作者:Wen, JG (Wen, Jianguang)[ 1,2,3 ] ; Liu, Q (Liu, Qiang)[ 2,4 ] ; Xiao, Q (Xiao, Qing)[ 1,3 ] ; Liu, QH (Liu, Qinhuo)[ 1,2,3 ] ; You, DQ (You, Dongqin)[ 1,2 ] ; Hao, DL (Hao, Dalei)[ 1,3 ] ; Wu, SB (Wu, Shengbiao)[ 1,3 ] ; Lin, XW (Lin, Xingwen)[ 1,3 ]

REMOTE SENSING

卷: 10  期: 3

文献号: 370

DOI: 10.3390/rs10030370

出版年: MAR 2018

文献类型:Review

摘要

Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF) has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

通讯作者地址: Wen, JG (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

通讯作者地址: Wen, JG (通讯作者)

JCGCS, Beijing 100875, Peoples R China.

通讯作者地址: Wen, JG (通讯作者)

Univ Chinese Acad Sci, Beijing 100049, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] JCGCS, Beijing 100875, Peoples R China

[ 3 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[ 4 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China