BREIZHCROPS: A TIME SERIES DATASET for CROP TYPE MAPPING

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

Research output: Contribution to journalConference articlepeer-review

34 Scopus citations

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.

Original languageEnglish
Pages (from-to)1545-1551
Number of pages7
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume43
Issue numberB2
DOIs
StatePublished - 6 Aug 2020
Event2020 24th ISPRS Congress - Technical Commission II - Nice, Virtual, France
Duration: 31 Aug 20202 Sep 2020

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