Title
An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery.
Abstract
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.
Year
DOI
Venue
2017
10.3390/rs9070671
REMOTE SENSING
Keywords
Field
DocType
local gradients method,retrieval,SAR,wind direction
Meteorology,Atmosphere,Satellite,Weather and climate,Wind speed,Synthetic aperture radar,Remote sensing,Wind direction,Smoothing,Geology,Multiplicative noise
Journal
Volume
Issue
ISSN
9
7
2072-4292
Citations 
PageRank 
References 
2
0.44
8
Authors
8
Name
Order
Citations
PageRank
Lizhang Zhou120.44
Gang Zheng210919.51
Xiaofeng Li333679.94
Jingsong Yang463.88
Lin Ren5153.15
Peng Chen641.88
Huaguo Zhang7173.25
Xiulin Lou841.82