%0 Journal Article %T Polarimetric SAR time-series for identification of winter land use %+ Littoral, Environnement, Télédétection, Géomatique (LETG - Nantes) %+ Institut d'Électronique et des Technologies du numéRique (IETR) %A Denize, J. %A Hubert-Moy, Laurence %A Pottier, E. %Z Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche, MESR 2016Centre National d’Etudes Spatiales, CNESRégion BretagneMinistère de l'Education Nationale, de l'Enseignement Supérieur et de la Recherche, MENESRConseil Général Département des Bouches du RhôneFederación Española de Enfermedades Raras, FEDERGenome Institute of Singapore, GIS %< avec comité de lecture %@ 1424-8220 %J Sensors %I MDPI %V 19 %N 24 %P 5574 %8 2019 %D 2019 %R 10.3390/s19245574 %M 31861133 %K ALOS-2 %K C-band frequency %K Crops %K Dual-polarization %K L-band frequency %K Quad polarization %K RADARSAT-2 %K Random forest classification %K Sentinel-1 %Z Engineering Sciences [physics]Journal articles %X In the past decade, high spatial resolution Synthetic Aperture Radar (SAR) sensors have provided information that contributed significantly to cropland monitoring. However, the specific configurations of SAR sensors (e.g., band frequency, polarization mode) used to identify land-use types remains underexplored. This study investigates the contribution of C/L-Band frequency, dual/quad polarization and the density of image time-series to winter land-use identification in an agricultural area of approximately 130 km2 located in northwestern France. First, SAR parameters were derived from RADARSAT-2, Sentinel-1 and Advanced Land Observing Satellite 2 (ALOS-2) time-series, and one quad-pol and six dual-pol datasets with different spatial resolutions and densities were calculated. Then, land use was classified using the Random Forest algorithm with each of these seven SAR datasets to determine the most suitable SAR configuration for identifying winter land-use. Results highlighted that (i) the C-Band (F1-score 0.70) outperformed the L-Band (F1-score 0.57), (ii) quad polarization (F1-score 0.69) outperformed dual polarization (F1-score 0.59) and (iii) a dense Sentinel-1 time-series (F1-score 0.70) outperformed RADARSAT-2 and ALOS-2 time-series (F1-score 0.69 and 0.29, respectively). In addition, Shannon Entropy and SPAN were the SAR parameters most important for discriminating winter land-use. Thus, the results of this study emphasize the interest of using Sentinel-1 time-series data for identifying winter land-use. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. %G English %2 https://univ-rennes.hal.science/hal-02442758/document %2 https://univ-rennes.hal.science/hal-02442758/file/sensors-19-05574.pdf %L hal-02442758 %U https://univ-rennes.hal.science/hal-02442758 %~ UNIV-BREST %~ UNIV-NANTES %~ EPHE %~ UNIV-RENNES1 %~ UR2-HB %~ CNRS %~ INSA-RENNES %~ IETR %~ LETG %~ LETG-GEOLITTOMER %~ SUP_IETR %~ STATS-UR1 %~ CENTRALESUPELEC %~ COMUE-NORMANDIE %~ UR1-HAL %~ PSL %~ UR1-MATH-STIC %~ UR1-UFR-ISTIC %~ UNIV-RENNES2 %~ IETR-SHINE %~ IETR-OS %~ TEST-UR-CSS %~ UNIV-RENNES %~ UNICAEN %~ INSA-GROUPE %~ TEST-DEV %~ IGARUN %~ TEST-HALCNRS %~ EPHE-PSL %~ UR1-MATH-NUM %~ IETR-POLARIS %~ NANTES-UNIVERSITE %~ UNIV-NANTES-AV2022