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AI4Platform: INFER – artIficial iNtelligence for Food sEcuRity – The artIficial iNtelligence for Food sEcuRity - INFER - Project aims to foster adoption of AI models for Earth Observation (EO) applications. Many initiatives have been recently launched by ESA to augment the availability of training data, to [...]CGI ITALIA S.R.L. (IT)Digital Platform ServicesAI4EO, Food Security, platforms, thematic exploitation platformThe artIficial iNtelligence for Food sEcuRity – INFER – Project aims to foster adoption of AI models for Earth Observation (EO) applications. Many initiatives have been recently launched by ESA to augment the availability of training data, to support new ideas through creation and management of challenges, and to incrementally adopt standards that facilitate interchange and reuse of resources. This project has to goal to focus on a more operational aspect, e.g. to enhance existing cloud-based processing oriented platforms (e.g. TEPs, DIAS and other initiatives) by adding AI specific capabilities. These capabilities include the possibility of performing the following: Facilitate creation or improvement of existing models, by running on an already established platform providing seamless access to data and scalable processing resources. Facilitate access to existing training datasets and exchange of training datasets within a community. Provisioning of AI-oriented tools in a unique environment which serves as an experimental lab for Data Scientists. Supporting the possibility for third parties to deploy and make available AI models and training datasets with a predefined remuneration model. We are proposing a simple and robust implementation approach, which is based on the FS-TEP. This platform is already listed in the services offered by the NOR. The platform will be enhanced with additional AI-related features and with an enhanced module supporting fine grained accounting to enable the required business models. The consortium will be led by CGI, who has extensive expertise in developing and operating distributed EO-processing platforms and will integrate a set of tools developed during previous activities, including an ESA activity sponsored by the Open Call mechanism, during which a suite of AI-oriented tools were developed and demonstrated. The consortium will be complemented by 2 partners with solid expertise in EO and with a focus on the AI adoption, namely:  KP Labs, very active in the field of AI activity in ESA will implement a showcase based on super-resolution for hyperspectral data, by leveraging the finding of other related projects. KP Labs will be the independent entity validating the service Vista, the prime contractor of the FS-TEP will bring another showcase focusing on crop mapping and will also complement the consortium with the relevant business-oriented expertise derived from selling commercial EO services to third parties and from the direct management of the NOR offering
AIOPEN The AIOPEN project will combine and extend the existing platform ASB (Automated Service Builder), EOPEN (Open Interoperable Platform for Unified Access & Analysis of EO Data) and EOEPCA (EO Exploitation Platform Common Architecture) with new [...]SPACE APPLICATIONS SERVICES S.A./N.V. (BE)Digital Platform ServicesAI4EO, generic platform service, platformsThe AIOPEN project will combine and extend the existing platform ASB (Automated Service Builder), EOPEN (Open Interoperable Platform for Unified Access & Analysis of EO Data) and EOEPCA (EO Exploitation Platform Common Architecture) with new and innovative services based on operationally mature AI/ML software capabilities to provide a platform that supports the end-to-end AI model development lifecycle. The platform, hosted in the ONDA DIAS, owned by Serco, will be capable to distribute processing tasks in remote environments. The result will be a public commercial service offering a dynamic pricing structure with a remuneration policy for contributors to the platform content (with models or data) or for performing activities such as labelling data and training AI models. AIOPEN will bring together: the processing and data access capabilities of a powerful and flexible platform, the users interested in offering training datasets and AI/ML models, and the EO science and application development community looking at how to exploit these technologies with EO data. The service will allow versioning, sharing and customising the various AI/ML resources and provide the tools to integrate/exploit the AI/ML models in new applications, for example exposing these ones via programming interfaces for running predictions. Based on the Automated Service Builder (ASB) and EOPEN, developed by Space Applications Services, AIOPEN will allow importing custom processes, creating workflows and executing them in a distributed environment to deliver services on user customisable dashboards. Components from ESA/ESRIN EO Exploitation Platform Common Architecture (EOEPCA) project, led by Telespazio, will be included to bring interactive development, cataloguing and sharing capabilities. Popular open-source software will be integrated to include AI capabilities required by the AI model development lifecycle such as the ability to version and store model training projects, publish available models and datasets, annotate raw data, further train models and use models to do predictions. Key operations such as model training and predictions generation will also be available through programming interfaces. Validation Showcases In the course of the project, two showcases related to the Space for a Green Future theme will be implemented using the platform in order to demonstrate and validate its AI capabilities: Forest cover monitoring, proposed by KP Labs, and Urban Change Detection with Transformer Architecture, proposed by IT4Innovations (VSB —Technical University of Ostrava). Forest cover monitoring, including deforestation tracking, can be achieved via segmentation and comparison of segmentation masks. This approach enables the usage of standard, well-known, favourably supervised, architectures like U-Nets for image segmentation. Moreover, images taken at any time interval can be subjected to this type of deforestation analysis. The deforestation tracking will use segmentation as an intermediate step. The resulting model will offer services like generating forest coverage masks, deforestation masks (via subtraction of forest masks), and quantification of deforestation (% of forests that were lost in the given time interval). In the second showcase proposed by IT4Innovations we use EO data and Deep Neural Networks (DNNs) to detect (urban) related changes on the Earth’s surface to construct a digital twin of Earth’s (urban) changes. Detection of how urban areas, cities, infrastructure, and urban sprawl change over time helps to understand the dynamics of how the environment is impacted, to identify new (illegal) settlements, and to extrapolate trends for future planning. The showcase uses modern transformer based architectures to demonstrate the versatility and performance of DNNs for urban change detection.
APPLICABILITY OF SATELLITE AND DRONES EO DATA FOR LANDFILLS DETECTION AND MONITORING SAT+Dron4Landfills is a project which aims to use EO data for effective and timely detection and monitoring of landfills. As a major innovation, two main types of EO data are considered under the project: from existing satellite systems, and [...]FUNDACIÓN ANDALUZA PARA EL DESARROL (ES)Enterpriseland, platformsSAT+Dron4Landfills is a project which aims to use EO data for effective and timely detection and monitoring of landfills. As a major innovation, two main types of EO data are considered under the project: from existing satellite systems, and from in-situ drone campaigns. EO satellite data will be used to provide relevant information to detect illegal landfills, and also to allow macro-scale monitoring capacities. Data from ad-hoc drone campaigns willprovide closer-to-the-ground, more frequent and cloud coverage independency inputs. The development of a data processing platform is proposed to analyze both sources of data, using advanced AI techniques. Moreover, a User Committee has ben created to raise awareness in the community of waste management users of the capacities that EO could bring for the efficient management of landfills.The project is envisaged as a proof of concept for the demonstration of the proposed solution, with field tests in Torija landfill in Guadalajara, Spain. The project started in October 2022 with the characterization of landfills in order to select the key parameters that can be extracted for their efficient detection and monitoring, and the initial activities for identifying available EO satellite resources and the definition of the drone campaigns to carry out.
Arctic Crowdsourcing The Arctic Crowdsourcing project has been successfully completed. The objective was to create an enhanced Earth Observations (EO) services for Arctic applications planned for C-CORE’s Coresight Platform to include community/crowd sourced very [...]C-CORE (CA)Digital Platform Servicespermanently open call, platformsThe Arctic Crowdsourcing project has been successfully completed. The objective was to create an enhanced Earth Observations (EO) services for Arctic applications planned for C-CORE’s Coresight Platform to include community/crowd sourced very high-resolution drone data, ESA Sentinel mission data and other forms of field data that support Arctic stakeholder needs.   The Arctic Crowdsourcing project included: 1)  Engagement of Arctic communities to develop skills around drone operations, as well as GIS, and EO satellite knowledge. The community engagement also investigated remote sensing based services for that could directly benefit communities. 2) The development Arctic Crowdsourcing Service for collecting community-sourced knowledge, targeting community sourced Drone Data, and geotagged video and image data. 3) The prototype development of enhanced EO based services and incorporate other community sourced data or new products created via the Polar TEP. The developed products were on display and ready for live demos at ESA’s Living Planet Symposium May 2019 in the C-CORE booth, and available publically to all, after the symposium. The project involved direct engagement with community members via several face-to-face meetings with communities, supporting the establishment of training programs and the hiring of local commercial drone operators to collect test scenario data.  Initial community engagement highlighted two obstacles to support crowdsourcing of drone imagery which were the lack of in region drone operation skills, and lack of high bandwidth connectivity to transfer the high number of large bandwidth files created by drones and their higher resolution sensors.  While this project has completed, the opportunity of developing Arctic crowdsourced drone data will continue to be developed as numbers of drone operators in the Arctic increase, and further engagement and feedback are received from Arctic communities.
Big EO Data Analytics
EO data allows us to gather massive global information about our planet Earth’s physical, chemical and biological systems via satellites carrying remote sensing devices.


When large amounts of data are concerned, such as those captured by [...]
SPACETEC PARTNERS SPRL (BE)AI4EOagriculture, AI4EO, analytics, crops and yields, platforms EO data allows us to gather massive global information about our planet Earth’s physical, chemical and biological systems via satellites carrying remote sensing devices. When large amounts of data are concerned, such as those captured by remote sensing devices on satellites used in EO, our computers and AI algorithms can be used to help us solve problems. They can learn to recognise patterns and find correlations that humans would otherwise miss. The goal of Big EO data analytics is to bring the worlds of AI and EO closer together through a series of challenges based on societal problems that can be solved by combining AI and EO, stimulating and fostering interaction and collaboration. The initiative targets customers worldwide, with a specific focus on the data science and AI communities. Our customers can be potential challenge participants as well as companies, startups and other entities aiming to launch their challenges in the AI4EO platform.  Potential participants can be researchers, students, coders or any other parts interested in combining AI tools and EO data to solve the proposed problems. We are organizing several artificial intelligence-based challenges with world-class partners and sponsors, and our team manages the platform where the challenges are hosted, the overall organization of the challenges and related events, the interaction with contestants and the marketing campaigns.
Bringing the power of AI to Sentinel Hub Sentinel Hub is one of the most commonly used services for satellite imagery processing, powering hundreds of data scientists worldwide, who jointly process more than 12 billion km2 of Sentinel, Landsat, MODIS and commercial satellite images [...]SINERGISE LTD. (SI)Digital Platform Servicesartificial intelligence, platformsSentinel Hub is one of the most commonly used services for satellite imagery processing, powering hundreds of data scientists worldwide, who jointly process more than 12 billion km2 of Sentinel, Landsat, MODIS and commercial satellite images every single month – an equivalent of 80-times the total surface area of the Earth. During the project, we will upgrade Sentinel Hub to provide even more value in AI procedures by allowing users to deploy more powerful custom scripts and scale up the level of processing. This should speed up the development of the new ML model and make it much easier to integrate in the 3rd party systems – ML developers will not need to set-up all the elements of the operational system (resource management and scheduling, monitoring, error handling, billing, etc.) – they will simply upload their model in the Sentinel Hub and expose it via existing services and standard interfaces.
