• DocumentCode
    2110187
  • Title

    Object based analysis of polarimetric SAR data in alpha-entropy-anisotropy decomposition using fuzzy classification by eCognition

  • Author

    Benz, Ursula ; Pottier, Eric

  • Author_Institution
    DEFiNiENS AG, Munich, Germany
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1427
  • Abstract
    Polarimetric SAR data possess a high potential for classification of the Earth surface. Various publications demonstrate detailed analysis of soil and vegetation properties and characteristics of man made structures on selected examples. To ensure wider application of these developments, integration in commercial systems should be studied. In a first approach, the object based image analysis eCognition is employed on alpha, entropy and anisotropy and the span of fully polarimetric L-band SAR data of the German airborne sensor, E-SAR. We show that by using eCognition land cover classes can be conveniently assigned to the scattering classes and ambiguities can be resolved by geometric and context object features
  • Keywords
    radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; vegetation mapping; E-SAR; Earth surface; German airborne sensor; alpha-entropy-anisotropy decomposition; context object features; eCognition; fuzzy classification; geometric features; land cover classes; object based image analysis; polarimetric L-band SAR data; scattering classes; soil properties; vegetation properties; Anisotropic magnetoresistance; Data mining; Earth; Eigenvalues and eigenfunctions; Entropy; Image analysis; Matrix decomposition; Radar scattering; Remote sensing; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    0-7803-7031-7
  • Type

    conf

  • DOI
    10.1109/IGARSS.2001.976867
  • Filename
    976867