O, HDO and, if possible, H218O. To this end, the SICOR retrieval algorithm suite, which has high software maturity, is employed. After setting up a processing pipeline at a high performance computing infrastructure, results will be validated against ground-based observations from the Total Carbon Column Observing Network (TCCON). Should recent data from the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project become available, these will also be used for validation. The influence of state-of-the-art molecular water vapour spectroscopy on the data product will be investigated. Moreover, the feasibility to infer the H218O isotopologue from TROPOMI measurements will be assessed. In this context, the spectral window will be optimised to minimise cross-dependencies between different isotopologues. Finally, the maturity and use of the new data product will be demonstrated. First, it will be compared to simulations with an isotope-enable global circulation model. The topic of the following investigation depends on the outcome of the feasibility study. In case the deuterium excess parameter can be obtained with sufficient accuracy, water vapour originating from combustion shall be studied on city scale. Alternatively, the role of evapotranspiration on the isotopic composition (HDO/H216O) in dependence of land usage will be examined. The outcome of this project will be an additional mature data product in ESA’s portfolio from the Sentinel missions. |
| WOODWATCH – NOVEL ALGORITHM DEVELOPMENT FOR EO APPLICATIONS AND SERVICES IN THE FORESTRY DOMAIN | The goal of Pixstart is to establish a new EO-based service dedicated to the foresters, denoted Woodwatch. This new service will help them to optimize their forest management thanks to ingestion of satellite derived maps into dedicated GIS [...] | PIXSTART (FR) | Enterprise | forestry, generic platform service, Sentinel-1, Sentinel-2 | The goal of Pixstart is to establish a new EO-based service dedicated to the foresters, denoted Woodwatch. This new service will help them to optimize their forest management thanks to ingestion of satellite derived maps into dedicated GIS environments. The present project will consist of developing the scientific part (algorithms) of the Woodwatch service. The project outputs will allow ESA to demonstrate the capacity of Sentinel missions (more specifically Sentinel 1 and Sentinel 2) to provide mandatory and operational resource indicators for foresters. In details, the foresters objectives are to expand their monitoring capacity, to optimize their on-site visits, to manage their forests according to legislation and to anticipate risks like phytosanitary diseases. All of these goals are participating to a main goal which is to improve the wood industry productivity while taking into account the climate change impacts. If you need more information you can contact directly Pixstart : contact@pixstart.io |
| WORLD EMISSION | Pollutant and greenhouse gas emission inventories provide essential information for policy makers, governments and subsidiary bodies to evaluate progress towards emission abatement measures, and decide on future strategies. Inventories use [...] | GMV AEROSPACE AND DEFENCE, SA (ES) | Applications | air quality, atmosphere, atmosphere science cluster, atmospheric chemistry, Ecosystems, environmental impacts, science | Pollutant and greenhouse gas emission inventories provide essential information for policy makers, governments and subsidiary bodies to evaluate progress towards emission abatement measures, and decide on future strategies. Inventories use different methodologies between countries, and have large uncertainties related to both activity data and emission factors. The use of satellite data, notably the imagery of the atmospheric composition, should enhance the accuracy, timeliness and the spatial and temporal resolution of inventories. The European Space Agency (ESA)-funded WORLD EMISSION project kicked-off on 4th of March 2022 and will last two years. The project aims to provide an enhanced global emission monitoring service by developing top down emissions estimates based on satellite data. These estimates based on proven methodologies from the science community will be compared with bottom-up inventories, in close collaboration with end-user organisations, to define related product target requirements. The WORLD EMISSION project team’s ambition is to achieve an emission inventory system with the following characteristics: Species to be monitored: CH4 (methane), CO2 (carbon dioxide), H2O (water vapour), NH3 (ammonia), SO2 (sulphur dioxide), NO2 (nitrogen dioxide), PM (particle matter), CO (carbon monoxide), CH3OH (methanol), CH2O (formaldehyde), CHOCHO (glyoxal), C5H8 (isoprene). Increase spatial and temporal resolution of existing inventories by introducing high resolution satellite data New processing framework that is capable to work globally (at least, capable to manage the heterogeneities of different regions) Cover localized point source emissions from large industrial sites, hotspot emissions from oil, gas, and coal extraction basins forest fires and megacities, and regional and national scale emissions Attribution of the anthropogenic sources to socioeconomic sectors Merge the specific processing stages of each specie into a unified flow For more information on the project, contact Beatriz Revilla-Romero (brevilla@gmv.com) |