Building trust in digital economy While IPR protection will have to rely mainly on contractual mechanisms, technology is increasingly offering means to enforce IPR protection via technical solutions. The study was to identify the approaches that are ready for operational use and [...]ARGANS LIMITED (GB)Digital Platform Servicesblockchain, platformsWhile IPR protection will have to rely mainly on contractual mechanisms, technology is increasingly offering means to enforce IPR protection via technical solutions. The study was to identify the approaches that are ready for operational use and can be implemented as part of the common architecture.  The implementation strategy defined aftr user consultation entailed development of the IPR traceability services using the Merkel tree hash-functions which are the underlying the cryptographic element of the blockchain data structures. This approach has been independently validated by the Nov. 2020 announcement of the European Commission Action Plan for Intellectual Property Right Protection which is addressing the impact of new technologies (such as AI and blockchain) on the IP system. The underlying ambition of the European Commission is to create a ground breaking unitary system for Patent and IP recognition and dramatically increase the IP registration by SMEs using blockchcain-driven services to be offered by the EU Intellectual Property Office (EU IPO). A liaison with the EU Intellectual Property Office (IPO) has been established and EU IPO  demonstrated own blockchain-based IP infrastructure being developed for all European IPOs. There are multiple other initatives at the EU IPO that will drive the digitisation and innovation agenda and it was agreed that multiple checkpoints will continue to enhance the cooperation opportunity and for ESA  to represent the EO sector IP perspectives to the EU IPO stakeholders. The project has demonstrated blockchain-based IP protection/registration/traceability services deployed on the ESA Coastal TEP. The video demonstration of the Proof-of-Concept is available at https://www.youtube.com/playlist?list=PLNePkHV3wXsrgHMrChF-Ws1FLGMoub-d9
Business Model Validation for Exploitation Platforms This activity validated the specific business model of the EODC initiative - hyprid use of public infrastructure for public R&D and commercial use - for its possible reuse in the context of the Exploitation Platform programmatic activities.EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT)Digital Platform ServicesplatformsThis activity validated the specific business model of the EODC initiative – hyprid use of public infrastructure for public R&D and commercial use – for its possible reuse in the context of the Exploitation Platform programmatic activities.
Cloudfree Mosaic Platform Pathfinder This activity shall demonstrate platform efficiency in generatong a worldwide cloudfree Sentinel-2 mosaic at full resolutionEOX IT SERVICES GMBH (AT)Digital Platform ServicesplatformsThis activity shall demonstrate platform efficiency in generatong a worldwide cloudfree Sentinel-2 mosaic at full resolution
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 Servicesapplications, coastal zone, platformsThrough the provision of access to large volumes of EO and in-situ data, computing resources, algorithm development space and the fundamental processing software required to extract temporal and spatial information from Big Data, C-TEP provides a dedicated service for the observation and monitoring of our coastal environment and society. Integration of satellite EO data, in-situ sensor data and model predictions shall provide an effective means of analysing and understanding the many linked coastal processes across a wide range of space and time scales.
Commercial Operator Identity Hub (COIH): Identity as a Service for the Network of EO Resources In the context of Space 4.0 and its “EO Innovation Europe” concept, the European Space Agency (ESA) is forming a new ecosystem for exploitation of EO data under the name “Network of EO Resources”. The main goal is to bring the numerous and [...]DEIMOS SPACE S.L.U (ES)Digital Platform ServicesplatformsIn the context of Space 4.0 and its “EO Innovation Europe” concept, the European Space Agency (ESA) is forming a new ecosystem for exploitation of EO data under the name “Network of EO Resources”. The main goal is to bring the numerous and largely disparate EO datasets into a federated layer of exploitation platforms and enable the End-Users to perform research directly where the data is stored. Thus, the current paradigm “bring the data to the user” (users having to download enormous datasets to their premises and own massive infrastructures to process that data) will be replaced with the “bring the user to the data” paradigm, as the exploitation platforms will not only provide the raw data, but also a computing framework with specific tools and algorithms relevant to Earth Sciences. Federated Authentication and Authorization Infrastructure (AAI) is one of the key building blocks of this new ecosystem, aimed at providing a Single Sign On (SSO) experience for the users of the Network of EO Resources. In this context, the Agency has run several Pathfinder activities with the aim to align the Federation approaches among the various players in the Earth Observation domain and ensure these approaches are in-line with the AARC Blueprint Architecture and the technical practises in EduGain. To ensure the most cohesive operation of the Network of EO Resources, a centralised “IDaaS” (Identity as a Service) has been identified as the most suitable Identity and Access Management model, which is the subject of this service contract. The European Association of Remote Sensing Companies (EARSC) has been chosen by ESA to act as the Data Controller and Statutory Body for governing the IDaaS services resulting from this contract. The operational context of these services is a pure Business to Business (B2B) environment with no general public involved. The actors of this B2B environment are EARSC and the COIH service provider on one side, and commercial companies involved in the Earth Observation business on the other side.
COMMUNITY EARTH OBSERVATION INTELLIGENCE SERVICE: PROTOTYPING FOR SCALE At present NGOs/CSOs have limited expertise in accessing and utilizing EO data. This project is working with NGOs adressinghuman rights concerns and will develop methodologies for integrating in-situ (citizen data collection), drone and EO data [...]OMANOS ANALYTICS (GB)Digital Platform Servicespermanently open call, platforms, sustainable developmentAt present NGOs/CSOs have limited expertise in accessing and utilizing EO data. This project is working with NGOs adressinghuman rights concerns and will develop methodologies for integrating in-situ (citizen data collection), drone and EO data to enhance the collection of information and evidence on activities affecting human rights in developing countries
CTEO – CryptoTradeable EO EO derived information are increasingly being used as the basis for a range of sensitive decisions linked to commercial operations, public safety and environmental security. At the same time, developments in ICT capability enable an expanded [...]Planetek Italia (IT)Enterpriseblockchain, permanently open call, platforms, securityEO derived information are increasingly being used as the basis for a range of sensitive decisions linked to commercial operations, public safety and environmental security. At the same time, developments in ICT capability enable an expanded volume of information to be generated using distributed approaches such as cloud based storage and processing and platform based interactions, use of algorithms and proprietary datasets. This makes guaranteeing the integrity of both the data and the derived information more and more difficult. This project is testing various Blockchain based approaches to support the different verification elements needed to guarantee the integrity of the data and the analysis. In particular, this project is investigating and testing approaches for dividing, encrypting and distributing large datasets (typical EO imagery) to a group of peers (e.g. in the ground segment and on-board) for enabling tradeable distributed processing, encrypting and distributing metadata in the peer-to-peer network, with guarantee of correct association to the related datasets, signing and uniquely identifying smart contracts (this may be also full-fledged algorithms) based on their input requirements and output products so that the P2P network can guarantee processing traceability and security and implementing a runtime environment suitable for running EO smart contracts, which is able to perform processing with specific execution time constraints, storage constraints, device usage constraints, network usage constraints, metrics constraints applied to output quality.
Datacube Demonstration for TPM The service enables advanced data access and retrieval capabilities on global to local / low to very high resolution EO products, based on OGC WCS and WCPS APIs. The project implements a showcase for Landsat European coverage and validating he [...]MEEO S.R.L. (IT)Digital Platform ServicesplatformsThe service enables advanced data access and retrieval capabilities on global to local / low to very high resolution EO products, based on OGC WCS and WCPS APIs. The project implements a showcase for Landsat European coverage and validating he benefit via an Urban application over Eastern Austria.
DYNAMOS – Dynamic Mosaic Service DYNAMOS is being implemented as a cloud-based, dynamic mosaicking service, initially focussing on Sentinel-2 data. The service will provide users the ability to request the creation of large area mosaics according to their requirements, [...]SPACEMETRIC AB (SE)Digital Platform Servicesgeneric platform service, permanently open call, platforms, Sentinel-2DYNAMOS is being implemented as a cloud-based, dynamic mosaicking service, initially focussing on Sentinel-2 data. The service will provide users the ability to request the creation of large area mosaics according to their requirements, primarily in terms of area and time frames, image selection and prioritisation considerations. DYNAMOS is building on the concept of dynamic mosaic creation. Here “mosaic recipes” capture the required data details and processing steps for the on-demand creation of the mosaic. This also allows actual processing operations to only occur for areas directly demanded e.g. for visualisation or storing only the virtual recipe rather than a large dataset. The DYNAMOS activity is driven by a set of use cases in the agriculture and forestry application areas. The service is currently being designed for and deployed in AWS.
E-COMMERCE PLATFORM FOR MICRO-GEOSERVICES (Store4EO) Innovative approaches to distribute services to both public and private markets, being more automated and interoperable, are expected to support EO companies in getting the best return on investment.Micro geo-services based on the use of [...]Deimos Engenharia (PT)Digital Platform Servicesgeneric platform service, platformsInnovative approaches to distribute services to both public and private markets, being more automated and interoperable, are expected to support EO companies in getting the best return on investment. Micro geo-services based on the use of satellite data, delivering very focused earth measurements (e.g. burnt area map/index, NDVI, land use, etc..), address potentially a wide audience, available to pay only a small amount, typically ordering products for a few tens of Euros, for their geo-temporal area ofinterest. Given the rather limited revenue margin, it is essential that scalable data storage and processing environments (e.g. on the cloud), but also e-commerce platform capabilities can be shared across value adding providers. In particular, the EO value adding sector is characterised by a high number of small and specialized companies operating in specific application domains; building the complete vertical stack by themselves. While they excel in their core business, they may lack IT competences and/or resources to publish and market their information extraction algorithms via modern on-line platforms. The purpose of this project is aimed then at simplifying and automating overall ICT deployment and commercial exploitation of micro geo-services from the Earth Observation sector. Through an online e-commerce platform (Store4EO) enabling advanced capabilities for publishing, ordering, delivery, accounting and billing, the elapsed time between service demand and service output shall be shortened, avoiding repetitive ICT tasks non related to EO value adder core activities, with an overall efficiency improvement and cost reduction. These micro geo services will be deployed and processed at remote cloud infrastructure (e.g DIAS) and will be executed on demand and scheduled for execution (e.g subscription based) . The Store4EO platform will matchmake EO value adders the customers of EO services by providing the capability to commercialise their processing algorithm. The will be able to order these services and integrate in their decision making process or even to chain a set of micro geo services to create a work a complex workflow.The Store4EO eCommerce service aims to close the gap between the vast number of EO services available in the EO sector and discoverability of these services to the end users. Store4EO will then foster:   B2B commerce where other value adders could also build high-value added services from further concatenation of micro services (e.g. through APIs and workflows)B2G benefitting from trusted and ready-to-use micro services easy to integrate in their processes B2G benefitting from trusted and ready-to-use micro services easy to integrate in their processes B2C commerce where users likely make heavy usage of mobile devices in their daily life A validated pre-operational platform within 4 months of the project. This first version of the pre-operational platform will be ready for the services providers to register and publish their services for the end users. A business model will be defined. It will incorporate the price model, the subscription schemes , the revenue sharing model with the EO services providers , the envisioned cost structure etc.In terms of high level functionality, the Store4EO service will offer interfaces for the service providers to register and deploy their services in the platform. The platform will provide a user interface for the end users to browse through the service catalogue and select the service they prefer. The catalogue will contain all the necessary information to assist the purchasing decision making process of the end user. The end users will be able to order the service after successfully payment. The users will also be view the status of the orders and receive notification when the product is ready for delivery. The end users will have the option to get the output data from the platform or via API.
