• DocumentCode
    765425
  • Title

    Herbaceous biomass retrieval in habitats of complex composition: a model merging SAR images with unmixed landsat TM data

  • Author

    Svoray, Tal ; Shoshany, Maxim

  • Author_Institution
    Dept. of Geogr. & Environ. Dev., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
  • Volume
    41
  • Issue
    7
  • fYear
    2003
  • fDate
    7/1/2003 12:00:00 AM
  • Firstpage
    1592
  • Lastpage
    1601
  • Abstract
    A remote sensing methodology for herbaceous areal above-ground biomass (AAB) estimation in a heterogeneous Mediterranean environment is presented. The methodology is based on an adaptation of the semiempirical water-cloud backscatter model to complex vegetation canopies combined with shrubs, dwarf shrubs, and herbaceous plants. The model included usage of the green leaf biomass volumetric density as a canopy descriptor and of cover fractions derived from unmixing Landsat Thematic Mapper image data for the three vegetation formations. The inclusion of the unmixed cover fractions improves modeling synthetic aperture radar backscatter, as it allows separation between the different radiation interaction mechanisms. The method was first assessed with reference to the reproduction of the backscatter from the vegetation formations. In the next phase, the accuracy of AAB retrievals from the backscatter data was evaluated. Results of testing the methodology in a region of climatic gradient in central Israel have shown a good correspondence between observed and predicted AAB values (R2=0.82). This indicates that the methodology developed may lay a basis for mapping important and more advanced ecological information such as primary production and contribute to better understanding of processes in Mediterranean and semiarid regions.
  • Keywords
    geophysical signal processing; geophysical techniques; image processing; radar imaging; remote sensing; remote sensing by radar; sensor fusion; synthetic aperture radar; 350 to 2500 nm; IR; Israel; Landsat TM; Mediterranean; SAR; backscatter; canopy; complex canopies; complex habitat; geophysical measurement technique; green leaf biomass; herbaceous biomass; image processing; infrared; merging; model; multispectral remote sensing; optical imaging; radar image; radar remote sensing; radar scattering; sensor fusion; shrubs; synthetic aperture radar; vegetation mapping; visible; volumetric density; Backscatter; Biomass; Image retrieval; Information retrieval; Merging; Production; Remote sensing; Satellites; Testing; Vegetation mapping;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2003.813351
  • Filename
    1221813