Together with our partner dida Datenschmiede GmbH, the CropClass project uses optical and radar data to classify crop types at different growth stages. The project focuses on typical crops in Germany such as wheat, rye, barley, rapeseed, potato, corn and sugar beet. The target update interval is 3-5 days, and the underlying classification is based on machine learning algorithms.
If you are interested in our prototype, please contact us at
fernlab@gfz-potsdam.de
