熊川等:Simulating polarized light scattering in terrestrial snow based on bicontinuous random medium and Monte Carlo ray tracing
被阅读 1922 次
2014-04-08

Simulating polarized light scattering in terrestrial snow based on bicontinuous random medium and Monte Carlo ray tracing
作者:Xiong, C (Xiong, Chuan)[ 1,2,3 ] ; Shi, JC (Shi, Jiancheng)[ 1,2 ]
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
卷: 133  页: 177-189
DOI: 10.1016/j.jqsrt.2013.07.026
出版年: JAN 2014

摘要
To date, the light scattering models of snow consider very little about the real snow microstructures. The ideal spherical or other single shaped particle assumptions in previous snow light scattering models can cause error in light scattering modeling of snow and further cause errors in remote sensing inversion algorithms. This paper tries to build up a snow polarized reflectance model based on bicontinuous medium, with which the real snow microstructure is considered. The accurate specific surface area of bicontinuous medium can be analytically derived. The polarized Monte Carlo ray tracing technique is applied to the computer generated bicontinuous medium. With proper algorithms, the snow surface albedo, bidirectional reflectance distribution function (BRDF) and polarized BRDF can be simulated. The validation of model predicted spectral albedo and bidirectional reflectance factor (BRF) using experiment data shows good results. The relationship between snow surface albedo and snow specific surface area (SSA) were predicted, and this relationship can be used for future improvement of snow specific surface area (SSA) inversion algorithms. The model predicted polarized reflectance is validated and proved accurate, which can be further applied in polarized remote sensing. (C) 2013 Elsevier Ltd. All rights reserved.

通讯作者地址: Shi, JC (通讯作者)
Chinese Acad Sci, Jointly Sponsored Inst Remote Sensing & Digital E, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Jointly Sponsored Inst Remote Sensing & Digital E, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
[ 2 ] Beijing Normal Univ, Beijing 100875, Peoples R China
[ 3 ] Univ Chinese Acad Sci, Beijing, Peoples R China