• DocumentCode
    790563
  • Title

    Quantitative analysis of RADARSAT SAR data over a sparse forest canopy

  • Author

    Magagi, Ramata ; Bernier, Monique ; Ung, Chhun-Huor

  • Author_Institution
    INRS-Eau, Sainte-Foy, Que., Canada
  • Volume
    40
  • Issue
    6
  • fYear
    2002
  • fDate
    6/1/2002 12:00:00 AM
  • Firstpage
    1301
  • Lastpage
    1313
  • Abstract
    This article studies the behavior of the backscattering coefficient of a sparse forest canopy composed of relatively short black spruce trees. Qualitative analysis of the multiangular data measured by the RADARSAT synthetic aperture radar (SAR) sensor shows a good agreement with surface and vegetation volume scattering fundamental behaviors. For a quantitative analysis, allometric equations and measurements of tree components collected within the framework of the Extended Collaboration to Link Ecophysiology and Forest Productivity (ECOLEAP) project are used, in an existing multilayer radiative transfer model for forest canopies, to simulate the RADARSAT SAR data. In our approach, the fractional cover of trees estimated from aerial photographs is used as a weighting parameter to adapt the closed-canopy backscattering model to the sparse forest under study. Our objective is to analyze the sensitivity of the backscattering coefficient as a function of sensor configuration, soil wetness, forest cover, and forest structural properties in order to determine the suitable soil, vegetation, and sensor parameters for a given thematic application. For the entire incidence angle domain (20° to 50°) of the sensor, simulations show that over a sparse forest composed of mature trees the monitoring of the ground surface is possible only under very wet soil conditions. Therefore, this article informs about the ability of the RADARSAT SAR sensor in monitoring wetlands.
  • Keywords
    backscatter; forestry; geophysical techniques; radar cross-sections; radar theory; remote sensing by radar; synthetic aperture radar; vegetation mapping; 5.3 GHz; C-band; Canada; ECOLEAP; Picea mariana; Quebec; RADARSAT; SAR; allometric equations; backscattering coefficient; black spruce; forest; fractional cover; geophysical measurement technique; mature trees; model; quantitative analysis; radar remote sensing; radar scattering; simulations; sparse canopy; synthetic aperture radar; trees; vegetation mapping; volume scattering; wetlands; Backscatter; Collaboration; Equations; Nonhomogeneous media; Productivity; Radar scattering; Soil; Synthetic aperture radar; Vegetation; Volume measurement;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2002.800235
  • Filename
    1020262