BreizhCrops: A Satellite Time Series Dataset for Crop Type Identification

Marc Rußwurm 1 Sébastien Lefèvre 2 Marco Körner 1
2 OBELIX - Environment observation with complex imagery
UBS - Université de Bretagne Sud, IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : This dataset challenges the time series community with the task of satellite-based vegetation identification on large scale real-world dataset of satellite data acquired during one entire year. It consists of time series data with associated crop types from 580k field parcels in Brittany, France (Breizh in local language). Along with this dataset, we provide results and code of a Long Short-Term Memory network and Transformer network as baselines. We release dataset, along with preprocessing scripts and baseline models in https://github.com/TUM-LMF/BreizhCrops and encourage methodical researchers to benchmark and develop novel methods applied to satellite-based crop monitoring.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-02343898
Contributor : Sébastien Lefèvre <>
Submitted on : Sunday, November 3, 2019 - 4:32:20 PM
Last modification on : Tuesday, November 5, 2019 - 1:19:27 AM

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  • HAL Id : hal-02343898, version 1
  • ARXIV : 1905.11893

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Marc Rußwurm, Sébastien Lefèvre, Marco Körner. BreizhCrops: A Satellite Time Series Dataset for Crop Type Identification. Time Series Workshop of the 36th International Conference on Machine Learning (ICML), 2019, Long Beach, United States. ⟨hal-02343898⟩

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