Sentinel-2 for Agriculture project : preparing Sentinel-2 operational exploitation for supporting national and global crop monitoring

Developing better agricultural monitoring capabilities based on Earth Observation (EO) data is critical for strengthening food production information and market transparency. The Sentinel-2 (S2) mission has the optimal capacity for agriculture monitoring in terms of resolution (10-20 meter), revisit frequency (5 days) and coverage (global). In 2014, the European Space Agency launched the “Sentinel-2 for Agriculture” project, which aims to provide to the international community an open-source system to process S2 data in an operational manner into relevant EO agricultural products for major worldwide representative agriculture systems. These products consist of (i) cloud-free surface reflectance composites, (ii) monthly cropland masks delivered along the agricultural season, (iii) cultivated crop type map for main crop groups and (iv) LAI and NDVI indicators describing on a 10-day basis the vegetative development of crops. The first phases of the project focused on algorithms selection, system design and implementation. They were achieved using S2-like time series (SPOT Take 5, Landsat 8) over 12 globally distributed sites as well as in-situ data shared by teams working in the various agrosystems. The last phase started in March 2016 and aims at demonstrating the developed system to deliver the products in operational conditions, i.e. over the 2016 growing season with S2 data in near real-time. The demonstration is done at national scale (~500.000 km²) over Ukraine, Mali and South Africa and at local scale (a full S2 swath) for seven sites located in France, Belgium, Czech Republic, Morocco, Madagascar, Sudan and China. It is carried out in close interaction with teams working on the field, with the additional objective to transfer the system to their operations. Doing so, the project wants to contribute to filling the gap between state-of-the-art remote sensing practices and operational systems, thus providing a strong scientific contribution to the GEOGLAM initiative