  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.
