文献类型：期刊文献

英文题名：Estimating zero-plane displacement height and aerodynamic roughness length using synthesis of LiDAR and SPOT-5 data

作者：Tian, X.[1,2] Li, Z. Y.[1] van der Tol, C.[2] Su, Z.[2] Li, X.[3] He, Q. S.[4] Bao, Y. F.[4,5] Chen, E. X.[1] Li, L. H.[2]

第一作者：Tian, X.;田昕

通信作者：Tian, X[1]

机构：[1]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Univ Twente, Fac Geoinformat Sci & Earth Observat, NL-7500 AA Enschede, Netherlands;[3]Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China;[4]Chinese Acad Sci, Inst Remote Sensing Applicat, Beijing 100101, Peoples R China;[5]Beijing Inst Space Mech & Elect, Beijing 100190, Peoples R China

年份：2011

卷号：115

期号：9

起止页码：2330-2341

外文期刊名：REMOTE SENSING OF ENVIRONMENT

收录：;EI(收录号：20112414065587);Scopus(收录号：2-s2.0-80955178393);WOS:【SCI-EXPANDED(收录号:WOS:000292484400013)】；

基金：This study is financially supported by the Active Remote Sensing Model and Forest Structure Information Extraction (grant 2007CB714404) project under the framework of National Basic Research Program of China (973 Program). The data used in the paper are obtained from the Watershed Allied Telemetry Experimental Research (WATER), which is jointly supported by the Chinese State Key Basic Research Project (grant 2007CB714400) and the Chinese Academy of Sciences Action Plan for West Development Program (grant KZCX2-KB2-09). We thank the joint experimental team for providing all the supports for carrying out the campaign. The other WATER campaign participants from Cold and Arid Regions Environmental and Engineering Research Institute are acknowledged for collecting and pre-processing the eddy covariance data.

语种：英文

外文关键词：Zero-plane displacement; Aerodynamic roughness length; WATER campaign; LiDAR; SPOT-5; Eddy covariance

摘要：In this study, a combination of low and high density airborne LiDAR and satellite SPOT-5 HRG data were used in conjunction with ground measurements of forest structure to parameterize four models for zero-plane displacement height d(m) and aerodynamic roughness length z(0m)(m), over cool-temperate forests in Heihe River basin, an arid region of Northwest China. For the whole study area, forest structural parameters including tree height (Ht) (m), first branch height (FBH) (m), crown width (ON) (m) and stand density (SD) (trees ha(-1)) were derived by stepwise multiple linear regressions of ground-based forest measurements and height quantiles and fractional canopy cover (f(c)) derived from the low density LiDAR data. The high density LiDAR data, which covered a much smaller area than the low density LiDAR data, were used to relate SPOT-5's reflectance to the effective plant area index (PAIe) of the forest. This was done by linear spectrum decomposition and Li-Strahler geometric-optical models. The result of the SPOT-5 spectrum decomposition was applied to the whole area to calculate PAIe (and leaf area index LAI). Then, four roughness models were applied to the study area with these vegetation data derived from the LiDAR and SPOT-5 as input. For validation, measurements at an eddy covariance site in the study area were used. Finally, the four models were compared by plotting histograms of the accumulative distribution of modeled d and z(0m) in the study area. The results showed that the model using by frontal area index (FAI) produced best d estimate, and the model using both LAI and FM generated the best z(0m). Furthermore, all models performed much better when the representative tree height was Lorey's mean height instead of using an arithmetic mean. (C) 2011 Elsevier Inc. All rights reserved.