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LAMASUS builds on i) decades of experience in direct policy support, ii) unique modeling tools, such as GLOBIOM, the only model that integrates agricultural and land use sectors, and CAPRI, MAGNET and CLUE, which underlie JRC’s land use policy assessments, and iii) novel approaches mobilizing machine learning and citizen science.

WorldCereal is funded by the European Space Agency (ESA) and aims to develop an efficient, agile and robust EO based system for timely global crop monitoring at field scale.

The objective of this project is to quantify feedstock expansion onto land with high carbon stock, as input for the determination of high ILUC fuels. IIASA oversees the global mapping of feedstock expansion into high carbon stock land.

SATFARM Services aims to derive new remote sensing indicators of climate-smart agricultural practices that provide enhanced resilience in the face of weather extremes resulting of climate change

Modification and adjustment of the Full Verified Carbon Account of Forest Ecosystems (Ukraine) based on integration of ground research, remote sensing data and regional models applied to forest ecosystems of Ukrainian Polissya

World Cover aims to produce, deliver and validate, as fast as possible, a global land cover map at 10m resolution with a mapping of a minimum of 10 land cover classes and a minimum overall accuracy of 75%. The project is user driven, aiming at a maximum impact of the global land cover map to a set of end-user organizations.

RapidAI4EO aims to advance rapid and continuous land monitoring with state-of-the-art AI solutions. Under the sponsorship of the European Union’s Horizon 2020 program, RapidAI4EO will establish the foundations for the next generation of Copernicus Land Monitoring Service (CLMS) products.

The ERC PoC project Picture Pile Platform is an innovative, commercially self-sustaining platform that uses the crowdsourcing game Picture Pile for efficiently and intuitively classifying images for machine learning. It will offer a standardized, easy-to-use way for everyone to freely and quickly set-up their own picture pile campaigns for collecting image classifications by the crowd in a gamified environment, where participation is incentivized through extrinsic and intrinsic motivations.

FRAMEwork enables research and empowerment initiatives for farmers and local communities to tackle biodiversity loss.

The CAMALIOT project involves the application of machine learning technology to raw data from the Global Navigation Satellite System (GNSS) to improve the prediction of extreme weather events in the atmosphere (troposphere) and in space (ionosphere)

European countries and regions have invested substantial amounts of resources into biodiversity conservation and knowledge. However, there continues to be limited availability at the EU-scale of harmonized, long-term, spatially explicit and regularly updated biodiversity data. This limits the uptake by policies and sectors that have an impact on biodiversity or that can mitigate biodiversity loss. How will EuropaBON address this challenge?

Towards sustainable food and land-use systems: The Food, Agriculture, Biodiversity, Land, and Energy (FABLE) Consortium.

The Horizon 2020-funded EuroGEOSS Showcases: Applications Powered by Europe (e-shape) project is an unprecedented initiative that brings together decades of public investment in earth observation and in cloud capabilities into services to the citizens, the industry, the decision-makers and the researchers.