| World Ocean Circulation | The objectives of this activity are to (i) develop and validate innovative methodologies allowing to optimize the synergetic capacity offered by satellite data, in situ measurements and numerical models for improving the retrieval of upper-layer [...] | OCEANDATALAB (FR) | Applications | ocean health flagship, ocean science cluster, oceans, platforms, science, sea surface topography, sustainable development | The objectives of this activity are to (i) develop and validate innovative methodologies allowing to optimize the synergetic capacity offered by satellite data, in situ measurements and numerical models for improving the retrieval of upper-layer ocean circulation products over FOUR high-priority pilot areas chosen as to represent at best the diversity of the world ocean circulation regimes, i.e. one polar sea area, one western boundary current, one upwelling region, one coastal area, and ii) in line with the objectives of the United Nations Decade of Ocean Science for Sustainable Development, demonstrate the unique capacity of the innovative products to support effective actions aiming at procuring a clean, safe, sustainably harvested and productive ocean by targeting FOUR high priority pilot applications, i.e. Pollution Monitoring, Safe Navigation, Sustainable Fisheries and Renewable Marine Energies. In order to answer the project’s objectives, the consortium will investigate the four following themes: Theme 1: Sea-state current interactions for Safe Navigation Theme 2: 3D currents and vertical motion for Sustainable Fisheries Theme 3: Surface Lagrangian drift for a Clean Ocean Theme 4: HR wave and current model assessment for a Productive Ocean For each theme, a minimum of two users have been engaged. Their role during the project is twofold. First, they will provide support to the consortium for the user requirement consolidation both in terms of products needed and ocean processes of utmost importance for their applications. Second, it is expected that feedback on usefulness and impact of the WOC products will be obtained through the impact studies performed by the users. In addition to the development of innovative methods and products targeting direct answers to the user needs, a series of tools will be also developed, implemented and maintained during the project. These tools should ease and maximize the WOC users’ involvement and further aim to attract potential new users. |
| WorldCereal – Global crop monitoring at field scale | The overarching goal of the WorldCereal project is to develop an open source EO solution for monitoring of global crop area extent, which can be exploited by a wide community of stakeholders involved in the agricultural sector and active over a [...] | VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK VITO (BE) | Applications | agriculture, applications | The overarching goal of the WorldCereal project is to develop an open source EO solution for monitoring of global crop area extent, which can be exploited by a wide community of stakeholders involved in the agricultural sector and active over a range of scales – from national agricultural reporting, regional crop productivity management, up to global assessment of cultivated crop area extent. Delivering maps of crop area extent in a timely manner and tracking its seasonal changes over time will be emphasized to monitor the dynamics of the global agricultural productive area. The WorldCereal project has the following principal objectives: to demonstrate the feasibility of global crop mapping at field scale based on open high resolution EO data such as Sentinel-1, Sentinel-2 and Landsat-8; to develop innovative and efficient open source EO algorithms and tools making full use of cloud computing capabilities for mapping the global extent of annual cropland and two of the major staple crops wheat and maize on a seasonal basis; to build a collaborative approach to exchange with the agricultural community relevant in-situ data sets and disseminate the global crop mapping results in a transparent manner to showcase the utility of the WorldCereal products by conducting use case studies related to the GEOGLAM initiative and SDG reporting. As the global crop monitoring at field scale is a true global challenge we are happy to count on an impressive international user group supporting WorldCereal: FAO, AMIS, GEOGLAM, AAFC, AFSIS, BAGE, CIMMYT, CIMMYT-GLTEN, DSSI, DG-JRC, GEOSYS, GODAN, ICARDA, ICRISAT, IFPRI, INTA, JECAM, N2AFRICA, NASAHarvest, ONESOIL, PlantVillage, RADI, ROTHAMSTED RESEARCH, WFP. The user group remains open to new stakeholders interested in contributing to the goals of WorldCereal which aims to be a community effort. |
