BreizhCrops: A Time Series Dataset for Crop Type Mapping

Marc Rußwurm, Charlotte Pelletier, Maximilian Zollner, Sébastien Lefèvre, Marco Körner
5/28/2019
cs.LGcs.CVstat.ML

Official code: dl4sits/BreizhCrops (225 stars, GPL-3.0, last commit 2022-05-11).

Abstract

We present Breizhcrops, a novel benchmark dataset for the supervised classification of field crops from satellite time series. We aggregated label data and Sentinel-2 top-of-atmosphere as well as bottom-of-atmosphere time series in the region of Brittany (Breizh in local language), north-east France. We compare seven recently proposed deep neural networks along with a Random Forest baseline. The dataset, model (re-)implementations and pre-trained model weights are available at the associated GitHub repository (https://github.com/dl4sits/BreizhCrops) that has been designed with applicability for practitioners in mind. We plan to maintain the repository with additional data and welcome contributions of novel methods to build a state-of-the-art benchmark on methods for crop type mapping.

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Code Implementations(1)

dl4sits/BreizhCropsOfficial100%
GPL-3.0

A Satellite Time Series Dataset for Crop Type Identification

22550Shell, PythonApr 27, 20194 years agoGPL-3.0

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Cite this paper

@article{ruwurm2019breizhcrops,
  title  = {BreizhCrops: A Time Series Dataset for Crop Type Mapping},
  author = {Marc Rußwurm and Charlotte Pelletier and Maximilian Zollner and Sébastien Lefèvre and Marco Körner},
  year   = {2019},
  eprint = {1905.11893},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1905.11893}
}

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