Deriving sea surface wind from synthetic aperture radar based on Fourier transform and neural network

2017 ◽  
Author(s):  
Lihua Wang ◽  
Peng Lu ◽  
Jiapei Ma
Keyword(s):  
Neural Network ◽  
Fourier Transform ◽  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Sea Surface Wind ◽  
Aperture Radar

Effectiveness of WRF wind direction for retrieving coastal sea surface wind from synthetic aperture radar

Wind Energy ◽  
2012 ◽  
Vol 16 (6) ◽  
pp. 865-878 ◽  
Author(s):  
Yuko Takeyama ◽  
Teruo Ohsawa ◽  
Katsutoshi Kozai ◽  
Charlotte Bay Hasager ◽  
Merete Badger
Keyword(s):  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Surface Wind ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Sea Surface Wind ◽  
Coastal Sea ◽  
Aperture Radar

scholarly journals Capabilities of Chinese Gaofen-3 Synthetic Aperture Radar in Selected Topics for Coastal and Ocean Observations

2018 ◽  
Vol 10 (12) ◽  
pp. 1929 ◽  
Author(s):  
Xiao-Ming Li ◽  
Tianyu Zhang ◽  
Bingqing Huang ◽  
Tong Jia
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Wave Mode ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Radiometric Calibration ◽  
Sea Surface Wind ◽  
Wind Retrievals ◽  
Sea Surface Wave ◽  
Aperture Radar

Gaofen-3 (GF-3), the first Chinese spaceborne synthetic aperture radar (SAR) in C-band for civil applications, was launched on August 2016. Some studies have examined the use of GF-3 SAR data for ocean and coastal observations, but these studies generally focus on one particular application. As GF-3 has been in operation over two years, it is essential to evaluate its performance in ocean observation, a primary goal of the GF-3 launch. In this paper, we offer an overview demonstrating the capabilities of GF-3 SAR in ocean and coastal observations by presenting several representative cases, i.e., the monitoring of intertidal flats, offshore tidal turbulent wakes and oceanic internal waves, to highlight the GF-3’s full polarimetry, high spatial resolution and wide-swath imaging advantages. Moreover, we also present a detailed analysis of the use of GF-3 quad-polarization data for sea surface wind retrievals and wave mode data for sea surface wave retrievals. The case studies and statistical analysis suggest that GF-3 has good ocean and coastal monitoring capabilities, though further improvements are possible, particularly in radiometric calibration and stable image quality.

scholarly journals Analysis on the variational model of synthetic aperture radar sea surface wind retrieval

2014 ◽  
Vol 63 (14) ◽  
pp. 148401
Author(s):  
Jiang Zhu-Hui ◽  
Zhou Xiao-Zhong ◽  
You Xiao-Bao ◽  
Yi Xin ◽  
Huang Wei-Quan
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Variational Model ◽  
Wind Retrieval ◽  
Sea Surface Wind ◽  
Sea Surface Wind Retrieval ◽  
Aperture Radar

scholarly journals Regularization method to retrieve synthetic aperture radar sea surface wind

2011 ◽  
Vol 60 (6) ◽  
pp. 068401
Author(s):  
Jiang Zhu-Hui ◽  
Huang Si-Xun ◽  
He Ran ◽  
Zhou Chen-Teng
Keyword(s):  
Synthetic Aperture Radar ◽  
Regularization Method ◽  
Surface Wind ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Sea Surface Wind ◽  
Aperture Radar

scholarly journals A new research on sea surface wind direction retrieval of synthetic aperture radar image

2011 ◽  
Vol 60 (10) ◽  
pp. 108402
Author(s):  
Jiang Zhu-Hui ◽  
Huang Si-Xun ◽  
Shi Han-Qing ◽  
Zhang Wei ◽  
Wang Biao
Keyword(s):  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Surface Wind ◽  
Synthetic Aperture Radar Image ◽  
Sea Surface ◽  
Radar Image ◽  
Synthetic Aperture ◽  
Sea Surface Wind ◽  
New Research ◽  
Aperture Radar
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