BigPicture
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 |
Contact:
