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

  • 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.

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Metadaten
Author:Joana Reuss, Jan Macdonald, Simon Becker, Lorenz Richter, Marco Körner
Document Type:Article
Parent Title (English):Scientific Data
Volume:12
Year of first publication:2025
DOI:https://doi.org/10.1038/s41597-025-04952-7
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