dida publishes paper about Early Crop Classification (Deep Learning in Remote Sensing)

The authors Frank Weilandt, Lorenz Richter, Tiago Sanona, and Jona Welsch from dida published a paper about the early classification of crops using satellite data together with our cooperation partner FERN.Lab, GFZ Potsdam.

The classification of crops is a well-known problem in Remote Sensing and is the basis for applications in public and private sector like yield forecasts.

The paper presents a deep learning based method. This method allows predictions at arbitrary time points during the year with a single model, as well as the seamless combination (fusion) of different data sources (e.g. optical and radar data).

The findings in this paper are based on research from the cooperation project "CropClass" with FERN.Lab.