DocumentCode
2188767
Title
Thermal front retreivals from SAR imagery
Author
Kuang, Hai-lan ; Perrie, William ; Chen, Wei ; Xie, Tao ; Liu, Xin-hua ; Zhang, Biao
Author_Institution
Key Lab. of Broadband Wireless Commun. & Sensor Networks, Wuhan Univ. of Technol., Wuhan, China
fYear
2012
fDate
22-27 July 2012
Firstpage
2637
Lastpage
2640
Abstract
Based on linear statistical relationships between components of SST gradients and wind stress variations, a high-resolution methodology is presented to retrieve Gulf Stream thermal front features using only variations in pixel-scale features of the SAR-derived wind stress divergence and curl fields, representing a significant improvement in methodology. It is important to remove small-scale features in divergence and curl wind stress images before they are used to construct the thermal front parameter, TF. We also verified the results with another 42 RADARSAT-2 images acquired at dual-polarization (VV, VH) image mode in the Gulf Stream region. Results indicates that the proposed method works well when retrieved wind speed lies between 5 m/s and 12 m/s, because SST-induced wind gradients can modify the vorticity and divergence fields [O´Neill et al. 2010].
Keywords
geophysical image processing; image resolution; image retrieval; ocean temperature; oceanographic regions; oceanographic techniques; radar imaging; remote sensing by radar; synthetic aperture radar; wind; Gulf Stream region; Gulf Stream thermal front retrieval; RADARSAT-2 images; SAR image; SAR-derived wind stress divergence; SST gradients; SST-induced wind gradients; curl fields; curl wind stress images; divergence field; divergence wind stress images; dual-polarization image; high-resolution methodology; linear statistical relationships; small-scale features; thermal front parameter; vorticity field; wind stress variations; Ocean temperature; Sea surface; Streaming media; Stress; Synthetic aperture radar; Wind;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6350387
Filename
6350387
Link To Document