• 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