BREIZHCROPS: A TIME SERIES DATASET FOR CROP TYPE MAPPING
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...
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Veröffentlicht in: | International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2020-01, Vol.XLIII-B2-2020, p.1545-1551 |
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Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 2194-9034 1682-1750 2194-9034 |
DOI: | 10.5194/isprs-archives-XLIII-B2-2020-1545-2020 |