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Project Abstract Prime Company Domain Tags Full text
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).
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 [...] 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.
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/
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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, 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 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 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.
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).
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.
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.
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. 
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 agriculture science cluster, 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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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.
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.
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.
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-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)
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.
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
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.
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.
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-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-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-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 – 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.
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.
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.
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.
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.
SUP FCP – CROSCIM The focus of CROSCIM is Arctic operations and the development of a processor that will take advantage of the novel products from the Copernicus Expansion missions and deliver near real time and short term forecast (up to 2 days) level 4 products [...] DANISH METEOROLOGICAL INSTITUTE (DK) altimeter, applications, Arctic, polar flagship, SAR, snow and ice The focus of CROSCIM is Arctic operations and the development of a processor that will take advantage of the novel products from the Copernicus Expansion missions and deliver near real time and short term forecast (up to 2 days) level 4 products for sea ice concentration, sea ice thickness, snow thickness, sea surface height anomaly and derived L4 products. The implementation will be co-developed with champion users and demonstrate how the Copernicus Expansion missions will improve the information for future Arctic operations. This will primarily focus on the added value from the polar missions: CRISTAL (dual frequency radar altimeter), ROSE-L (SAR L band) and CIMR (passive microwave). The demonstration of the improvements will be based on two Arctic domains with different characteristics. The first is a pan Arctic that will demonstrate the value of the products from all three sensors and how they contribute with increased coverage and improved monitoring of the Arctic wide sea ice. The second demonstrator is a near coastal demonstration of the impact of ROSE-L, CRISTAL and CIMR products and how they will improve the observations of the sea ice coverage in a High Arctic fjord, namely Disko Bay in Greenland. In order to provide a representative dataset for the future missions, a state of the art sea ice model and a state of the art machine learning model will be used to produce realistic data that mimics the products from the expansion missions. Data will be extracted and resampled according to the descriptions in the Mission Requirement Documents (MRD)’s of the individual satellite missions, which will make the foundation for creating a representative dataset. This will for instance include orbital and sensor characteristics, resolution and expected noise levels. In order to ensure maximum knowledge transfer from the missions to the project, the consortium includes expertise from the CRISTAL and CIMR MAG’s and representatives from the operational SAR processing group including the Greenlandic ice service, who will ensure that the representative data sets are designed according to the specifications. The development of the representative dataset, the processor and the two demonstrators will be carried out in co-development with the two champion users involved in this proposal. These are the Greenlandic ice service at DMI and Drift+Noise who are both intermediate users with focus on the provision of services to the end user. Especially for a demonstration of future satellites it is important to incorporate champion users who both understand the future perspectives and the current needs of the users. The champion users will also ensure that the outreach to the end users are of relevance to the end users
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.  
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.
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, agriculture science cluster, 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.