BREIZHCROPS: A TIME SERIES DATASET FOR CROP TYPE MAPPING

M. Russwurm (1) , C. Pelletier (2) , M. Zollner (1) , Sébastien Lefèvre (2) , M. Körner (1)

1 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
2 OBELIX - Observation de l’environnement par imagerie complexe

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.

Domaines: Traitement des images [eess.IV]

M. Russwurm, C. Pelletier, M. Zollner, Sébastien Lefèvre, M. Körner. BREIZHCROPS: A TIME SERIES DATASET FOR CROP TYPE MAPPING. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020, XLIII-B2-2020, pp.1545-1551. ⟨10.5194/isprs-archives-XLIII-B2-2020-1545-2020⟩. ⟨hal-03213882⟩