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Open AccessArticle

An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery

State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
GST at National Oceanic and Atmospheric Administration (NOAA)-National Environmental Satellite, Data, and Information Service (NESDIS), College Park, MD 20740, USA
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(7), 671;
Received: 21 April 2017 / Revised: 23 June 2017 / Accepted: 26 June 2017 / Published: 30 June 2017
(This article belongs to the Special Issue Ocean Remote Sensing with Synthetic Aperture Radar)
Sea surface wind affects the fluxes of energy, mass and momentum between the atmosphere and ocean, and therefore regional and global weather and climate. With various satellite microwave sensors, sea surface wind can be measured with large spatial coverage in almost all-weather conditions, day or night. Like any other remote sensing measurements, sea surface wind measurement is also indirect. Therefore, it is important to develop appropriate wind speed and direction retrieval models for different types of microwave instruments. In this paper, a new sea surface wind direction retrieval method from synthetic aperture radar (SAR) imagery is developed. In the method, local gradients are computed in frequency domain by combining the operation of smoothing and computing local gradients in one step to simplify the process and avoid the difference approximation. This improved local gradients (ILG) method is compared with the traditional two-dimensional fast Fourier transform (2D FFT) method and local gradients (LG) method, using interpolating wind directions from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis data and the Cross-Calibrated Multi-Platform (CCMP) wind vector product. The sensitivities to the salt-and-pepper noise, the additive noise and the multiplicative noise are analyzed. The ILG method shows a better performance of retrieval wind directions than the other two methods. View Full-Text
Keywords: local gradients method; retrieval; SAR; wind direction local gradients method; retrieval; SAR; wind direction
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MDPI and ACS Style

Zhou, L.; Zheng, G.; Li, X.; Yang, J.; Ren, L.; Chen, P.; Zhang, H.; Lou, X. An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery. Remote Sens. 2017, 9, 671.

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