Public-Private EO Datacube Partnership

In the BigPicture project rule-based classification of field health was established for a variety of crop types. In particular, this allows to determin In-field anomalies such as frost and drought effects. Computation relies on complex timeseries analytics combining Sentinel-2a timeseries, CORINE land cover timeseries, soil data, and climate water balance timeseries. All analytics was formulated in the OGC WCPS datacube language - this made it flexible during the design process where alternatives had to be tried out and, due to the high-level nature, made the code self-documenting. Likely this has resulted in the largest WCPS queries ever, with up to 200 lines. Analysis can be carried out using rasdaman in realtime for any regional point; the whole of Germany becomes available in about one hour.

The project was led by Spatial Business Integration, Germany.

Crop growth anomalies for German municipality

Evapotranspiration for Germany, obtained as timeseries aggregation


Dynamic field-level health status derivation

Crop drought situation