DocumentCode
2979599
Title
Different HH-to-VV polarisation models´ performance in retrieving wind speed using Radarsat2 image mode data by CMOD5
Author
Shao, Weizeng ; Guan, Changlong ; Sun, Jian ; Sun, Zhanfeng
Author_Institution
Phys. Oceanogr. Lab., Ocean Univ. of China, Qingdao, China
fYear
2009
fDate
26-30 Oct. 2009
Firstpage
1107
Lastpage
1110
Abstract
As we known, CMOD models were developed for C-band VV-polarized SAR images, and when CMOD family models are applicable for HH-polarized SAR images such as Radarsat2 images it is necessary to convert normalized radar cross section (NRCS) (HH-polarized) to NRCS (VV-polarized) by the HH-to-VV polarisation model. In this study, we discussed different HH-to-VV polarisation models´ performance in retrieving wind speed by CMOD5 from Radarsat2 image mode data. Image data used in this paper was taken in south of China, Hainan Island. One image was taken on condition of low wind speed while another was taken on condition of moderate wind speed. After retrieving wind speed using CMOD5 model, we compared inversion results to observation results under low and moderate wind speed conditions (the observed wind speed is 3.4m/s and 8.7m/s). In conclusion, it is shown that three polarisation models can be applicable by acceptable error standard under different conditions. This study just gives a preliminary understanding of HH-to-VV polarisation models´ performance under different wind speed conditions.
Keywords
polarisation; radar cross-sections; radar imaging; synthetic aperture radar; wind; CMOD5 model; HH-polarized SAR images; HH-to-VV polarisation models; Hainan Island; Radarsat2 image mode data; normalized radar cross section; south China; wind speed; Decision support systems; Image retrieval; Information retrieval; Polarization; Wind speed; CMOD5; NRCS; polarisation model;
fLanguage
English
Publisher
ieee
Conference_Titel
Synthetic Aperture Radar, 2009. APSAR 2009. 2nd Asian-Pacific Conference on
Conference_Location
Xian, Shanxi
Print_ISBN
978-1-4244-2731-4
Electronic_ISBN
978-1-4244-2732-1
Type
conf
DOI
10.1109/APSAR.2009.5374106
Filename
5374106
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