Earth Observation for Alpine ecosystems ‘eco4alps’ – Alps regional initiative The project is an Application element of EO4ALPS Regional Initiative. It will develop 6 EO services on ecosystem mapping and monitoring in the alpine region, addressing the specific requirements of national and regional stakeholders and being [...]Solenix Schweiz GmbH (CH)Regional InitiativesAlps, ecosystems/vegetation, forestry, platforms, regional initiativesThe project is an Application element of EO4ALPS Regional Initiative. It will develop 6 EO services on ecosystem mapping and monitoring in the alpine region, addressing the specific requirements of national and regional stakeholders and being sufficiently large in scope and content to strengthen regional cooperation across alpine countries: ecosystem mapping, forest disturbance, forest phenology, forest fire recovery, grassland management and grassland abandonment. A 2nd objective of the project is to demonstrate the added value of an open and federated network of platforms to provide these services at regional scale. A proof of concept on a transboundary area of 50,000 km2 will demonstrate the adequacy and usefulness of the proposed services.   Discover more projects, activities and resources on the Alps regional initiative (EO4ALPS) page.  
Earth Observing Dashboard A Tri-Agency Dashboard by NASA, ESA, JAXA
International collaboration among space agencies is central to the success of satellite Earth observations and data analysis. These partnerships foster more comprehensive measurements, robust datasets, [...]
NASA, JAXA and ESA (IT)Digital Platform Servicescovid19, platforms, scienceA Tri-Agency Dashboard by NASA, ESA, JAXA International collaboration among space agencies is central to the success of satellite Earth observations and data analysis. These partnerships foster more comprehensive measurements, robust datasets, and cost-effective missions.   The tri-agency COVID-19 Dashboard is a concerted effort between the European Space Agency (ESA), Japan Aerospace Exploration Agency (JAXA), and National Aeronautics and Space Administration (NASA). The dashboard combines the resources, technical knowledge and expertise of the three partner agencies to strengthen our global understanding of the environmental and economic effects of the COVID-19 pandemic. Use the dashboard to explore environmental and economic indicators based on remote sensing data from ESA, JAXA and NASA, and investigate how social distancing measures and regional shelter-in-place guidelines have affected Earth’s air, land, and water. Explore individual countries and regions across the world to see how the indicators in each specific location have changed over time. EO Dashboard Hackathon From June 23- 29, coders, scientists, entrepreneurs, designers, storytellers, makers, builders, artists, technologists, and space enthusiasts from around the world joined NASA (National Aeronautics and Space Administration), ESA (European Space Agency), and JAXA (Japan Aerospace Exploration Agency) for the all-virtual, global Earth Observation Dashboard Hackathon. Go to the hackathon webpage. 
Earth System Data Lab (ESDL) The main objective of the Earth System Data Lab (ESDL) project is to establish and operate a service to the scientific community that greatly facilitates access and exploitation of the multivariate data set in the ESDL and by this means advances [...]BROCKMANN CONSULT GMBH (DE)Scienceland, marine environment, oceans, platforms, scienceThe main objective of the Earth System Data Lab (ESDL) project is to establish and operate a service to the scientific community that greatly facilitates access and exploitation of the multivariate data set in the ESDL and by this means advances the understanding of the interactions between the ocean-land-atmosphere system and society. To this end, the main tasks of the project fall into four main categories: infrastructure and operations, data sets and tools, use cases and scientific exploitation, and communication and outreach. The core part of the ESDL is the data in analysis-ready form, together with tools and methods to generate, access, and exploit the ESDL. The software to generate the ESDL and the data access APIs have been developed in the preceding project CAB-LAB. The modular open source approach adopted in CAB-LAB has proven to be convenient, flexible, and powerful and effectively meets user requirements. ESDL further evolves the range of available tools according to the requirements formulated by the different user groups of the service, while users may also contribute their own solutions and share them with others on github. The project continuously extends the datasets included in the ESDL. The additions imply both extending the data coverage in time as well as the introduction of completely new data sets.  Examples for specific requirements include marine parameters and the missing parameters from ESA’s CCI programme, e.g. Land Cover, Clouds, Aerosols, and Green House Gases. As for the software part, the main objective for these additions is to increase the ESDL’s utility and versatility and thus ultimately the uptake of scientific users, who will then have a powerful tool to advance our understanding of the Earth system dynamics. User uptake and scientific exploitation through the implementation of use cases is actively promoted by several tasks. The project adopts a three-stage approach and accordingly defines three different user types, Champion Users (CU, pre-defined use cases), Early Adopters (EA, Open call), and the Scientific Community (SC, free use). All ESDL users have in common that they are using the ESDL for scientific exploitation. While doing so, they are helping to improve the ESDL and the service provided, to increase the awareness for this activity and the offered service, and to extend the ESDL by contributing own source code and data sets. The ESDL is complemented by extensive outreach, communication, and training activites, which will foster user uptake, empower users to optimally exploit the ESDL, and eventually yield tangible scientific results in the form of peer-reviewed articles in international journals. Champion Use Cases: Four Champion use cases will be implemented in collaboration with distinguished experts  to demonstrate the wide range of different approaches that may be adopted with the ESDL: EM-DAT: Environmental conditions during societal catastrophes GEO-BON Colombia: Supporting regional initiatives in Colombia towards an Ecological Observation System Marine NPP: Primary productivity models in the ocean MDI: Biogeochemical Model Optimization Results: The Data Lab is accessible via registration https://www.earthsystemdatalab.net/index.php/interact/data-lab/ User Guide and Source code for Python and Julia https://www.earthsystemdatalab.net/index.php/documentation/user-guide/ The Earth System Data Lab is available on the Euro Data Cube https://eurodatacube.com/
EARTH-CODE: EARTH SCIENCE COLLABORATIVE OPEN DEVELOPMENT ENVIRONMENT EarthCODE (Earth Science Collaborative Open Development Environment) has the objective to: enable adoption of FAIR Open Science Principles throughout ESA-funded Earth System Science activities, to deliver long-term persistence of data, [...]TELESPAZIO VEGA UK LIMITED (GB)Scienceopen science, platforms, science hubEarthCODE (Earth Science Collaborative Open Development Environment) has the objective to: enable adoption of FAIR Open Science Principles throughout ESA-funded Earth System Science activities, to deliver long-term persistence of data, code and documentation, aiding reproducibility, reuse and consumption of research outputs by a wider community. EarthCODE brings existing pieces together in a single, open-access solution for ESA scientific activities, offering an Open access cloud-based development environment leveraging on federated EO platforms, with: Scalable computing, tools for FAIR management of open data, open-source code, documentation Guidelines, community management, and support to use the tools and apply the principles in practice, including for activities that use own institutional computing resources Persistent storage, cataloguing and discovery services for the activities’ research outputs EarthCODE is being developed incrementally, with subcontractors being selected via annual Best Practice procurements. These Best Practice procurements will address three main Work Streams: Infrastructure and Services – looking to integrate cloud computing services from EO Platforms with the EarthCODE Portal.  FAIR Open Science – looking to integrate tools for the management of Open Data and Open Source Software Community – looking to manage and develop the community of scientists contributing to and using EarthCODE Community manager for EarthCODE: Alasdair Kyle <Alasdair.Kyle@telespazio.com>
Ease QC – Development of a Service to detect anomalies in Earth Observation data using AI (Artificial Intelligence) models The EASEQC project aimed at expanding the use of AI/ML for quality control of EO products. The traditional approach to quality control, usually involving deterministic models together with considerable manual intervention, is no longer feasible [...]TELESPAZIO VEGA UK LIMITED (GB)Digital Platform Servicesartificial intelligence, generic platform service, permanently open call, platformsThe EASEQC project aimed at expanding the use of AI/ML for quality control of EO products. The traditional approach to quality control, usually involving deterministic models together with considerable manual intervention, is no longer feasible given increasing data volumes of EO data archives. ML/AI has potential to make the process of quality control more efficient. EASEQC focused on the development of semi-supervised ML models for detection anomalies in EO products. This entailed that models can be trained with limited training data and that a model is capable of identifying generally anomalous data products i.e. different anomalies can be detected by the same model. The service has been implemented in a cloud environment and is accessible via an API. Overall, the outcome of the project has seen significant steps made towards the establishment of an operational Ease QC service. Further work is still required to improve the ML models, but the infrastructure successfully developed by the project both with respect to the development of the ML models, and their deployment / operation alongside the data (be that on the cloud or otherwise) is an extremely significant development with respect to the long term objectives of the Ease QC team.
Education Platform This activity has produced a data cube based browser for educational purposes.SINERGISE LTD. (SI)Digital Platform Servicesplatforms, training and educationThis activity has produced a data cube based browser for educational purposes.
EO BALTIC PLATFORM FOR GOVERNMENTAL SERVICES (EO-BALP) The goal of the EO-BALP project is to develop a cloud service platform for Earth Observation (EO) data access and processing and provide six different applications that will demonstrate the practical use of satellite data in different [...]Baltic Satellite Service (LV)Enterpriseagriculture, Baltic, clouds, coastal processes, human settlements, natural hazards and disaster risk, platforms, water qualityThe goal of the EO-BALP project is to develop a cloud service platform for Earth Observation (EO) data access and processing and provide six different applications that will demonstrate the practical use of satellite data in different domains: Monitoring application of infrastructure and settlements with more than 60,000 inhabitants, which will help to detect and characterize ground movements from satellite data, and to identify dangerous places in infrastructure protection zones; A water quality monitoring application that will help determine water quality and pollution, as well as pollution sources in the Baltic Sea, coastal waters and inland waters; A forest change monitoring application, which will help to regularly detect clear-cuts and wind falls, as well as forest damage caused by diseases, pests, fires, water, etc.) and will provide the latest satellite data mosaic service in all Baltic countries; An agricultural land monitoring application that will help to assess crops, yield, soil quality, generate burnt area map delineating agricultural lands affected by grassland fires and flooded agriculture field areas. Natural resource extraction monitoring application that will help identify illegal resource extraction sites (sand, gravel, etc. mineral resources); A maritime monitoring application that will help identify ships, their type, location and movement. To achieve the technical goals, the initial phase of the project will gather business and functionality requirements from potential end users of the platform, who will also be involved in testing and validating the applications. Currently, various organizations from all Baltic countries have shown their interest in the project and in the possibility of using satellite data, such as the cities of Tallinn and Riga, the Environmental Protection Agency under Ministry of Environment of Lithuania, the Klaipeda State Seaport Authority, the Latvian State Forest Service, the Latvian Peat Association, the Latvian Institute of Aquatic Ecology and many others. The new EO-BALP platform is planned to be designed in such a way that it can be easily used by users without specific knowledge and also by professionals in the field. The EO platform will enable all participating stakeholders in the three Baltic countries to deploy, operate and deliver EO-based services to national governments and institutions. The platform will therefore support activities allowing users to discover and select data, pre-existing processing services, EO based services, products and applications, visualize and analyze them or select and apply data manipulation tools to the result. The Platform will also allow users to discover and select data samples and software components, upload and validate applications and deploy them on the platform for use also by other users. Users will be able to authenticate, upload and deploy a new application software, discover and select data, process the data and eventually publish the resulting product. In addition, the interoperability of EO Platform with existing e-government platforms will be ensured, by: importing existing geospatial data from governmental and other public/private entities to the platform to be used for provision of specialised services; developing functionality allowing to integrate XYZ/TMS, WMS web services and JSON/GeoJSON data from governmental and other public/private entities directly into specialised service web applications; publishing all geographic data produced by specialised applications based on standard and widely used web service formats (XYZ/TMS, WMS, GeoJSON) which allow using them by governmental and other public/private entities in their own web applications and in desktop GIS software (QGIS, ArcGIS, etc).  
