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Identification of winter land use in temperate agricultural landscapes based on Sentinel-1 and 2 times-series.

Julien Denize 1 Laurence Hubert-Moy 1 Samuel Corgne 2 Julie Betbeder 3 E. Pottier 1 
2 LETG - Nantes - Littoral, Environnement, Télédétection, Géomatique
UNICAEN - Université de Caen Normandie, EPHE - École pratique des hautes études, UBO - Université de Brest, UR2 - Université de Rennes 2, CNRS - Centre National de la Recherche Scientifique : UMR6554, IGARUN - Institut de Géographie et d'Aménagement Régional de l'Université de Nantes
Abstract : Land cover and land use monitoring, particularly during winter season, is still a major environmental and scientific issue in agricultural areas. From an environmental point of view, the presence and type of vegetation cover in winter have an impact on pollutant transport to water bodies. From a methodological point of view, characterizing spatio-temporal dynamics of winter land cover and land use at a field scale remains a challenge due to the diversity of farming strategies and practices. The objective of this study was to evaluate the potential of optical and SAR time-series to improve the monitoring of winter land use in an area of 130 km(2). For that purpose, Sentinel-1 and 2 time-series were classified using SVM and RF algorithms. Winter land use was identified with an overall accuracy of 81% and a kappa index of 0.77 from a combination of Sentinel-1 and 2 images.
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-02018912
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Submitted on : Thursday, February 14, 2019 - 11:25:44 AM
Last modification on : Wednesday, April 27, 2022 - 3:58:25 AM

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Julien Denize, Laurence Hubert-Moy, Samuel Corgne, Julie Betbeder, E. Pottier. Identification of winter land use in temperate agricultural landscapes based on Sentinel-1 and 2 times-series.. 38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2018, Valencia, Spain. ⟨10.1109/igarss.2018.8517673⟩. ⟨hal-02018912⟩

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