| WorldCover | The KO has been hold the 27 August 2019 at ESRIN, for a duration of 2 years. The Mid Term Review has been successfully passed the 31 August 2020. The Final results are expected for June 2021. The project consists of the following cardinal [...] | VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK VITO (BE) | Applications | applications, land cover | The KO has been hold the 27 August 2019 at ESRIN, for a duration of 2 years. The Mid Term Review has been successfully passed the 31 August 2020. The Final results are expected for June 2021. The project consists of the following cardinal requirements: Generation, delivery and validation of a LC map of the world consisting of a minimum of: 10 predefined classes (based on IPCC Level 1) 10 meters resolution 75 % overall accuracy (as specified by CEOS WGCV) Fast generation and validation (possibly less than 3 months after last data take). Access the website developed by the consortium. |
| WorldSoils | The WorldSoils activity aims at developing a global Earth Observation-Soil Monitoring System (EO-SMS) on a suitable cloud environment utilizing open source and information available from operational services (e.g. information layers from the [...] | GMV AEROSPACE AND DEFENCE, SA (ES) | Applications | applications, land | The WorldSoils activity aims at developing a global Earth Observation-Soil Monitoring System (EO-SMS) on a suitable cloud environment utilizing open source and information available from operational services (e.g. information layers from the Copernicus Land Monitoring Service (CLMS) such as impervious layers e.g. soil sealing, land cover and change, soil moisture, etc…), user exchangeable soil reference data (e.g. LUCAS Topsoil, local or regional reference data (e.g. Soil Spectral Libraries (SSLs)) and additional variables and/or indices derived from EO data together with blending and modelling techniques. The development of the EO-SMS shall be done in close cooperation with authoritative end users with a mandate on reporting on soils, the proximal soil mapping community, and EO experts. EO-SMS shall allow to monitor soil indices relevant for monitoring the global top soils as baseline information for downstream research, institutional and commercial applications and services (e.g. reporting, soil management systems, agricultural applications, …). This project is focused on topsoil organic carbon content. |
| WorldWater, Surface Water Dynamics | The project develops novel multi-source EO tools for monitoring the seasonal and annual dynamics of inland surface waters with the objective to empower countries and river basin authorities with advanced EO technology to manage their water [...] | DHI WATER – ENVIRONMENT HEALTH (DK) | Applications | science, surface water, sustainable development, water resources | The project develops novel multi-source EO tools for monitoring the seasonal and annual dynamics of inland surface waters with the objective to empower countries and river basin authorities with advanced EO technology to manage their water resources and report on the global water agendas. Main objective is to develop a scientifically robust method that exploits the full time series of Sentinel 1, Sentinel 2 and Landsat satellite imagery to better capture the seasonal changes of surface waters in extent, and to complement these observations with radar altimetry measurements of water levels in order to derive the changes in lake volume and river discharge. A Proof of Concept will be conducted in 5 partner countries (Colombia, Mexico, Gabon, Zambia and Greenland) . The Sustainable Development Goal (SDG) on water in the 2030 agenda for sustainable development has brought a spotlight to water policy at global level and in national planning and represents a clear indication that countries worldwide recognise the ‘water crisis’, which has consistently been ranked by the World Economic Forum as one of the threats with the highest potential impact and likelihood. A recent report from the World Resource Institute (WRI) highlights that the ‘water crisis’ is far more commonplace than previously thought. Water withdrawals globally have more than doubled since the 1960s and show no signs of slowing down. Population growth, socioeconomic development and urbanization are all contributing to increased water demand, while