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Open AccessArticle

A Wind Speed Retrieval Model for Sentinel-1A EW Mode Cross-Polarization Images

Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China
Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27607, USA
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(2), 153;
Received: 30 December 2018 / Revised: 14 January 2019 / Accepted: 14 January 2019 / Published: 15 January 2019
(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)
In contrast to co-polarization (VV or HH) synthetic aperture radar (SAR) images, cross-polarization (CP for VH or HV) SAR images can be used to retrieve sea surface wind speeds larger than 20 m/s without knowing the wind directions. In this paper, a new wind speed retrieval model is proposed for European Space Agency (ESA) Sentinel-1A (S-1A) Extra-Wide swath (EW) mode VH-polarized images. Nineteen S-1A images under tropical cyclone condition observed in the 2016 hurricane season and the matching data from the Soil Moisture Active Passive (SMAP) radiometer are collected and divided into two datasets. The relationships between normalized radar cross-section (NRCS), sea surface wind speed, wind direction and radar incidence angle are analyzed for each sub-band, and an empirical retrieval model is presented. To correct the large biases at the center and at the boundaries of each sub-band, a corrected model with an incidence angle factor is proposed. The new model is validated by comparing the wind speeds retrieved from S-1A images with the wind speeds measured by SMAP. The results suggest that the proposed model can be used to retrieve wind speeds up to 35 m/s for sub-bands 1 to 4 and 25 m/s for sub-band 5. View Full-Text
Keywords: Sentinel-1; cross-polarization; wind retrieval; SMAP Sentinel-1; cross-polarization; wind retrieval; SMAP
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MDPI and ACS Style

Gao, Y.; Guan, C.; Sun, J.; Xie, L. A Wind Speed Retrieval Model for Sentinel-1A EW Mode Cross-Polarization Images. Remote Sens. 2019, 11, 153.

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