EO Innovation Platform Testbed Poland The project has validate procurement mechanisms for a cloud-based resource tier, offering bundled infrastructure (IaaS) and data services (DaaS) to the users, based at minimum on MERIS full resolution, S-2 and Landsat data, possibly extending to [...]CREOTECH INSTRUMENTS SA (PL)Digital Platform ServicesplatformsThe project has validate procurement mechanisms for a cloud-based resource tier, offering bundled infrastructure (IaaS) and data services (DaaS) to the users, based at minimum on MERIS full resolution, S-2 and Landsat data, possibly extending to S-1 and S-3 data.
EO Law – EO derived information in support of Law Enforcement derived information in support of Law Enforcement The EO Law project aims at demonstrating the benefits of using EO based information together with state of the art ICT data analytics and non-EO data fusion in support of Law Enforcement in various domains, from environment to terrorism, and [...]GMVIS SKYSOFT S.A. (PT)Enterpriseplatforms, securityThe EO Law project aims at demonstrating the benefits of using EO based information together with state of the art ICT data analytics and non-EO data fusion in support of Law Enforcement in various domains, from environment to terrorism, and counter proliferation. For this purpose the consortium that will develop the EO Law has engaged relevant users and stakeholders that work in the domains covered in the project, providing context and related requirements to support the definition of service specifications, in order to develop capabilities that can really tackle operational problems of the various areas in support of law enforcing. The domains and services that will be approached in the project are the following: Environmental Crimes -Illegal Logging. In the last few years, illegal logging has emerged as a serious worldwide concern in the forest sector. By its nature of being illegal it is also clandestine, making it difficult to estimate with precision how much wood is logged illegally, where exactly, and by whom. What is known though, is that illegal logging remains a very big problem despite existing efforts to fight it. In this context, the consortium will develop services that can help on the investigation and mitigation of the consequences that result from the illegal logging activities, namely: Detection of routes for movement of timber Detection of forest change Detection of logging support infrastructure   Crimes against humanity – As crimes against humanity are still occurring on a regular basis, there are in contrary often not “visible” to the wider public. This is based mainly on the fact that hostile actions are taken place most of the times in remote and less-accessible areas, where accessibility is limited either due to e.g. armed conflicts or wars, or due to governmental restrictions. As the amount of in-sight information rapidly increased during the last years due to e.g. social media, the confidence level of the information overload was decreasing making it harder to distinguish between “wrong” or “right”. EO-data and EO-derived information can be seen as an independent information source suitable to verify on-sight information and to gain a more sound evidence of actions taken place. The services that will be provided are: Multi-criteria mass grave site suitability model Fire detection in settlements Settlement development & change detection   Terrorism and organized crime – Societies today constantly face terrorist and organize crime actions, which require new methods for modelling and analysis, inherited from various sectors and technological domains. Law enforcement organizations, analysts and field operators fighting terrorism and organized crime need front-line integrated technologies to support their cooperative work. The goal of the services will be spatially depict the activities of different terrorist organizations by means of generalized locations, anomaly characterization/interpretation and also activity analysis. Preparing helpful and applicable/realistic services requires the fusion of multi-source data combining unstructured (descriptive and informational data sources) and structured geospatial data (vector and satellite data) as well as information from open source and public databases like social media networks, crowdsource information etc. The services that will be provided are: Comprehensive and contextual imagery intelligence analysis combing EO data and media sources Hotspot detection layer with potential training camps Hotspot detection layer with potential abnormal activities related to terrorism and organized crime   All the services will be deployed through a virtual web platform that will be used for service ordering, processing and delivery. This platform will be composed by a set of software components integrated together and implemented on a data-rich cloud infrastructure so that the EO data can be accessed online and without the need to transfer it from external sources.
EO Network of Resources The increasing size of available satellite mission data sets, together with Information Computer Technology (ICT) advances has resulted in a paradigm shift. Data do not need any more to be downloaded by the user to their local machine for [...]CLOUDEO AG (DE)Digital Platform ServicesplatformsThe increasing size of available satellite mission data sets, together with Information Computer Technology (ICT) advances has resulted in a paradigm shift. Data do not need any more to be downloaded by the user to their local machine for further processing, on the contrary it is the user who can find the data and process them in cloud environments hosted by ICT providers with expandable processing capabilities. The Network of Resources (NoR) is an ESA initiative to facilitate the use of cloud environments by users, building on and enlarging the previous Open Science for Earth Observation (OSEO) call, sponsoring R&D users for the use of commercial platform resources. The NoR call supports research, development and pre-commercial users to innovate their working practices, moving from a data download paradigm towards a bring the user to the data paradigm, considered essential for maintaining competitiveness of European data exploitation.
EO SERVICES DEMONSTRATION IN SUPPORT TO WEST AFRICA CAPACITY BUILDING PROGRAM OF THE OECD ABOUT GOLD MINING PRACTICES This collaborative tool on artisanal gold mining (ASM) and security will take the form of a secure web mapping platform. The prototype will include some layers of geographic information and various satellite images of ASM areas resulting from [...]Geo212 (FR)Enterpriseafrica, AI4EO, mapping/cartography, platforms, securityThis collaborative tool on artisanal gold mining (ASM) and security will take the form of a secure web mapping platform. The prototype will include some layers of geographic information and various satellite images of ASM areas resulting from automated detection by artificial intelligence, and will propose spatialized indicators and analytics, for example on the evolution of gold ASM sites, or the impact of gold panning on security. This preliminary one-year project for the Liptako-Gourma Authority (LGA) and its three member states (Mali, Niger and Burkina Faso) also aims to analyse the LGA’s needs for geolocalised information, to set up a roadmap for the development of the final observatory and to address the project’s governance.  This project develops an innovative perspective at different levels: The first innovation consists in testing image processing (AI and SAR coherence change detection) to identify artisanal mining in Sahelian environment The second innovation is to consider the cooperation between LGA, ministries, agencies, etc as an important success point addressed, and the involvement of anthropologists to drive this challenge is an original approach. They will introduce social skills to analyse and optimize the collaboration between actors The third innovation consists in developing statistical tools to analyse the spatial and temporal correlation between artisanal mining (legal and illegal) and violent acts. Geo212 is leading this project in association with two partners: Anthropolinks  and Pixstart.  The OECD is supporting the project, in connection with its work on due diligence for responsible mineral supply chains in conflict or high-risk areas.
EOvideo product Exploitation Platform (VANTAGE) Capturing video from Earth Observation (EO) is one of the most exciting innovations to hit the remote sensing world in recent times. High-resolution, full-colour EO video is enabling fundamental and disruptive changes for the Geospatial [...]Earth-i Ltd (GB)Digital Platform Servicesgeneric platform service, platformsCapturing video from Earth Observation (EO) is one of the most exciting innovations to hit the remote sensing world in recent times. High-resolution, full-colour EO video is enabling fundamental and disruptive changes for the Geospatial Intelligence and Earth Observation industries. EO Video provides several advantages over still imagery, for example: it enables faster and more accurate object recognition using AI and machine learning; It enables 3D models to be created to much higher precision than from a single stereo pair; It provides more contextual information to analysts and researchers, by capturing movement; It allows for more accurate change detection including detection of 3D changes over time; It provides the ability to mitigate patchy cloud and haze in a scene to derive a clear image. VANTAGE is a new, online, cloud-based platform for analysis and exploitation of video from space. The VANTAGE platform includes a repository of high-definition videos captured from Earth orbiting satellites – including data from the Earth-i Vivid-X2 satellite that was launched in 2018. Alongside this data is a suite of sophisticated analytical tools, enabling a user to extract value and insight from the videos such as derivation of 3D models, tracking of moving objects in the videos, extraction of movement vectors and building up cloud-free composite images. The VANTAGE platform also connects to complementary external data sources and enables development of commercial, scientific and public sector applications. VANTAGE enables a user to bring their own EO data as well as their own user-defined workflows and processing algorithms to be deployed and used alongside the predefined list of services and functions. VANTAGE is being developed by Earth-i and CGI under a two-year contract with the European Space Agency, which kicked off in March 2020. The project launched the first version of the platform in November 2020 and will deploy incremental releases of functionality every four months focusing on pre-defined use cases such as earthworks monitoring, deforestation and seaport analytics. The existing VANTAGE services include: Vessel Detection – an AI algorithm to detect and count vessels in satellite video. Motion Tracking – an AI algorithm to track velocity and direction of moving objects, such as aircraft and shipping vessels. Cloud-Free Compositing – an AI algorithm to composite multiple video frames segment the clouds and then removes them to create a cloud-free satellite image. Video Stabilisation – an AI algorithm to stabilise video by aligning each video frame. Frame Extraction – an algorithm to break the video down into individual images for 2D image processing. Video Generation – an algorithm to take multiple 2D images and build it back up into a video, as well as transcoding videos into different formats (e.g. H.264, H.265, MPEG and Motion JPEG). 3D Model Creation – The VANTAGE platform computes a 3D model of the satellite scene and outputs it as a Mesh, DSM and Point Cloud. 3D Volumetric Change Detection Reporting – The VANTAGE platform undertakes change detection between two pre-processed 3D models to map cut and fill regions and report on the volumetric changes detected. Additional features and algorithms will be added to the platform in future releases.
Euro Data Cube Facility The Euro Data Cube Facility (EDC) service is providing a unique service to access to a considerable amount of EO related information from instrument data up to environmental variables, including Copernicus Services.
Capitalizing on EO data [...]
SINERGISE LTD. (SI)Digital Platform ServicesplatformsThe Euro Data Cube Facility (EDC) service is providing a unique service to access to a considerable amount of EO related information from instrument data up to environmental variables, including Copernicus Services. Capitalizing on EO data offer from the cloud (e.g. DIAS), EDC avoids at maximum data replication. It offers to EO value-adders the possibility to apply their own algorithm and data transformations in a one-stop-shop Information Factory. The EDC marketplace gives also the opportunity to expose value added data and services from Third parties. Thanks to its data and processing capabilities offer in the cloud, EDC establishes a “bridge from Space to Applications”. The project also contributes to the interoperability activities in the related domain to maximize the service capabilities and foster federation of similar initiatives worldwide.
European Ecostress Hub The European Ecostress Hub is focusing on the development and implementation of the European Ecostress Hub (EEH) in support of the Copernicus High Priority Candidate Land Surface Temperature Monitoring mission (LSTM). ECOSTRESS data acquired [...]LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY (LU)Applicationsapplications, land surface, platformsThe 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. 
