• DocumentCode
    1485003
  • Title

    Experimental and model investigation on radar classification capability

  • Author

    Ferrazzoli, Paolo ; Guerriero, Leila ; Schiavon, Giovanni

  • Author_Institution
    Dipt. di Inf. Sistemi e Produzione, Univ. Tor Vergata-Ingegneria, Rome, Italy
  • Volume
    37
  • Issue
    2
  • fYear
    1999
  • fDate
    3/1/1999 12:00:00 AM
  • Firstpage
    960
  • Lastpage
    968
  • Abstract
    The capability of multifrequency polarimetric synthetic aperture radar (SAR) to discriminate among nine vegetation classes is shown using both experimental data and model simulations. The experimental data were collected by the multifrequency polarimetric AIRSAR at the Dutch Flevoland site and the Italian Montespertoli site. Simulations are carried out using an electromagnetic model, developed at Tor Vergata University, Rome, Italy, which computes microwave vegetation scattering. The classes have been defined on the basis of geometrical differences among vegetation species, leading to different polarimetric signatures. It is demonstrated that, for each class, there are some combinations of frequencies and polarizations producing a significant separability. On the basis of this background, a simple, hierarchical parallelepiped algorithm is proposed
  • Keywords
    geophysical techniques; radar polarimetry; remote sensing by radar; synthetic aperture radar; vegetation mapping; Dutch Flevoland site; Holland; Italy; Montespertoli site; SAR; geophysical measurement technique; hierarchical parallelepiped algorithm; model simulation; multifrequency polarimetric radar; polarization; radar classification capability; radar polarimetry; radar remote sensing; synthetic aperture radar; vegetation class discrimination; vegetation mapping; Computational modeling; Electromagnetic modeling; Electromagnetic scattering; Electromagnetic wave polarization; Frequency; Polarimetric synthetic aperture radar; Radar polarimetry; Radar scattering; Synthetic aperture radar; Vegetation;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.752214
  • Filename
    752214