climate change induced impacts on precipitation patterns and temperature extremes further exacerbate water resource depletion. The Sustainable Development Goals, especially the goal on ‘clean water for all’ (SDG 6) and the ‘climate action goal’ (SDG 13) therefore need all the attention they can get to avoid an accelerating ‘water crisis’ towards 2030 and beyond. A ‘water crisis’ is ultimately a management crisis that can be solved through the application of sound water management policies. The need for proper and timely information on water (non-) availability is probably the most important requirement for water management activities. In large, remote and inaccessible regions, in-situ monitoring of inland waters is sparse and hydrologic monitoring can benefit from information extracted from satellite earth observation (EO). Rivers, streams and lakes/reservoirs throughout the world provide water for domestic usage as well as for irrigation, for livestock watering and as a source for hydropower and recreation. Still, in most countries, government’s measurement of water resources is limited to major dam resources and river flow stations. This however represents only a small portion of the overall water resources with substantial portions of water being stored in ungauged regions. The unmonitored proportion of water resources represents a major known unknown and representing an information gap which can produce inaccuracies that may lead to ineffective or erroneous decision-making. Monitoring water bodies for a whole country or river basin in a comprehensive manner is essential for the national water resources management in respect to drought mitigation, irrigation management and planning of infrastructure investment (e.g. dam constructions), and EO is increasingly being recognized as an essential tool for large-scale monitoring of water resources. This is needed to promote more efficient planning and decision making, as well as for direct reporting in response to the SDG global indicator framework. The availability of the growing volume of environmental data from the Copernicus Sentinels, combined with data from long-term Earth Observation archives (e.g. Landsat) represents a unique opportunity for the operational usage of EO for operational applications in support of water resource management. Global EO based surface water maps are already readily accessible (cf. JRC Global Surface Water Explorer, Deltares AcquaMonitor and GLAD Global Surface Water Dynamics), but the global products are based solely on optical data (cf. Landsat) and will inevitably tend to have a bias at the national/local level. By launching the WorldWater project, ESA is aiming to meet these shortcomings by further developing EO tools and products to effectively use the most up to date, open and free satellite data, primarily from the Sentinel missions, for improved monitoring of the world’s inland water resources in both extent and volume. WorldWater is about empowering countries and river basin authorities so they can independently monitor surface water dynamics at all scales in a robust way – thereby providing them with essential information for more evidence-based planning and management of water resources and an ability to efficiently report and act in response to the global water agenda. |
| YIPEEO: Yield Prediction and Estimation from Earth Observation | Crop yield forecasting is a vital tool to support stakeholders and decision-makers in preparing for potential yield deficiencies. Most crop yield forecasts so far have been implemented on a regional to national scale. Field-scale forecasts can [...] | TECHNISCHE UNIVERSITAT WIEN (TU WIEN) (AT) | Science | agriculture science cluster, crops and yields, Sentinel-1, Sentinel-2, Sentinel-3 | Crop yield forecasting is a vital tool to support stakeholders and decision-makers in preparing for potential yield deficiencies. Most crop yield forecasts so far have been implemented on a regional to national scale. Field-scale forecasts can add vital information for farmers and insurers but still have much potential to improve. Especially the increasing availability of high-resolution climate data from sources such as Copernicus Sentinel-1, Sentinel-2, Sentinel-3 data, and Proba-V can significantly improve such forecasts. The goal of the YIPEEO project is to improve field-scale crop yield forecasts by using these datasets in combination with novel machine-learning techniques or crop growth models. For this purpose, we are working with various field datasets distributed over Europe (Ukraine, Finland, Netherlands, Denmark, Italy, and several in central Europe). In addition, we will explore the impact of droughts on crop yields, assess the impact of the war on Ukraine’s crop production, and develop an irrigation timing and fertilizer advisory tool |