EXPAND DEMAND – OIL & GAS AND DISASTER RISK FINANCING & TRANSFER In recent years the need for real-time incident satellite imagery has grown within the oil and gas industry.  Following the Gulf of Mexico (Deep water Horizon) oil spill, it became clear that access to real-time satellite data, tasked within [...]CGI IT UK LIMITED (GB)Enterprisenatural hazards and disaster risk, platformsIn recent years the need for real-time incident satellite imagery has grown within the oil and gas industry.  Following the Gulf of Mexico (Deep water Horizon) oil spill, it became clear that access to real-time satellite data, tasked within hours of an incident and used to inform critical decision-making, could have far-reaching impacts for oil & gas operators in their response to oil spill incidents. However, effective use of satellite imagery to help drive response decisions faces a unique challenge in the time it takes from collecting the first image of an area of interest, to a revisit pass of the same area of interest (16 days in the case of Landsat).  This is exacerbated in locations that are closer to the equator than to the poles. The solution is therefore more access to satellites, resulting in non-reliance on a single provider to meet standard needs.  This demand for better access to mission-critical Earth Observation (EO) data has led to the ‘Expand Demand Oil and Gas’ project, created and funded by the European Space Agency (ESA). This project has been running within ESA since 2018, and has two key high-level requirements: To meet a specific operational requirement of the oil and gas industry. To establish generic EO capabilities within the oil and gas industry and showcase the capabilities of the Sentinel mission and the European EO service industry. The benefit of this project to its end-users would be a service delivering relevant near-real-time EO data.  This would be provided by a dedicated portal, where information relating to a specific spill incident is gathered and presented in a clear and systematic way.  The information provided would cover: A timeline of available products from a range of providers. Predictions of future availability of products. Actual products wherever possible Derived services such as oil spill extent mapping. To meet this challenge, the Oil and Gas Industry Earth Observation Response Portal (OGEO – ReP) has been developed.  This platform will assist oil spill responses by gathering, processing and displaying a wide range of relevant EO data, including: Satellite data products from a wide range of sources (free and commercial). Predicted acquisitions relevant to the incident. Derived products, e.g. Oil spill extent mapping, processed as a hosted service. Contextual background information, such as asset locations. The scalability of the platform allows it to process large amounts of data in a spill event, allowing for the inclusion of swath prediction (to identify potential acquisitions of interest),the mapping of a spill event, and running of oil spill drift models to forecast the behaviour of the spill.  This is all presented via an intuitive graphical user interface (G
extrAIM extrAIM (AI-enhanced uncertainty quantification of satellite-derived hydroclimatic extremes) is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, [...]National Technical University of Athens (GR)AI4EOAI4EO, AI4Science, Ecosystems, Mediterranean, platforms, scienceextrAIM (AI-enhanced uncertainty quantification of satellite-derived hydroclimatic extremes) is part of the AI4SCIENCE activity. The first AI4SCIENCE ITT was launched in 2021 and had a focus on Extreme Events, Multi-Hazards and Compound Events, and contributes to the ESA Extremes and Natural Disasters Science Cluster.  The AI4SCIENCE ITT had 2 main objectives: Advancing Earth System Science: advancing our capacity to combine EO and AI to address a major scientific challenge: The observation, understanding and characterisation of multi-hazards, compound and cascade events and its impacts on society and ecosystems. Advancing Artificial Intelligence for EO: unlocking the full potential of Artificial Intelligence for Earth System Science with focus on two main AI challenges: physics-driven Artificial Intelligence and explainable AI. extrAIM will develop a first-of-its-kind, satellite-based, low-latency, uncertainty-aware precipitation dataset for the Mediterranean region, adjusted to account for the extremes’ probabilistic behavior. extrAIM will combine statistical learning and Bayesian modelling methods (for uncertainty quantification) with an AI (Artificial Intelligence)-enhanced dataset integration approach, suitable for combining multiple precipitation products (e.g., satellite-data, estimates based on soil moisture), with an eye on model’s explainability. Finally, and with improving understanding and awareness in mind, extrAIM will develop a user-friendly data-management and visualization platform able to provide easy access to the UA Mediterranean dataset, as well as communicate risks arising from individual and compound extreme events. In more detail, extrAIM project’s specific objectives are:  1.  The development of an AI-enhanced, yet explainable and operational approach capable of optimally combining multiple SPPs into a single, and improved integrated SPP.  2.   The development of a general probabilistic framework for the uncertainty modelling and quantification of the quantitative precipitation estimates obtained by SPPs (with a focus on extremes).  3.     The creation of a first-of-its-kind UA satellite-based precipitation dataset for the Mediterranean region. 4.    The development of a user-friendly data analysis and visualization platform, which will enable easy data retrieval and visualization, aiming to increase understanding and awareness against hydroclimatic risks arising from individual and compound extreme events. The project results and publications will be made available at the project website: https://extraim.eu/en/     
Federated Identity Management Pathfinders Several different activities to explore the notion of having Federated Identities for EO Exploitation, allowing a user to access services using its home organisation account, e.g. university account being used to access a DLR service or an ATOS [...]CGI IT UK LIMITED (GB)Digital Platform ServicesplatformsSeveral different activities to explore the notion of having Federated Identities for EO Exploitation, allowing a user to access services using its home organisation account, e.g. university account being used to access a DLR service or an ATOS Commercial service.
Flexible ONBoard Data Analysis The amount of data coming from imaging sensors increases steadily and a modern imaging sensor creates frames of several megapixels at a high frame acquisition rate. These imaging sensors with their large data output are mounted on spaceborne [...]Science [&] Technology Norway (NO)Enterprisepermanently open call, platformsThe amount of data coming from imaging sensors increases steadily and a modern imaging sensor creates frames of several megapixels at a high frame acquisition rate. These imaging sensors with their large data output are mounted on spaceborne platforms, but the downlink capability of these spaceborne platforms, especially for small platforms, has not been increasing at the same rate as the data generation of the imaging sensors. This has resulted in a ‘big data problem’ on board these spaceborne platforms. An industry trend towards smaller satellites – with smaller antennas, less power and worse pointing accuracy- leads to an expectation that the downlink capability will remain well below the data generation capability for such imaging satellites. In order to use more acquisitions and have a high ‘usability’ of the satellite, the on-board processing of payload data is a solution. In this project, S&T will determine and test the technology platform that is best suited for onboard intelligent processing of imaging payload data. This will include testing techniques such as development of low volume data products instead of raw image files for downlink, verifying using concrete algorithms and implementation choices how performant such processing can be, exploring the implications of moving certain parts of the processing functionality to FPGA and conducting tests using HyperSpectral imagery on a cubesat.
Food Security Thematic Exploitation Platform The project successfully developed a Thematic Exploitation Platform (TEP) dedicated to Food Security in order to support sustainable agriculture, aquaculture and fisheries by providing access to data, processing tools and computing resources in [...]VISTA GEOWISSENSCHAFTLICHE FERNERKUNDUNG GMBH (DE)Digital Platform ServicesplatformsThe project successfully developed a Thematic Exploitation Platform (TEP) dedicated to Food Security in order to support sustainable agriculture, aquaculture and fisheries by providing access to data, processing tools and computing resources in a cloud environment. It  facilitates collaborative research and benchmarking of methods, development of innovative Apps and services, as well as uptake of EO data in processes of end-users in the above-mentioned sectors.
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)Applicationsapplications, carbon cycle, forestry, generic platform service, platformsInformation 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 Servicesapplications, forestry, platformsThe 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.
GAME.EO Recent years have brought tremendous advancements in the area of automated information extraction from Earth Observation (EO) imagery, but problems still remain since even state-of-the-art algorithms based on imagery alone do not provide a [...]GISAT S.R.O. (CZ)AI4EOpermanently open call, platforms, sustainable developmentRecent years have brought tremendous advancements in the area of automated information extraction from Earth Observation (EO) imagery, but problems still remain since even state-of-the-art algorithms based on imagery alone do not provide a satisfactory solution. In these situations, it is possible to exploit the crowdsourcing of human intelligence, which is a recent promising area for EO. This is of particular interest with respect to providing information on devleoping countries to International Finance Institutions such as the World Bank.In this project an integrated (hybrid) crowdsourced and EO data-based information extraction framework is being developed. Mobile-based tools for supporting crowdsourcing campaigns and gaming approaches will be developed, and then used to mobilize and train volunteers to provide data via dedicated EO-based workflows to extract the required information in a more timely and accurate manner, with lower costs than would be incurred using professional datacollection services. The approach will be demonstrated using specific service cases for EO-based monitoring of Informal Settlements/Slum Areas (SDG11), with the aim to enhance current machine-learning algorithms for the identification, delineation and further characterization of these areas. The developed framework and tools will be tested in cooperation with World Bank users and stakeholders (GWASP/GSURRP) in an ongoing internal project1 for Dhaka, Bangladesh, to demonstrate the potential and the added value of the synergies of crowdsourcing- and EO-based information to support the World Bank’s research and operational activities.
GammaCloud: Feasiblity of using S1 Terrain Flattened Gamma_0 backscatter across EO platforms The project prototyped a prototype of a processing workflow for improved Sentinel-1 backscatter data, providing a temporal stack of analysis ready data (ARD) that can be integrated into a data cube system allowing to access the data in a spatial [...]EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT)Digital Platform Servicespermanently open call, platforms, Sentinel-1The project prototyped a prototype of a processing workflow for improved Sentinel-1 backscatter data, providing a temporal stack of analysis ready data (ARD) that can be integrated into a data cube system allowing to access the data in a spatial and temporal domain.
Geohazards Thematic Exploitation Platform The Geohazards Exploitation Platform or GEP supports the exploitation of satellite EO for geohazards. In particular it is a contribution to the CEOS WG Disasters to support its Seismic Hazards Pilot and terrain deformation applications of its [...]TERRADUE SRL (IT)Digital Platform ServicesplatformsThe Geohazards Exploitation Platform or GEP supports the exploitation of satellite EO for geohazards. In particular it is a contribution to the CEOS WG Disasters to support its Seismic Hazards Pilot and terrain deformation applications of its Volcano Pilot. The geohazards platform is sourced with elements – data, tools, and processing including INSAR – relevant to the Geohazards theme and related exploitation scenarios.
Geopedia Pay-Per-Use Demonstration on Optical High-Resolution Cloud Platform The project enabled the Sentinel-Hub functions for MERIS, ESA Landsat, validating procurement mechanisms for a cloud-based resource tier sharing also Sentinel data.Centre of Excellence for Space Sciences and Technologies (SPACE-SI) (SI)Digital Platform ServicesplatformsThe project enabled the Sentinel-Hub functions for MERIS, ESA Landsat, validating procurement mechanisms for a cloud-based resource tier sharing also Sentinel data.
Harmonised Landsat-8 and Sentinel-2 Analysis-Ready Products The project developed a prototype service providing analysis-ready harmonized Landsat-8 and Sentinel-2 data/products to the user for easy exploitation. The service will be embedded as a SNAP “plug in”, aiming to be available in the Copernicus [...]TELESPAZIO VEGA UK LIMITED (GB)Digital Platform Servicespermanently open call, platformsThe project developed a prototype service providing analysis-ready harmonized Landsat-8 and Sentinel-2 data/products to the user for easy exploitation. The service will be embedded as a SNAP “plug in”, aiming to be available in the Copernicus Data and Information Access System (DIAS).
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 Servicesapplications, platforms, water resourcesThe 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.
