• DocumentCode
    2141851
  • Title

    Modeling the albedo of mixed vegetation canopy and snow

  • Author

    Jiang, Lingmei ; Yang, Hua ; Wang, Jindi ; Li, Xiaowen

  • Author_Institution
    Res. Center for Remote Sensing, Beijing Normal Univ., China
  • Volume
    6
  • fYear
    2002
  • fDate
    24-28 June 2002
  • Firstpage
    3492
  • Abstract
    Predictions of climate change typically use a GCM linked to a land surface model. Land surface models, e.g. Biosphere-Atmosphere Transfer Scheme (BATS), estimate the albedo of trees over snow roughly with the parameters of roughness length, z0, and snow depth, d. Based on their work, we further consider the difference in directional-to-hemisphere albedo for different solar zenith angle (SZA), and leaf area index (LAI) dependence. In order to keep the basic feature of the BATS model and to add these two new features, we simplified the geometric optical and radiative transfer (GORT) hybrid model of Li, et al. [1995] to reach this purpose. This model can be rather simple to retrieve the albedo of remote sensing pixel. It can be a strong tool to understand the climate system.
  • Keywords
    albedo; climatology; radiative transfer; snow; sunlight; BATS; Biosphere-Atmosphere Transfer Scheme; GCM; GORT hybrid model; albedo; climate change; directional-to-hemisphere albedo; geometric optical and radiative transfer hybrid model; land surface model; leaf area index; mixed vegetation canopy; remote sensing pixel; snow; solar zenith angle; trees; Biomedical optical imaging; Geometrical optics; Land surface; Optical sensors; Predictive models; Rough surfaces; Snow; Solid modeling; Surface roughness; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
  • Print_ISBN
    0-7803-7536-X
  • Type

    conf

  • DOI
    10.1109/IGARSS.2002.1027226
  • Filename
    1027226