• Title of article

    Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties

  • Author/Authors

    Kِtz، نويسنده , , Benjamin and Schaepman، نويسنده , , Michael and Morsdorf، نويسنده , , Felix and Bowyer، نويسنده , , Paul and Itten، نويسنده , , Klaus and Allgِwer، نويسنده , , Britta، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2004
  • Pages
    13
  • From page
    332
  • To page
    344
  • Abstract
    Imaging spectrometer data were acquired over conifer stands to retrieve spatially distributed information on canopy structure and foliage water content, which may be used to assess fire risk and to manage the impact of forest fires. The study relied on a comprehensive field campaign using stratified systematic unaligned sampling ranging from full spectroradiometric characterization of the canopy to conventional measurements of biochemical and biophysical variables. Airborne imaging spectrometer data (DAIS7915 and ROSIS) were acquired parallel to the ground measurements, describing the canopy reflectance of the observed forest. Coniferous canopies are highly heterogeneous and thus the transfer of incident radiation within the canopy is dominated by its structure. We demonstrated the viability of radiative transfer representation and compared the performance of two hybrid canopy reflectance models, GeoSAIL and FLIGHT, within this heterogeneous medium. Despite the different nature and canopy representation of these models, they yielded similar results. Subsequently, the inversion of a hyperspectral GeoSAIL version demonstrated the feasibility of estimating structure and foliage water content of a coniferous canopy based on radiative transfer modeling. Estimates of the canopy variables showed reasonably accurate results and were validated through ground measurements.
  • Keywords
    coniferous canopy , Canopy structure , foliage water content , Imaging spectroscopy , radiative transfer , forest fire
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2004
  • Journal title
    Remote Sensing of Environment
  • Record number

    1574482