Integrating AI/ML Capabilities for Geohazards and Urban Management Applications The primary objective of this project is to augment the capabilities of Ellip-powered Exploitation platforms, specifically Geohazards Exploitation Platform (GEP) and Urban Thematic Exploitation Platform (U-TEP), by seamlessly integrating an [...]TERRADUE SRL (IT)Digital Platform ServicesAI4EO, analytics, platforms, thematic exploitation platformThe primary objective of this project is to augment the capabilities of Ellip-powered Exploitation platforms, specifically Geohazards Exploitation Platform (GEP) and Urban Thematic Exploitation Platform (U-TEP), by seamlessly integrating an AI/ML processing framework. This comprehensive framework will encompass the entire machine learning pipeline, including data discovery, access to training data, model development and deployment. GEP and U-TEP are both platforms that are designed to support the exploitation of satellite Earth Observation (EO) data in their respective thematic areas, geohazards and urban management, catering to diverse user communities such as researchers, policymakers, and planners: GEP is designed to support the exploitation of satellite Earth Observations for geohazards, focusing on mapping hazard-prone land surfaces and monitoring terrain deformation. With more than 25 services for monitoring terrain motion and critical infrastructures, GEP has over 2950 registered users, with 350+ actively creating new content. U-TEP aims to provide end-to-end and ready-to-use solutions for a broad spectrum of users to extract unique information and indicators required for urban management and sustainability. It focuses on bridging the gap between the mass data streams and archives of various satellite missions and the information needs of users involved in urban and environmental science, planning, and policy. Both platforms offer various services, including data access, processing, analytics, and visualization, while providing tools and resources for customized applications. They leverage cloud-based infrastructure to handle large volumes of EO data efficiently and offer seamless access to their services. A critical aspect of this project will be the integration of MLOps processes into both GEP and U-TEP platforms’ service offerings. MLOps, which combines machine learning, DevOps, and data engineering practices, will facilitate seamless deployment, monitoring, and management of AI/ML models, ensuring the smooth operation of AI-driven applications on the platforms. To achieve the project’s goals, the focus will be on addressing key questions related to necessary services, interface requirements, component interactions, support for various geospatial data types, and algorithm independence. Several approaches will be considered to tackle these challenges, such as managing training data, implementing “move-the-algorithm-to-the-data” principles, emphasizing transparency and accountability, and enabling testing and deployment of ML algorithms on fully-scaled infrastructures. Upon successful completion, the project will result in the enhancement of both GEP and Urban TEP platforms and their service offerings. The addition of AI/ML capabilities will empower service providers to develop and deploy AI/ML models, ultimately improving their services and delivering added value to their customers. This enhancement will greatly benefit the GEP and Urban TEP platforms by expanding their capabilities and enabling new AI-driven applications for geohazards and urban management.
Interactive Hosted EO Processing The project demonstrated, through a proof-of-concept, that merging the concept of hosted EO data processing with GPUs (Graphics Processing Unit) and Web technologies, a solution could be created to allows users to easily exploit data in a fast [...]BRITISH ANTARCTIC SURVEY (GB)Digital Platform ServicesplatformsThe project demonstrated, through a proof-of-concept, that merging the concept of hosted EO data processing with GPUs (Graphics Processing Unit) and Web technologies, a solution could be created to allows users to easily exploit data in a fast interactive manner via a web browser. The PoC used InSAR for demonstration with very good results, the user just having to select the AoI and the algorithm and after some seconds having a InSAR output image.
Massive Open Online Course (MOOC) – EO Open Data Science The EO Open Data Science MOOC is hosted on EO-College with the title "Cubes and Clouds" https://eo-college.org/courses/cubes-and-clouds/.This course teaches the concepts of data cubes, cloud platforms, and open [...]EURAC RESEARCH – ACCADEMIA EUROPEA (IT)AI4EOAI4EO, platforms, training and education The EO Open Data Science MOOC is hosted on EO-College with the title “Cubes and Clouds” https://eo-college.org/courses/cubes-and-clouds/. This course teaches the concepts of data cubes, cloud platforms, and open science in the context of Earth Observation.   Its goal is to provide students with  practical knowledge on how to effectively use EO Platforms for Open Data Science in the cloud. At the end of the course, students will be able to develop and execute EO applications on the most commonly used cloud platforms (for EO) and to successfully apply the key principles of Openness for EO Scientific research and applications.   In particular, the course will help students to develop essential skills and knowledge in:    How to programmatically access ESA and other open data in a platform environment; Designing, developing and executing algorithms on EO cloud platforms; Scalable EO and geospatial analytics in the cloud; Open Source development practices.   The course explains the concepts of data cubes, EO cloud platforms, and open science by applying them to a typical EO workflow from data discovery, and data processing up to sharing the results in an open and FAIR (Findable, Accessible, Interoperable, Reusable) way. An engaging mixture of videos, animated content, lectures, hands-on exercises, and quizzes transmits the content.  You will learn the theoretical concepts of cloud native EO processing and have gained practical experience by conducting an end-to-end EO workflow. You will be capable of independently using cloud platforms to approach EO-related research questions and be confident in how to share research by adhering to the concepts of open science.  As proof of the acquired skills a community snow cover map is created where every participant contributes and shares his results openly and FAIR:  Cubes and Clouds: Snow Cover STAC Collection The course is now in beta-testing and will be launched in February 2024. This course is part of ESA’s Open Science activities.  @EO_OPEN_SCIENCE
Ocean Virtual Laboratory The aimof this activity is To exploit the synergy between Sentinel instruments and other mission EO datasets together with in situ measurements in complex waters and improve scientific understanding of ocean and coastal processes and impacts.The [...]OCEANDATALAB (FR)Sciencealtimeter, carbon cycle, carbon science cluster, CryoSat, oceans, platforms, Sentinel-1, Sentinel-2, Sentinel-3The aimof this activity is To exploit the synergy between Sentinel instruments and other mission EO datasets together with in situ measurements in complex waters and improve scientific understanding of ocean and coastal processes and impacts.The main objective of the project is to develop a virtual plateform to allow oceanographers to discover the existence and then to handle jointly, in a convenient, flexible and intuitive way, the various co-located EO datasets and related model/in-situ datasets over dedicated regions of interest with a different multifacet point of view. This is first demonstrated over the Agulhas region. Developed tools shall foster the emergence of new methods prototype and products making use of the complementarity between sensors to study ocean related processes. The tool shall also provide the best possible visibility on the upcoming Sentinel1/2/3 datatakes to help plan and coordinate with field campaign. The OVL is filling the gap between Space agencies data portals that distributes specific EO data and analysis software like IDL/ENVI or Matlab that are more suitable for in-depth analysis of a given dataset. A few GIS systems such as Google Earth are able to import several data layers but very little interaction with data (apart for basic layer transparency) is possible. The project scientific committee has to ensure that the developed OVL is providing significant added value and is not duplicating existing efforts in the international community. Scientists in the consortium shall ensure that OVL is built for scientists and with a large beta-tester community and response effectiveness to satisfy most needs of a rather versatile community.
OPEn platform for the Retrieval of Aerosol and CO2 from S5 (OPERA-S5) The aim of the OPEn platform for the Retrieval of Aerosol and CO2 from S5 (OPERA-S5) project is to develop a totally modular open scientific platform for the combined retrieval of CO2, CH4, aerosol and surface properties based on GRASP [...]GRASP-SAS (FR)ScienceAerosols, air quality, atmosphere, atmosphere science cluster, platforms, Sentinel-5, Sentinel-5P, Surface Radiative PropertiesThe aim of the OPEn platform for the Retrieval of Aerosol and CO2 from S5 (OPERA-S5) project is to develop a totally modular open scientific platform for the combined retrieval of CO2, CH4, aerosol and surface properties based on GRASP (Generalized Retrieval of Atmosphere and Surface Properties) code with the measurements of Sentinel-5 spectrometer UVNS as stand alone, and in combination with the Multiangular Polarimeter 3MI. This new open platform will allow state-of-the-art characterization of atmospheric and surface properties. But also, thanks to its modular architecture, it will serve as a scientific hub for the development of new modeling and retrieval techniques based on AI methodologies.  Two of the main challenges to reach the accuracy requirements in the retrieval of GreenHouse gas concentrations from spaceborne sensors are the scattering elements (aerosol and surface) and the computationally expensive calculations involved in the hyperspectral gas absorption features. OPERA-S5 platform tackles both of them by taking advantage of the highly accurate aerosol and surface characterization of GRASP with Multiangle-Polarimetric measurements and the acceleration possibilities offered by AI based approaches. 
OPEN SAR LIBRARY (AlignSAR) The AlignSAR project aims to provide FAIR-guided open datasets and tools designed for SAR applications, ensuring interoperability and consistency with existing and upcoming initiatives and technologies. The project facilitates a wider [...]UNIVERSITY OF TWENTE (NL)Scienceopen science, platforms, SAR, Sentinel-1The AlignSAR project aims to provide FAIR-guided open datasets and tools designed for SAR applications, ensuring interoperability and consistency with existing and upcoming initiatives and technologies. The project facilitates a wider exploitation of SAR data and its integration and combination with other datasets. The project aims to achieve the following objectives: Define a procedure for creating SAR benchmark datasets for machine learning applications. Develop a reference, quality-controlled, documented, open benchmark datasets of SAR spatial and temporal signatures of complex real-world targets with high diversity to serve a wide range of applications with societal relevance. The database will respect FAIR (Findable, Accessible, Interoperable, Reproducible) and Open Science principles. Create the database considering both open and closed SAR missions (including at minimum Sentinel-1), maximizing the geographical and temporal coverage, and integrating and aligning multi-SAR images and other geodetic measurements in time and space. Define a specification of the signatures and their associated descriptors so that they can be easily indexed, programmatically searched, and retrieved. Develop an open-source software library with associated documentation to create, describe, test, validate, and publish SAR signatures, and expand the database. Demonstrate, test, and validate the Open SAR Library (database and open-source software) on at least two use cases for machine learning applications. Ensure long-term availability of the database and open-source library, potentially through integration with other relevant open platforms and tools.
openEO platform: a Federated Open Earth Observation Platform openEO platform is being implemented as a versatile  cloud-based processing and analytics environment for Earth Observation data. It is being established to address the prevailing capability gap in cloud-based platforms for big EO data [...]EODC EARTH OBSERVATION DATA CENTRE FOR WATER RESOURCES MONITORING (AT)Digital Platform Servicesgeneric platform service, platforms, Sentinel-1, Sentinel-2openEO platform is being implemented as a versatile  cloud-based processing and analytics environment for Earth Observation data. It is being established to address the prevailing capability gap in cloud-based platforms for big EO data processing and analytics. The concepts builds on a federated architecture with initial deployments in EODC, TerraScope, CreoDIAS and the EuroDataCube. openEO platform is a collaborative effort of a experienced European consortium, consisting of partners with strong expertise in cloud platform operation and development, EO science and service provisioning: EODC (AT), VITO (BE), Sinergise (SI), EURAC (IT), EGI (NL) and University Muenster (DE). Additional in kind support is provided by GEO. The current federated architecture includes backends in EODC, VITO Terrascope and CreoDIAS while EuroDataCube is utilised for data access in additional cloud environments.  Several guiding principles govern the implementation of openEO platform. These include:  • Abstracting the complexity of processing and analytic operations through intuitive, high-level API, processes and front end libraries;  • Providing full flexibility and scalability from pixel- to continental level;  • Ensuring transparency, confidentiality, scientific integrity and reproducibility;  The agile open source development is following 9 key use cases that incrementally enhance the capabilities of openEO platform. The first ones that have been addressed include on-demand Analysis Ready Data generation for SAR and multi-spectral data, systematic feature engineering and time series based change detection. 
Platform Common Architecture The project has defined, developped and validated a reference architecture and related implementation of a generic EO Exploitation Platform, as well as its interconnection within a Network of Resources. The architecture and implementation are [...]TELESPAZIO VEGA UK LIMITED (GB)Digital Platform ServicesplatformsThe project has defined, developped and validated a reference architecture and related implementation of a generic EO Exploitation Platform, as well as its interconnection within a Network of Resources. The architecture and implementation are based on open standards and open source.Reusable open source code covering three main domain areas (Federated Identity Management and Authentication plus Authorisation, Processing plus Production Chaining, Data Provisioning and Management plus Accounting) has been released and will be deployed on the varius NoR Resource Tier providers as interoperable layer by the operations teams.
