The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Aug 2020)

BREIZHCROPS: A TIME SERIES DATASET FOR CROP TYPE MAPPING

  • M. Rußwurm,
  • C. Pelletier,
  • M. Zollner,
  • S. Lefèvre,
  • M. Körner

DOI
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1545-2020
Journal volume & issue
Vol. XLIII-B2-2020
pp. 1545 – 1551

Abstract

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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.