摘要
The leaf area index(LAI) is an important ecological parameter that characterizes the interface between vegetation canopy and the atmosphere.In addition,it is used by most process-oriented ecosystem models.This paper investigates the potential of HJ-1 CCD data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of the shrub LAI in Wushen Banner of Inner Mongolia in the Mu Us Sandland.MODTRAN(Moderate Resolution Atmospheric Radiance and Transmittance Model) was used for atmospheric correction.Shrubland was extracted using the threshold of the normalized difference vegetation index,with which water bodies and farmland were separated,in combination with a vegetation map of the People's Republic of China(1:1000000).Using the geometric-optical model,we derive the per-pixel reflectance as a simple linear combination of two components,namely sunlit background and other.The fraction of sunlit background is related to the shrub LAI.With the support of HJ-1 CCD data,we employ linear spectral unmixing to obtain the fraction of sunlit background in an atmospherically corrected HJ image.In addition,we use the measured shrub canopy structural parameters for shrub communities to invert the geometric-optical model and retrieve the pixel-based shrub LAI.In total,18 sample plots collected in Wushen Banner of Inner Mongolia are used for validation.The results of the shrub LAI show good agreement with R2 of 0.817 and a root-mean-squared error of 0.173.
The leaf area index(LAI) is an important ecological parameter that characterizes the interface between vegetation canopy and the atmosphere.In addition,it is used by most process-oriented ecosystem models.This paper investigates the potential of HJ-1 CCD data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of the shrub LAI in Wushen Banner of Inner Mongolia in the Mu Us Sandland.MODTRAN(Moderate Resolution Atmospheric Radiance and Transmittance Model) was used for atmospheric correction.Shrubland was extracted using the threshold of the normalized difference vegetation index,with which water bodies and farmland were separated,in combination with a vegetation map of the People’s Republic of China(1:1000000).Using the geometric-optical model,we derive the per-pixel reflectance as a simple linear combination of two components,namely sunlit background and other.The fraction of sunlit background is related to the shrub LAI.With the support of HJ-1 CCD data,we employ linear spectral unmixing to obtain the fraction of sunlit background in an atmospherically corrected HJ image.In addition,we use the measured shrub canopy structural parameters for shrub communities to invert the geometric-optical model and retrieve the pixel-based shrub LAI.In total,18 sample plots collected in Wushen Banner of Inner Mongolia are used for validation.The results of the shrub LAI show good agreement with R2 of 0.817 and a root-mean-squared error of 0.173.
作者
CHEN Wei1,2,CAO ChunXiang1,HE QiSheng1,2,GUO HuaDong3,ZHANG Hao1,2,LI RenQiang4,ZHENG Sheng1,2,XU Min1,2,GAO MengXu1,2,ZHAO Jian1,2,LI Sha1,NI XiLiang1,2,JIA HuiCong1,JI Wei1,TIAN Rong1,2,LIU Cheng1,2,ZHAO YuXing5 & LI JingLu6 1 State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China
2 Graduate University of Chinese Academy of Sciences,Beijing 100049,China
3 Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing 100190,China
4 China Key Laboratory of Ecological Network Observation and Modeling,Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China
5 Ordos Forestry Sand Control Science Institute,Dongsheng 017000,China
6 Inner Mongolia Biomass Thermoelectricity Limited Company,Wushen 017300,China
基金
supported by National Natural Science Foundation of China (Grant No.40871173)
Special Grant for Prevention and Treatment of Infectious Diseases (Grant No.2008ZX10004-012)
National State Basic Research Program of China (Grant No. 2007CB714404)
