作者:Yan, GJ (Yan, Guangjian)[ 1 ] ; Hu, RH (Hu, Ronghai)[ 1 ] ; Wang, YT (Wang, Yiting)[ 2,3 ] ; Ren, HZ (Ren, Huazhong)[ 4 ] ; Song, WJ (Song, Wanjuan)[ 1 ] ; Qi, JB (Qi, Jianbo)[ 1 ] ; Chen, L (Chen, Ling)[ 5 ]

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

卷: 54  期: 6  页: 3475-3484

DOI: 10.1109/TGRS.2016.2519098

出版年: JUN 2016

摘要

Scale effect, which is caused by a combination of model nonlinearity and surface heterogeneity, has been of interest to the remote sensing community for decades. However, there is no current analysis of scale effect in the ground-based indirect measurement of leaf area index (LAI), where model nonlinearity and surface heterogeneity also exist. This paper examines the scale effect on the indirect measurement of LAI. We built multiscale data sets based on realistic scenes and field measurements. We then implemented five representative methods of indirect LAI measurement at scales (segment lengths) that range from meters to hundreds of meters. The results show varying degrees of deviation and fluctuation that exist in all five methods when the segment length is shorter than 20 m. The retrieved LAI from either Beer's law or the gap-size distribution method shows a decreasing trend with increasing segment lengths. The length at which the LAI values begin to stabilize is about a full period of row in row crops and 100 m in broadleaf or coniferous forests. The impacts of segment length on the finite-length averaging method, the combination of gap-size distribution and finite-lengthmethods, and the path-length distribution method are relatively small. These three methods stabilize at the segment scale longer than 20 m in all scenes. We also find that computing the average LAI of all of the short segment lengths, which is commonly done, is not as good as merging these short segments into a longer one and computing the LAI value of the merged one.

通讯作者地址: Hu, RH (通讯作者)

Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China

[ 2 ] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 3 ] Natl Marine Data & Informat Serv, Tianjin 300171, Peoples R China

[ 4 ] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Sch Earth & Space Sci, Beijing 100871, Peoples R China

[ 5 ] Beijing Forestry Univ, Sch Forestry, Key Lab Silviculture & Conservat, Minist Educ, Beijing 100083, Peoples R China