1. College of Resources & Environmental Science, Xinjiang University, Urumqi 830046, China
2. Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
3. General Institutes of Higher Learning Key Laboratory of Smart City and Environmental Modeling, Xinjiang University, Urumqi 830046, China
4. Area Management Bureau of Ebinur Lake Wetland Natural Reserve, Bole 833400, China
Abstract：The chlorophyll can effectively monitoring vegetation growth status, currently the hyperspectral vegetation index (VI) is one of the common methods that have been widely applied to estimate the leaf chlorophyll content (LCC) inversion. Non-destructive rapid estimation of chlorophyll using hyperspectral remote sensing technology is a prerequisite to dynamically monitor chlorophyll content, and it is an important research issue of vegetation remote sensing. The author measured the leaf spectral reflectance and chlorophyll relative content of desert plants, analyzed the spectral curves of different desert plants under the same chlorophyll content, then transformed the SPAD value, compared Pearson and VIP methods to study the correlation between chlorophyll content and vegetation index of desert vegetation. Finally, the author selected the best fitting model from accuracy test. The results showed that: Based on the comparative analysis between Pearson and VIP, established the chlorophyll content estimation model by VIP method, selected 7 vegetation indices, which was NDVI705，ARVI，CIred edge，PRI，VARI，PSRI and NPCI respectively, the value of VIP all greater than 0.8, thus these 7 vegetation indices were the optimal vegetation indices. The prediction results indicated that the correlation of all models was more than 0.7, the best correlation between the predicted value and the measured value was the SPAD value of the reciprocal transformation, R=0.816, RMSE=0.007. The inversion model based on VIP method can estimate the chlorophyll content of vegetation in the study area, it provides an important theoretical basis and technical support for the practical application in the diagnosis of plant chlorophyll content.
Key words：Chlorophyll content; Vegetation index; Estimation model
李 哲，张 飞，陈丽华，张海威. 光谱指数的植物叶片叶绿素含量估算模型[J]. 光谱学与光谱分析, 2018, 38(05): 1533-1539.
LI Zhe, ZHANG Fei, CHEN Li-hua, ZHANG Hai-wei. Research on Spectrum Variance of Vegetation Leaves and Estimation Model for Leaf Chlorophyll Content Based on the Spectral Index. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1533-1539.
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