In the frame of the SnapEarth project, EarthAgriculture pilot will improve the performance and the accuracy of the existing Sen2-Agri processing chains using services offered by the SnapEarth project. The main benefits are:
- Providing a self-service Web portal simplifying the use of this services and the decision making;
- Use EarthSignature land cover database to generate samples as an input of one processing chain;
- The processing framework (SafeScale) and the computing infrastructure deployed on Copernicus DIASes.
As a consequence, EarthAgriculture proposes to agriculture users a set of added values services to support agriculture monitoring activities:
- Reports and statistical analysis of the vegetation status over the crop area into an Area of Interest over a season;
- Reports and statistical analysis of the vegetation status over several crop types into an Area of Interest over a season.
These services will be based on the following products:
- Vegetation Status Indicators: Sentinel-2 based vegetation indicators informing about the evolution of the green vegetation corresponding to the crop vegetative development (NDVI time series, mono- and multi-temporal Leaf Area Indices – LAI);
- Dynamic Crop Mask: A Sentinel-2 based crop mask that consists in a binary map separating annual cropland areas and other areas, thus corresponding to a mask over annually cultivated area. This binary map will be produced along the agricultural season on a monthly basis, to serve for instance as a mask for monitoring crop growing conditions, as basis for sampling stratification and for agricultural extension;
- Crop Type Map: A Sentinel-2 based map of the main crop types in a given region, with a Minimum Mapping Unit of 0.01 ha and provided along with several quality flags. The crop types are classified over the cropland area identified in the cropland mask. The map is generated twice over the season, with a first delivery at the middle of the season and the second one at the end.
Theses value added products are provided as-is and also used to generate statistics over an Area of Interest (AOI: a country, a regional state or a farmer area) and a season. These statistics will contain for example the vegetation status over various crop types or the variation of crop surface between different dates.