Platform Common Architecture – OGC Testbed 14 The activity (a thread within the OGC Testbed 14 initiative) builds up on the previous Testbed 13 activities by allowing the definition of more complex algoritms (worflows, i.e. multiple tasks executed in proper order) can be defined, deployed [...]CGI IT UK LIMITED (GB)Digital Platform ServicesplatformsThe activity (a thread within the OGC Testbed 14 initiative) builds up on the previous Testbed 13 activities by allowing the definition of more complex algoritms (worflows, i.e. multiple tasks executed in proper order) can be defined, deployed and executed with appropiate access control mechanisms in an interoperable manner across a number of different environments.
Platform Common Architecture – OGC Testbed 13 The activity (a thread within the OGC Testbed 13 initiative) demonstrated how an EO algorithm could be package, deployed and executed in an interoperable manner across a number of different environments.CGI IT UK LIMITED (GB)Digital Platform ServicesplatformsThe activity (a thread within the OGC Testbed 13 initiative) demonstrated how an EO algorithm could be package, deployed and executed in an interoperable manner across a number of different environments.
POINTOUT (Automatic Target Detection in Planet Imagery) Traditional empirical and analytical Earth Observation (EO) algorithms retrieving physical parameters are getting to a fundamental change where learning algorithms without any prior background will be able to set themselves through the ingestion [...]STARLAB BARCELONA SL (ES)Enterpriseartificial intelligence, permanently open call, platformsTraditional empirical and analytical Earth Observation (EO) algorithms retrieving physical parameters are getting to a fundamental change where learning algorithms without any prior background will be able to set themselves through the ingestion of Inputs/Outputs training datasets. Nowadays, Deep Learning (DL) networks among many other Machine Learning (ML) techniques are accurate enough, and computation technology is available to run such models. One of the key issue of such approach is the availability of massive or, large enough, reference datasets to train the models. As the models learn from the available data within the training datasets, if the size of such dataset is relatively small, the models learn very specific features that do not allow o generalize to any input data due to the lack of representativeness of the training dataset. This project addresses this issue in the context of a specific ML application, ie target/feature detection. The main goals are (1) to develop a PLATFORM to build and share collaborative training datasets for combined EO/ML communities, and (2) to implement a generic ML algorithm to detect targets in EO scenes for expert and/or non-expert users online
Polar TEP extension with AI capabilities EO has a unique role in monitoring the Polar Regions by providing information that is consistent, repeatable, year-round, and covers the extensive area. In particular, Synthetic Aperture Radar (SAR) missions, such as Sentinel-1, have for many [...]POLAR VIEW EARTH OBSERVATION LTD (GB)Digital Platform Servicesartificial intelligence, natural hazards, platforms, polar flagship, Sentinel-1EO has a unique role in monitoring the Polar Regions by providing information that is consistent, repeatable, year-round, and covers the extensive area. In particular, Synthetic Aperture Radar (SAR) missions, such as Sentinel-1, have for many years proven useful in high resolution monitoring due to their capability of acquiring data independent of cloud cover and polar night. However, the size of the polar regions means that relying on human analysis of the large volume of data available is not practical. The polar user communities have been early adopters of AI/ML applied to EO data. This project addresses the need for a ML platform to better serve the polar user communities. The work will implement MLflow, a well-proven ML platform, augmented by DVC to manage training data. The operation and benefits of MLflow within Polar TEP will be validated and illustrated through the following showcases: Showcase 1: Nature-Based Solutions for Flood and Erosion Protection, and Showcase 2: Polar Voyage Planning and Support Showcase 1 addresses the need for resilient infrastructures to mitigate increased coastal and riverine flood and erosion potential as a consequence of climate change. Employing nature-based methods to mitigate flood and erosion hazards is an environmentally friendly solution. Showcase 2 responds to the needs of ships and people operating in the polar regions for past, present, and future environmental information, especially concerning sea ice. These regions are experiencing climate change at a rate that is up to five times greater than the rest of the planet. ML applied to environmental data can help mitigate the impact of these changes by providing better information with which to plan and conduct polar operations and thus provide improved safety for people, infrastructure, and the environment.
Polar Thematic Exploitation Platform The Polar Thematic Exploitation Platform provides a complete working environment where users can access algorithms and data remotely, providing computing resources and tools that they might not otherwise have, avoiding the need to download and [...]POLAR VIEW EARTH OBSERVATION LTD (GB)Digital Platform Servicesapplications, cryosphere, platformsThe 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.
Privacy Preserving Federated Machine Learning in EO Science Big Data and artificial intelligence (AI) pave the way for new pathways in the improvement of healthcare. But they also hide risks for the security of sensitive clinical data stored in critical healthcare ICT infrastructure. The EU-funded [...]GMV SOLUCIONES GLOBALES INTERNET SA (ES)AI4EO, Digital Platform ServicesAI4EO, generic platform service, permanently open call, platformsBig Data and artificial intelligence (AI) pave the way for new pathways in the improvement of healthcare. But they also hide risks for the security of sensitive clinical data stored in critical healthcare ICT infrastructure. The EU-funded FeatureCloud project proposes a transformative security-by-design concept aiming to reduce the possibility of cyber crime and allow safe cross-border collaborative data mining efforts. The concept will be applied to a software toolkit employing the worldwide first privacy-by-architecture method. Central features of this method are no sharing of sensitive data via any communication channels and no data storage in one central point. FeatureCloud will integrate federated machine learning with blockchain technology to safely apply next-generation AI technology in medical innovations. The digital revolution, in particular big data and artificial intelligence (AI), offer new opportunities to transform healthcare. However, it also harbors risks to the safety of sensitive clinical data stored in critical healthcare ICT infrastructure. In particular data exchange over the internet is perceived insurmountable posing a roadblock hampering big data based medical innovations. FeatureCloud’s transformative security-by-design concept will minimize the cyber-crime potential and enable first secure cross-border collaborative data mining endeavors. FeatureCloud will be implemented into a software toolkit for substantially reducing cyber risks to healthcare infrastructure by employing the world-wide first privacy-by-architecture approach, which has two key characteristics: (1) no sensitive data is communicated through any communication channels, and (2) data is not stored in one central point of attack. Federated machine learning (for privacy-preserving data mining) integrated with blockchain technology (for immutability and management of patient rights) will safely apply next-generation AI technology for medical purposes. Importantly, patients will be given effective means of revoking previously given consent at any time. Our ground-breaking new cloud-AI infrastructure only exchanges learned model representations which are anonymous by default. Collectively, our highly interdisciplinary consortium from IT to medicine covers all aspects of the value chain: assessment of cyber risks, legal considerations and international policies, development of federated AI technology coupled to blockchaining, app store and user interface design, implementation as certifiable prognostic medical devices, evaluation and translation into clinical practice, commercial exploitation, as well as dissemination and patient trust maximization. FeatureCloud’s goals are bold, necessary, achievable, and paving the way for a socially agreeable big data era of the Medicine 4.0 age.
Proba-V Mission Exploitation Platform – Third-Party Services The project has demonstrated the Proba-V Mission Exploitation Platform (MEP) capabilities (in terms of infrastructure and vegetation product access) with a number of identifies pilot users (scientists and industry) giving them the opportunity to [...]SPACE APPLICATIONS SERVICES S.A./N.V. (BE)Digital Platform ServicesplatformsThe project has demonstrated the Proba-V Mission Exploitation Platform (MEP) capabilities (in terms of infrastructure and vegetation product access) with a number of identifies pilot users (scientists and industry) giving them the opportunity to prototype potential tools and services.
Query Planet QueryPlanet aims at democratizing the access of Artificial Intelligence to the Earth Observation community by developing open-tools for the creation of AI-ready EO dataset and use-cases that leverage such datasets to build global insights [...]SINERGISE LTD. (SI)AI4EOAI4EO, forestry, platforms, Sentinel-2QueryPlanet aims at democratizing the access of Artificial Intelligence to the Earth Observation community by developing open-tools for the creation of AI-ready EO dataset and use-cases that leverage such datasets to build global insights applications. Material and datasets develop under QueryPlanet are open-access. The project aims at providing open-source tools for the exploitation of Earth Observation data, in particular of Sentinel-2 imagery. The target audiences of the project are the EO and AI communities, fostering their engagement in exploiting EO dataset, in particular Sentinel-2, to build applications that tackle relevant topics.In the first phase of the project, tools to annotate Sentinel-2 imagery are developed, allowing any user to set-up and share with the community their labeling campaign. Following the creation of the label datasets, the creation of the EO processing workflow is facilitated by eo-learn, the open-source Python package developed within the project. eo-learn provides common processing tasks to scale the analysis of satellite imagery to global scale through seamless parallelization. To further promote the upake of the tools created, AI-ready dataset and use-cases capitalising on such datasets are created and published. Currently developed use-cases include: super-resolution of Sentinel-2 bands beyond the 10 metre spatial resolution, using the HighResNet multi-frame super-resolution algorithm and VHR imagery as target reference. The training dataset for such algorithm is globally sampled and includes humanitarian targets; a hierarchical object detection scheme which uses several data sources with increased spatial resolution to detect buildings in an efficient and scalable way. The hierarchical scheme in this case uses Sentinel-2, Airbus SPOT and Airbus Pleiades imagery to perform object detection using rotated bounding boxes; a pan-European map of forest and forest types using Sentinel-2 time-series. The developed algorithm is based on the latest deep learning architectures for the analysis of spatio-temporal datasets, and uses tens of thousands of samples collected over the EEA countries area. Open-source tools to ease labelling of EO imagery Open-source tools to process EO imagery for the creation of AI-ready datasets Publishing of AI-ready datasets covering a wide range of thematics Publishing of material to create use-case applications based on AI to extract insights from the EO datasets Facilitate entry to the field to non EO experts
R4OpenEO – Integrating R Analytics with openEO Platforms This project will develop, test and demonstrate the use of the R data science language within openEO platform.
This involves the continuation of development of the openEO R client, integration of openEO software components in R integrated [...]
EURAC RESEARCH – ACCADEMIA EUROPEA (IT)Digital Platform Servicespermanently open call, platformsThis project will develop, test and demonstrate the use of the R data science language within openEO platform. This involves the continuation of development of the openEO R client, integration of openEO software components in R integrated development environments (Rstudio, Project Jupyter), as well as R user-defined functions that directly operate on data cubes and their interaction with the openEO back-end drivers. Three selected use cases, from the context of the ESA Regional Initiatives, will demonstrate the usability of the developed components and foster collaboration with the EO4Alps regional initiative and the openEO Platform project.
RACE – Rapid Action on Covid-19 and EO The Rapid Action coronavirus Earth observation dashboard presents the results of the Joint cooperation between ESA and the European Commission on Covid 19 and EO.The platform demonstrates how the use of Earth [...]European Space Agency (ESA) – EOPDigital Platform Servicescovid19, platforms, scienceThe Rapid Action coronavirus Earth observation dashboard presents the results of the Joint cooperation between ESA and the European Commission on Covid 19 and EO. The platform demonstrates how the use of Earth observation data can help shed new light on societal and economic changes currently taking place owing to the coronavirus pandemic. Across all European countries and ESA Member States, the dashboard showcases examples of how different analyses over a wide range of Earth observation data coming from the Copernicus Sentinels and Third Party Missions, as well as ground-based observations and advanced numerical models via the Copernicus Services can illustrate these socio-economic and environmental changes. The dashboard not only captures the effects of the lockdown, but also shows how Europe is beginning its recovery and is relaunching a number of activities. The data populating the dashboard are a collective effort of a number of industrial and academic partners.                                      
