• DocumentCode
    2228223
  • Title

    Contribution of TerraSAR-X radar images texture for forest monitoring

  • Author

    Benelcadi, H. ; Frison, P. -L ; Lardeux, C. ; Capel, A. -C ; Routier, J. -B ; Rudant, J. -P

  • Author_Institution
    Lab. ESYCOM, Univ. of Paris-Est Marne-la-Vallee, Champs sur Marne, France
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6427
  • Lastpage
    6430
  • Abstract
    This study aims to evaluate the texture analysis of high spatial resolution images for mapping tropical forests. More precisely, it evaluates the potential of TerraSAR-X image, with spatial resolution of 0.5 meter for the classification of tropical forests located in southern Cambodia. In particular, the focus is put on the contribution of the analysis of textural information for classification. This latter is apprehended through the analysis of Haralick textural parameters. The retained algorithm of classification is the Support Vector Machine, as it allows taking into account numerous parameters, which can be heterogeneous with respect to their physical dimension. First results show that the addition of Haralick parameters to intensity channel may improve significantly the accuracy of the classification results. However, their performance for classification discrimination strongly depends on the size of the neighborhood from which they are estimated. Preliminary analysis of variograms allows optimizing the choice of the neighborhood size. Best results are obtained with a 25×25 sliding window size, with a classification accuracy improvement higher than 50% is observed.
  • Keywords
    forestry; geophysical image processing; image classification; image resolution; image texture; radar imaging; remote sensing by radar; support vector machines; synthetic aperture radar; vegetation mapping; Haralick textural parameters; TerraSAR-X radar image texture; classification discrimination analysis; forest monitoring; high spatial resolution images; southern Cambodia; support vector machine; textural information analysis; tropical forest classification; tropical forest mapping; variogram analysis; Accuracy; Biomass; Carbon; Spatial resolution; Support vector machines; Synthetic aperture radar; Vegetation mapping; Haralick; REDD+; SAR; SVM; TerraSAR-X; Texture; Tropical forest; Variogram;
  • 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.2012.6352130
  • Filename
    6352130