Sea Surface Wind Speed Retrieval From Textures in Synthetic Aperture Radar Imagery

被引:13
|
作者
Zhou, Lizhang [1 ,2 ]
Zheng, Gang [2 ,3 ]
Yang, Jingsong [1 ,2 ,3 ]
Li, Xiaofeng [4 ,5 ]
Zhang, Bin [4 ,5 ]
Wang, He [6 ]
Chen, Peng [2 ]
Wang, Yan [2 ]
机构
[1] Zhejiang Univ, Ocean Coll, Zhoushan 316021, Peoples R China
[2] Minist Nat Resources, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou 310012, Peoples R China
[3] Southern Marine Sci & Engn Guangdong Lab, Zhuhai 519082, Peoples R China
[4] Chinese Acad Sci, Big Data Ctr, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China
[5] Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China
[6] Minist Nat Resources, Natl Ocean Technol Ctr, Tianjin 300112, Peoples R China
基金
中国国家自然科学基金;
关键词
Radar polarimetry; Sea surface; Oceanography; Atmospheric modeling; Surface waves; Atmospheric waves; Wind speed; Entropy; gray-level cooccurrence matrix (GLCM); synthetic aperture radar (SAR); sea surface wind speed (SSWS); textures; OIL-SPILL TRAJECTORIES; SAR IMAGES; OCEAN; SCATTEROMETER; RADIOMETER; MODEL;
D O I
10.1109/TGRS.2021.3062401
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Wind-induced oriented textures (WIOTs) are commonly used to retrieve sea surface wind directions from synthetic aperture radar (SAR) images. In this study, we found that WIOTs are also related to sea surface wind speeds (SSWSs). The entropy values in the gray-level cooccurrence matrices (GLCMs) for SAR images containing WIOTs will become steady with increasing distance between pairs of pixels. Furthermore, these steady values of entropy (SVEs) show a clear linear relationship with SSWSs. As a result, an SSWS retrieval model was developed based on this relationship. We used 2222/2223 Sentinel-1 SAR images (wind speed ranges from 5 to 20 m/s) to fit/validate the algorithm. The retrieved SSWSs were compared with the European Centre for Medium-Range Weather Forecast (ECMWF) SSWSs, Cross-Calibrated Multi-Platform (CCMP) SSWSs, and Tropical Atmosphere/Ocean (TAO) buoy measurements, and the root-mean-square differences (RMSDs) were 1.78, 1.70, and 1.78 m/s, respectively. The new model was also tested for SAR images acquired under hurricane conditions. The wind comparisons against stepped-frequency microwave radiometer (SFMR) measurements show an RMSD of 1.28 m/s. Our modelx2019;s performance was also tested with the images at different spatial scales in the validation data set. Since the model is based on inherent image patterns, it still works well for SAR images without precise calibration.
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页数:11
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