EuroCropsML: A Time Series Benchmark Dataset For Few-Shot Crop Type Classification

We introduce EuroCropsML, an analysis-ready remote sensing machine learning dataset for time series crop type classification of agricultural parcels in Europe. It is the first dataset designed to benchmark transnational few-shot crop type classification algorithms that supports advancements in algorithmic development and research comparability. It comprises 706 683 multi-class labeled data points across 176 classes, featuring annual time series of per-parcel median pixel values from Sentinel-2 L1C data for 2021, along with crop type labels and spatial coordinates. Based on the open-source EuroCrops collection, EuroCropsML is publicly available on Zenodo.

@article{reuss2025_2407.17458,
  title={ EuroCropsML: A Time Series Benchmark Dataset For Few-Shot Crop Type Classification },
  author={ Joana Reuss and Jan Macdonald and Simon Becker and Lorenz Richter and Marco Körner },
  journal={arXiv preprint arXiv:2407.17458},
  year={ 2025 }
}