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

Joana Reuss, Jan Macdonald, Simon Becker, Lorenz Richter, Marco Körner
7/24/2024
cs.LG

No official code found. Best implementation: dida-do/eurocropsml (32 stars, MIT, last commit 2026-01-16).

Abstract

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.

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Code Implementations(1)

dida-do/eurocropsmlCommunity100%
MIT

EuroCropsML is a ready-to-use benchmark dataset for few-shot crop type classification using Sentinel-2 imagery.

323Python, MakefileApr 24, 20249 months agoMIT
agriculturecrop-classificationdatasetdeep-learningearth-observation+3 more

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Cite this paper

@article{reuss2024eurocropsml,
  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},
  year   = {2024},
  eprint = {2407.17458},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.17458v2}
}

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