Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1 CCD data in Mu Us Sandland |
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Authors: | Chen Wei Cao ChunXiang He QiSheng Guo HuaDong Zhang Hao Li RenQiang Zheng Sheng Xu Min Gao MengXu Zhao Jian Li Sha Ni XiLiang Jia HuiCong Ji Wei Tian Rong Liu Cheng Zhao YuXing Li JingLu |
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Affiliation: | 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,China;2.Graduate University of Chinese Academy of Sciences,Beijing,China;3.Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing,China;4.China Key Laboratory of Ecological Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing,China;5.Ordos Forestry Sand Control Science Institute,Dongsheng,China;6.Inner Mongolia Biomass Thermoelectricity Limited Company,Wushen,China |
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Abstract: | 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 R 2 of 0.817 and a root-mean-squared error of 0.173. |
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