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
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;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1027226