• DocumentCode
    1301683
  • Title

    Applying the Freeman–Durden Decomposition Concept to Polarimetric SAR Interferometry

  • Author

    Ballester-Berman, J. David ; Lopez-Sanchez, Juan M.

  • Author_Institution
    Syst. & Telecommun. Group, Univ. of Alicante, Alicante, Spain
  • Volume
    48
  • Issue
    1
  • fYear
    2010
  • Firstpage
    466
  • Lastpage
    479
  • Abstract
    In this paper, the Freeman-Durden polarimetric decomposition concept is adapted to polarimetric SAR interferometry (PolInSAR) data. The covariance matrix obtained from PolInSAR observations is decomposed into the three scattering mechanisms matrices proposed by Freeman and Durden for polarimetric SAR (PolSAR) data. The objective is to describe each interferometric cross correlation as the sum of the contributions corresponding to direct, double-bounce, and random volume scattering processes. This procedure enables the retrieval not only of the magnitude associated with each mechanism but also of their location along the vertical dimension of the scene. One of the most important features of this algorithm is the potential to isolate more accurately the direct and volume contributions which usually cannot be correctly separated by means of PolSAR measurements. In addition, it is also possible to distinguish between direct scattering responses originated either at ground or produced by upper layers of vegetation. The proposed algorithm has been tested with simulated data from PolSARProSim software, laboratory data from maize and rice samples, and airborne data from a test site with different scenarios.
  • Keywords
    covariance matrices; data analysis; geophysics computing; radar interferometry; radar polarimetry; synthetic aperture radar; Freeman-Durden decomposition concept; PolInSAR data; PolSARProSim software; covariance matrix; interferometric cross correlation; maize; polarimetric SAR interferometry; rice; scattering mechanisms; Parameter retrieval; polarimetric SAR interferometry (PolInSAR); target decomposition (TD); vegetation;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2009.2024304
  • Filename
    5208316