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Exploitation of C-Band Sentinel-1 Images for High-Resolution Wind Field Retrieval in Coastal Zones (Iroise Coast, France)

Tran Vu La 1, 2 Ali Khenchaf 1, 2 Fabrice Comblet 1, 2 Carole Nahum 3
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne
Abstract : Synthetic aperture radar (SAR) is one of the favorite tools for earth observation applications, i.e., oceanography, land use mapping, climate change since this device can offer the data at a high spatial resolution and in most meteorological conditions. This is more significant when the data acquired by the Sentinel-1, a new C-band satellite, are exploited. For high-resolution wind field extraction, two different approaches are proposed. In the scatterometry-based approach, wind direction is first extracted by the local gradient method at different scales, i.e., 1–5-km wind resolutions. It is then applied to the empirical geophysical model functions, i.e., CMOD (C-band), for surface wind speed estimation. The advantage of this approach is to deliver accurate wind speed estimates in the range of 2–25 m/s from different SAR data. However, it requires wind direction as an input parameter. This can lead to errors in wind speed estimation due to uncertain wind directions. Therefore, for comparison, in the second approach, we propose the use of the model without wind direction input proposed by Komarov et al. In general, the obtained wind fields based on two proposed approaches are quite similar, and they have good agreement with in situ measurements from the meteorological stations along the Iroise coast.
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Contributeur : Annick Billon-Coat <>
Soumis le : vendredi 1 décembre 2017 - 09:36:11
Dernière modification le : mercredi 24 juin 2020 - 16:19:51



Tran Vu La, Ali Khenchaf, Fabrice Comblet, Carole Nahum. Exploitation of C-Band Sentinel-1 Images for High-Resolution Wind Field Retrieval in Coastal Zones (Iroise Coast, France). IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2017, pp.1 - 14. ⟨10.1109/JSTARS.2017.2746349⟩. ⟨hal-01653119⟩



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