SatHound: Multi-object detection solution based on artificial intelligence for non-expert EO users SatHound is a solution to allow non-technical users configuring and executing multi-object detection processes over satellite images, based on deep learning technologies providing the following features:

Two modes of operation in a clean [...]
THALES ALENIA SPACE ESPANA (ES)Enterprisepermanently open call, platformsSatHound is a solution to allow non-technical users configuring and executing multi-object detection processes over satellite images, based on deep learning technologies providing the following features: Two modes of operation in a clean and powerful user interface with Web-GIS capabilities: The training mode is used for teaching the system how to recognize new objects or to improve previous trainings with new examples. No more training datasets to be shared! This is a user-driven training mode, allowing to define unlimited detection targets. The hound mode is used for searching target objects on different map areas using already acquired knowledge. Batch training lets the user to continue using the hound mode while a SatHound improves it cognitive functions in background. Training status can be consulted at any time. Models are trained incrementally providing fast trainings and the possibility to roll-back to previous knowledge status in case of a wrong training. REST API for integrating with other systems. This lets external systems to scan geographic areas using the hound mode as you would do using the user interface. On-premise, Hybrid or Cloud deployment capabilities. The scalable architecture lets you scale-out the whole application for high availability or heavy load scenarios A local catalogue for hosting the satellite data products used in the searches.
SEN3GCP – Sentinel for 3D Ground Control Point SEN3GCP is conceived as a service that will provide  GCPs (Ground Control Points) and precise co-registration of EO products as an automated service accessible via the web and API. The service will be based on a global database of GCPs that is [...]Planetek Italia (IT)Digital Platform Servicesgeneric platform service, permanently open call, platforms, SARSEN3GCP is conceived as a service that will provide  GCPs (Ground Control Points) and precise co-registration of EO products as an automated service accessible via the web and API. The service will be based on a global database of GCPs that is derived from SAR imagery (3D coordinates including height information) and for which corresponding image chips of multispectral data are derived and maintained. The implemented service will provide GCPs via API and other interfaces. The service will also provide a mechanism for precise co-registration of EO data enabling for example the precise co-registration of multi-spectral and SAR data.
Sentinel Hub for Network of Resources Sentinel Hub services are operational services running on several platforms (AWS EU-Frankfurt, AWS US-West, Creodias, Onda and Mundi web services), providing seamless access to various satellite missions over web service API. They are used by [...]SINERGISE LTD. (SI)Digital Platform Servicespermanently open call, platforms, scienceSentinel Hub services are operational services running on several platforms (AWS EU-Frankfurt, AWS US-West, Creodias, Onda and Mundi web services), providing seamless access to various satellite missions over web service API. They are used by thousands of users (free and payable) all over the world and two million requests are processed on average every single day. Two freely accessible web applications are operated within Sentinel Hub suite – Sentinel Playground, easy-to-use Google Maps-like web client and EO Browser providing a more advanced access to various data-sets supported by Sentinel Hub services. Various advanced features are available as well – export to GeoTiff, statistical analysis, time-lapse generation, custom scripting, etc. This project has performed an upgrade to Sentinel Hub services to make them ready for integration in Network of Resources, including: • User management (authentication and integration with EDUGAIN to make the access available to tens of thousands of Open Science Cloud users without additional registration) • Integration of Sentinel Hub services on the back-end level (to increase system performance, availability, and efficiently exploit separate deployments) • Security • Data fusion to make it possible to combine data from different missions in the same custom script, also adding further attributes (sun angle, quality, projections, etc..) • Upgrade of Python libraries and Web clients to support all above-mentioned new features
Technology and atmospheric mission platform – OPerations (TOP) The atmospheric mission platform has demonstrated that (1) multiple data sources (the "data triangle" namely satellite-based products, numerical model output, and ground measurements) can be simultaneously exploited by users (mainly scientists), [...]SISTEMA GMBH (AT)Digital Platform Servicesatmosphere science cluster, permanently open call, platforms, scienceThe atmospheric mission platform has demonstrated that (1) multiple data sources (the “data triangle” namely satellite-based products, numerical model output, and ground measurements) can be simultaneously exploited by users (mainly scientists), and (2) a fully Virtual Research Environment that allows avoiding the download of all data locally, and retrieving only the processing results is the optimal solution.
The DeepESDL AI-Ready Earth System Data Lab  The Deep Earth System Data Lab (DeepESDL) delivers a service to the Earth Science community. The lab provides convenient access to relevant data sets, many of them generated in ESA’s science projects, in an analysis-ready format. Moreover, [...]BROCKMANN CONSULT GMBH (DE)AI4EOAI4EO, AI4Science, platforms, training and education, virtual labsThe Deep Earth System Data Lab (DeepESDL) delivers a service to the Earth Science community. The lab provides convenient access to relevant data sets, many of them generated in ESA’s science projects, in an analysis-ready format. Moreover, DeepESDL comprises a powerful data science environment with a focus on machine-learning and artificial intelligence workflows. We are committed to open science and encourage and support research users in sharing and publishing products and workflows according to FAIR principles, thus fostering transparency and reproducibility in research. We invite interested users in joining us in this exciting endeavour!
Triple-A For Exploitation Platforms The project has provided a pre-operational demonstration of a Triple-A system (Authentication, Authorization and Accounting) for Exploitation Platforms using modern standards such as Open ID Connect (OIDC) and User Managed Access (UMA) based on [...]DEIMOS SPACE S.L.U (ES)Digital Platform Servicespermanently open call, platformsThe project has provided a pre-operational demonstration of a Triple-A system (Authentication, Authorization and Accounting) for Exploitation Platforms using modern standards such as Open ID Connect (OIDC) and User Managed Access (UMA) based on open source technologies.The proposed solution addresses significant gaps on current Authentication, Authorization and Accounting services made available to science users and application developers on exploitation platforms. The projeect results are operationally offered as support services to the “Network of Resources” to integrate platfrom services with federeated identity management.
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 Servicesapplications, platforms, urbanThe 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.
Vine irrigation from earth observation data – WineEO Optimizing water resources is a real issue in some geographical area. Temperature have increased by 0,85°C on average between 1880 and 2012 and couldreach 4.8°C by 2100 compared to the period from 1986 to 2005, according to the last IPCC report. [...]TERRANIS SAS (FR)Enterpriseagriculture, climate, permanently open call, platforms, Sentinel-2, water resourcesOptimizing water resources is a real issue in some geographical area. Temperature have increased by 0,85°C on average between 1880 and 2012 and couldreach 4.8°C by 2100 compared to the period from 1986 to 2005, according to the last IPCC report. As a result, agriculture and viticulture are facing an increasing water scarcity at the same time as a growing demand. This growing pressure leads to the necessity to optimize available water resources without losing neither yield production nor quality. Vine irrigation has been used for a very long time in the so-called “new world” vineyards (Australia, Argentina, United States (California) and Chile) and is widely practiced there. Its adoption in Mediterranean regions is much more recent and is one of the first adaptations of wine growers to the consequences of climate change (Ojeda and Saurin, 2014). Irrigation and water stress management of grapevines is essential in arid and semi-arid areas with limited water supplies to maintain both the quality and quantity of the harvest. This has led the scientific community and companies to develop new technologies for irrigation control, allowing to rationalize the inputs according to the needs of the crop. WineEO project is a step in this direction with the objective of developing an operational irrigation scheduling service for winegrowers. This service, named Wago, is based on a water balance model (named Sa’irr) mixing three data sources: satellite imagery with optical images coming from the Copernicus program (Sentinel-2), in situ data and meteorological data. It provides farmers with irrigation recommendations (when, where and how much water amount apply over the vineyard to optimize water inputs). Two main challenges are identified in this project: Adapting the existing water balance model developed by the Cesbio to vine specificities. Indeed, in contrast to annual crops, vines are characterized by a cover sparsity and a large variability of geometry (rows, inter-rows, vegetation height).  Sat’irr model has been mostly developed for one dimensional crops such as wheat and maize. To adapt the model to the vine, it is mandatory to take into account the geometry of the crop. Sentinel-2 optical images are used to determine the growth stage of vineyard. Nonetheless, the spatial resolution of Sentinel-2 bands is one of the limitations for their use in precision viticulture due to the intra-variability of the plots. Advances in Deep Learning in the field of Computer Vision allows enhancing the spatial resolution of these images by using single image super-resolution (SISR) techniques. In the WineEO project, a deep learning SISR was developed to recover a super-resolved Sentinel-2 image at 2.5m in the visible and near-infrared part of the spectrum from its low resolution counterpart. Developing a user friendly platform to allow winegrowers to access Wago products. Wago is a decision-making tool developed to help farmers manage their irrigations by providing irrigation recommandations. The tool is based on Sat’irr model and optical images and calculates the water balance on a daily-basis. The project is led by TerraNIS, which is in charge of the industrialization and commercialization of the service. The Cesbio, a French laboratory, will adapt the Sat’irr water balance model embedded in Wago. Finally, four end-users are targeted in four different countries – Portugal, Italy, Spain and Chile – to test the application in different agronomic conditions (soil, climate, agricultural practices, etc.).
World Ocean Circulation The objectives of this activity are to (i) develop and validate innovative methodologies allowing to optimize the synergetic capacity offered by satellite data, in situ measurements and numerical models for improving the retrieval of upper-layer [...]OCEANDATALAB (FR)Applicationsocean health flagship, ocean science cluster, oceans, platforms, science, sea surface topography, sustainable developmentThe objectives of this activity are to (i) develop and validate innovative methodologies allowing to optimize the synergetic capacity offered by satellite data, in situ measurements and numerical models for improving the retrieval of upper-layer ocean circulation products over FOUR high-priority pilot areas chosen as to represent at best the diversity of the world ocean circulation regimes, i.e. one polar sea area, one western boundary current, one upwelling region, one coastal area, and ii) in line with the objectives of the United Nations Decade of Ocean Science for Sustainable Development, demonstrate the unique capacity of the innovative products to support effective actions aiming at procuring a clean, safe, sustainably harvested and productive ocean by targeting FOUR high priority pilot applications, i.e. Pollution Monitoring, Safe Navigation, Sustainable Fisheries and Renewable Marine Energies. In order to answer the project’s objectives, the consortium will investigate the four following themes: Theme 1: Sea-state current interactions for Safe Navigation Theme 2: 3D currents and vertical motion for Sustainable Fisheries Theme 3: Surface Lagrangian drift for a Clean Ocean Theme 4: HR wave and current model assessment for a Productive Ocean For each theme, a minimum of two users have been engaged. Their role during the project is twofold. First, they will provide support to the consortium for the user requirement consolidation both in terms of products needed and ocean processes of utmost importance for their applications. Second, it is expected that feedback on usefulness and impact of the WOC products will be obtained through the impact studies performed by the users. In addition to the development of innovative methods and products targeting direct answers to the user needs, a series of tools will be also developed, implemented and maintained during the project. These tools should ease and maximize the WOC users’ involvement and further aim to attract  potential new users.