• DocumentCode
    143300
  • Title

    Wheat identifying in North China with RADARSAT-2 SAR data

  • Author

    Juan Xu ; Zhen Li ; Bangsen Tian

  • Author_Institution
    Key Lab. of Digital Earth Sci., Inst. of the Remote Sensing & Digital Earth, Beijing, China
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    2114
  • Lastpage
    2117
  • Abstract
    Compared with conventional single-polarization synthetic aperture radar (SAR), quad-polarimetric SAR observations provide more information and show potential for land cover classification. This paper evaluates the wheat identifying potential of quad-polarimetric SAR data. The fully polarimetric Radarsat-2 image for the Hebei province, China, is selected to evaluate the identification accuracy. Experimental results indicate that HH with HH-HV is the optimal linear polarization combination, with an accuracy of up to 82.3%. The Freeman-Durden decomposition can discriminate wheat more effectively, with an accuracy of about 86.8%. The combination of the Freeman-Durden decomposition and the parameter H is the best method for wheat identification, with an accuracy of up to 90.5%.
  • Keywords
    geophysical image processing; geophysical techniques; image classification; land cover; remote sensing by radar; synthetic aperture radar; vegetation; Freeman-Durden decomposition; Hebei province; North China; RADARSAT-2 SAR data; conventional single-polarization SAR; fully polarimetric Radarsat-2 image; land cover classification; optimal linear polarization; quadpolarimetric SAR data; quadpolarimetric SAR observations; synthetic aperture radar; wheat identification; Accuracy; Agriculture; Backscatter; Remote sensing; Scattering; Synthetic aperture radar; Synthetic aperture radar; classification; indentify; wheat;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6946883
  • Filename
    6946883