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
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