dida publishes data descriptor paper on few-shot crop type classification in Nature Scientific Data

Today we are happy to share that we published our latest paper in the Nature Scientific Data journal.

Dr. Jan MacDonald and Dr. Lorenz Richter from dida, in joint collaboration with external partners Joana Reuss and Dr. Marco Körner (both Technical University of Munich, Chair of Remote Sensing Technology), and Dr. Simon Becker (ETH Zürich, Department of Mathematics), developed EuroCropsML - a time series benchmark dataset for few-shot crop type classification in Europe.

It is the first time-resolved remote sensing dataset designed to benchmark transnational few-shot crop type classification algorithms that supports advancements in algorithmic development and research comparability. It comprises more than 700.000 multi-class labeled data points across more than 100 crop classes.

If you are active in the area of remote sensing analysis we recommend you take a look at the publication and the respective code.

Feel free to reach out to us with remarks, questions or remote sensing-related project initiatives.