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<p>We introduce <span>EuroCropsML</span>, an analysis-ready remote sensing dataset based on the open-source <span>EuroCrops</span> collection, for <i>machine learning (ML)</i> benchmarking of time series 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 706683 multi-class labeled data points across 176 crop classes. Each data point features a time series of per-parcel median pixel values extracted from Sentinel-2 L1C data and precise geospatial coordinates. <span>EuroCropsML</span> is publicly available on Zenodo.</p>

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The EuroCropsML time series benchmark dataset for few-shot crop type classification in Europe

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月19日

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  • Joana Reuss,
  • Jan Macdonald,
  • Simon Becker,
  • Lorenz Richter,
  • Marco Körner

摘要

We introduce EuroCropsML, an analysis-ready remote sensing dataset based on the open-source EuroCrops collection, for machine learning (ML) benchmarking of time series 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 706683 multi-class labeled data points across 176 crop classes. Each data point features a time series of per-parcel median pixel values extracted from Sentinel-2 L1C data and precise geospatial coordinates. EuroCropsML is publicly available on Zenodo.