吴晓丹等：Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: A case of MODIS albedo products preliminary validation over northern China
来源：发布时间：2016-10-14
Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: A case of MODIS albedo products preliminary validation over northern China
作者:Wu, XD (Wu, Xiaodan)[ 1,3 ] ; Wen, JG (Wen, Jianguang)[ 1,2 ] ; Xiao, Q (Xiao, Qing)[ 1 ] ; Liu, Q (Liu, Qiang)[ 4 ] ; Peng, JJ (Peng, Jingjing)[ 5 ] ; Dou, BC (Dou, Baocheng)[ 1 ] ; Li, XH (Li, Xiuhong)[ 4 ] ; You, DQ (You, Dongqin)[ 1 ] ; Tang, Y (Tang, Yong)[ 1 ] ; Liu, QH (Liu, Qinhuo)[ 1,2 ]
REMOTE SENSING OF ENVIRONMENT
卷: 184 页: 25-39
DOI: 10.1016/j.rse.2016.06.013
出版年: OCT 2016
摘要
To evaluate and improve the quality of coarse-pixel land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. The performance of albedo validation depends on the quality of ground-based albedo measurements at a corresponding coarse pixel scale, which can be conceptualized as the "truth" value of albedo at coarse-pixel scale. In this paper, a sampling strategy based on multiple nodes using wireless sensor network (WSN) technology, WSN-based albedo observation, is proposed. The WSN nodes are distributed in an optimal layout determined by a sequential selection method based on the representativeness of each sensor. The WSN dataset in this study includes 6 nodes. A method of weighting is used to upscale WSN node albedo to a coarse-pixel scale. The weights for each node are calculated with the ordinary least squares (OLS) linear regression method. Compared with the multiple scale validation strategy, the dataset of WSN albedo "truth" at the coarse-pixel scale reveals a good quality both in stability and continuity. Application of this strategy is exemplified by validation of the MODIS 1 km albedo product. (C) 2016 Elsevier Inc All rights reserved.
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.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China
[ 3 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 4 ] Beijing Normal Univ, Beijing 100875, Peoples R China
[ 5 ] Peking Univ, Beijing 100871, Peoples R China
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