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.
@article{arxiv.1905.11893,
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},
journal= {arXiv preprint arXiv:1905.11893},
year = {2020}
}