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Agricultural Remote Sensing Information for Farmers in Germany
H. Lilienthal, H. Gerighausen, E. Schnug
Research Center for Agricultural Remote Sensing (FLF) c/o Institute for Crop and Soil Science, Federal Research Institute for Cultivated Plants, Julius Kühn-Institut (JKI), Bundesallee 69, D-38116 B

The European Copernicus program delivers optical and radar satellite imagery at a high temporal frequency and at a ground resolution of 10m worldwide with an open data policy. Since July 2017 the satellite constellation of the Sentinel-1 and -2 satellites is fully operational, allowing e.g. coverage of Germany every 1-2 days by radar and every 2-3 days with optical sensors. This huge data source contains a variety of valuable input information for farmers to monitor the in-field variability and adopt their management strategies. In order to utilize the data in a meaningful way, data needs to be preprocessed and edited, because farmers need a translation from the image data into information and finally decision support based on that information.

The processing chain of the huge amount of data needs an intermediate level, where raw data is converted into information. The Copernicus Program will set up so called “Data and Information Access Services (DIAS)” that allow cloud processing of the raw data into information products. Also cloud computing services like Google Earth Engine or Amazon Web Services offer computing power to process the data.

The “research center for agricultural remote sensing” (FLF) processes the Sentinel Data acquired over Germany and provides several data sets e.g. crop type mapping, actual biomass, leaf area index and yield estimations, which helps farmers even with no precision farming equipment to access data for a start into digital farming. The delivered information products will be tested in the research project AGRO-DE, were consultants, practitioners, researchers and farmers will work with satellite derived information. The information products will be distributed via web services and mobile phone apps readymade for the usage in farm database.

Keyword: Remote sensing, Sentinel, crop type mapping, yield estimation
H. Lilienthal    H. Gerighausen    E. Schnug    Geospatial Data    Oral    2018