Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/620417
Title: Sea Surface Wind Speed Retrieval From TerraSAR-X HH Polarization Data Using an Improved Polarization Ratio Model
Authors: Weizeng Shao;Zheng Zhang;Xiaoming Li;Weili Wang
subject: wind speed|Polarization ratio (PR)|TerraSAR-X
Year: 2016
Publisher: IEEE
Abstract: The purpose of this study was to improve the accuracy of sea surface wind retrieval from the X-band spaceborne synthetic aperture radar (SAR) TerraSAR-X (TS-X) and TanDEM-X (TD-X) data in horizontal-horizontal (HH) polarization. Geophysical model functions (GMFs), e.g., XMOD1, XMOD2, and SIRX-MOD were developed for X-band SAR data in vertical-vertical (VV) polarization to retrieve sea surface wind fields. To date, the polarization ratio model for X-band SAR (XPR), which is only dependent on incidence angle, has only been available for sea surface wind retrieval from TS-X HH polarization images, in conjunction with an X-band GMF. In our previous study, it was found that the polarization ratio of TS-X dual-polarization data showed a particular relationship with sea surface wind speed. Therefore, in this study, we propose an improved X-band polarization ratio model, herein called XPR2, which is dependent on both incidence angle and sea surface wind speed. The XPR2 was tuned through 56 TS-X/TD-X dual-polarization (HH and VV polarization) images and the collocated European Centre for Medium-Range Weather Forecasts reanalysis wind data. The model was further validated by comparing the retrieved sea surface wind speed from another 38 TS-X HH polarization images against in situ buoy measurements. The comparison shows a root mean square error (RMSE) of 1.79 m/s and a bias of 0.68 m/s, which is better than the results achieved using the existing XPR with an RMSE of 2.31 m/s and a bias of 0.93 m/s.
URI: http://localhost/handle/Hannan/156327
http://localhost/handle/Hannan/620417
ISSN: 1939-1404
2151-1535
volume: 9
issue: 11
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7523267.pdf698.42 kBAdobe PDFThumbnail
Preview File
Title: Sea Surface Wind Speed Retrieval From TerraSAR-X HH Polarization Data Using an Improved Polarization Ratio Model
Authors: Weizeng Shao;Zheng Zhang;Xiaoming Li;Weili Wang
subject: wind speed|Polarization ratio (PR)|TerraSAR-X
Year: 2016
Publisher: IEEE
Abstract: The purpose of this study was to improve the accuracy of sea surface wind retrieval from the X-band spaceborne synthetic aperture radar (SAR) TerraSAR-X (TS-X) and TanDEM-X (TD-X) data in horizontal-horizontal (HH) polarization. Geophysical model functions (GMFs), e.g., XMOD1, XMOD2, and SIRX-MOD were developed for X-band SAR data in vertical-vertical (VV) polarization to retrieve sea surface wind fields. To date, the polarization ratio model for X-band SAR (XPR), which is only dependent on incidence angle, has only been available for sea surface wind retrieval from TS-X HH polarization images, in conjunction with an X-band GMF. In our previous study, it was found that the polarization ratio of TS-X dual-polarization data showed a particular relationship with sea surface wind speed. Therefore, in this study, we propose an improved X-band polarization ratio model, herein called XPR2, which is dependent on both incidence angle and sea surface wind speed. The XPR2 was tuned through 56 TS-X/TD-X dual-polarization (HH and VV polarization) images and the collocated European Centre for Medium-Range Weather Forecasts reanalysis wind data. The model was further validated by comparing the retrieved sea surface wind speed from another 38 TS-X HH polarization images against in situ buoy measurements. The comparison shows a root mean square error (RMSE) of 1.79 m/s and a bias of 0.68 m/s, which is better than the results achieved using the existing XPR with an RMSE of 2.31 m/s and a bias of 0.93 m/s.
URI: http://localhost/handle/Hannan/156327
http://localhost/handle/Hannan/620417
ISSN: 1939-1404
2151-1535
volume: 9
issue: 11
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7523267.pdf698.42 kBAdobe PDFThumbnail
Preview File
Title: Sea Surface Wind Speed Retrieval From TerraSAR-X HH Polarization Data Using an Improved Polarization Ratio Model
Authors: Weizeng Shao;Zheng Zhang;Xiaoming Li;Weili Wang
subject: wind speed|Polarization ratio (PR)|TerraSAR-X
Year: 2016
Publisher: IEEE
Abstract: The purpose of this study was to improve the accuracy of sea surface wind retrieval from the X-band spaceborne synthetic aperture radar (SAR) TerraSAR-X (TS-X) and TanDEM-X (TD-X) data in horizontal-horizontal (HH) polarization. Geophysical model functions (GMFs), e.g., XMOD1, XMOD2, and SIRX-MOD were developed for X-band SAR data in vertical-vertical (VV) polarization to retrieve sea surface wind fields. To date, the polarization ratio model for X-band SAR (XPR), which is only dependent on incidence angle, has only been available for sea surface wind retrieval from TS-X HH polarization images, in conjunction with an X-band GMF. In our previous study, it was found that the polarization ratio of TS-X dual-polarization data showed a particular relationship with sea surface wind speed. Therefore, in this study, we propose an improved X-band polarization ratio model, herein called XPR2, which is dependent on both incidence angle and sea surface wind speed. The XPR2 was tuned through 56 TS-X/TD-X dual-polarization (HH and VV polarization) images and the collocated European Centre for Medium-Range Weather Forecasts reanalysis wind data. The model was further validated by comparing the retrieved sea surface wind speed from another 38 TS-X HH polarization images against in situ buoy measurements. The comparison shows a root mean square error (RMSE) of 1.79 m/s and a bias of 0.68 m/s, which is better than the results achieved using the existing XPR with an RMSE of 2.31 m/s and a bias of 0.93 m/s.
URI: http://localhost/handle/Hannan/156327
http://localhost/handle/Hannan/620417
ISSN: 1939-1404
2151-1535
volume: 9
issue: 11
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7523267.pdf698.42 kBAdobe PDFThumbnail
Preview File