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《Science of Surveying and Mapping》 2019-01
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A method of combining the inversion of leaf area index

ZHU Jiaming;GUO Yunkai;LIU Haiyang;JIANG Ming;Transportation Engineering College/Institute of Surveying and Mapping and Remote Sensing Applied Technology,Changsha University of Science & Technology;  
Due to the disadvantages of the traditional PRO4 SAIL+look-up table method inversion of leaf area index,such as the large size of the look-up table and slow retrieval speed,a method based on combined model of PRO4 SAIL and local weighted multi-variable regression to invert the leaf area index was proposed.By using the spectral response function of the satellite sensor,the conversion of measured endmember hyper-spectral to pixel multi-spectral is realized,and the problem of the difference in reflectivity caused by different measurement scales is solved;Two vegetation index of leaf area index of MTVI1 and MCARI1 were selected as inversion factors,and only 40 sets of PRO4 SAIL model simulation data were used to establish a training group,which solve the problem of excessive data in the look-up table;The weighted distance formula of local weighted multi-variable regression expands from one-dimensional space to multidimensional space according to the number of inversion factors,which is more in line with practical application.The predictive coefficient of the combination model is 0.730 3,and the average relative error is 11.95%,the prediction coefficient of the traditional look-up table is 0.683 9,and the average relative error is 14.93%.The experimental results show that:the combined model has good predictive ability,and the accuracy of the leaf area index obtained by inversion is higher,which provides technical support for better monitoring of the road vegetation ecological environment.
【Fund】: 国家自然科学基金项目(41471421 41671498)
【CateGory Index】: X87
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