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Remote Sensing Technology and Application  2016, Vol. 31 Issue (4): 691-701    DOI: 10.11873/j.issn.1004-0323.2016.4.0691
    
Estimation of Corn LAI by Synergy Multi-spectral and SAR Remote Sensing Data based on Least Squares Method
Lin Yuefeng1,2,Liu Qiuhuo1,Li Jing1,Zhao Jing1
(1.State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and
Digital Earth,Chinese Academy of Sciences,Beijing 100101,China;
2.School of Resource and Environment,University of Electronic Science and
Technology of China,Chengdu 611731,China)
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Abstract  

As a result of different kinds of RS data containing varied information about green plants,to avoid the problem of low precision,the joint inversion model that constructed by the least squares method combined optical and radar remote sensing data such as Landsat8/OLI and Radarsat2 data was put forward to estimate LAI.And this research area was based on Remote Sensing Synthetic Experiment Station of Chinese Academy of Sciences in Huailai,Hebei Province and the research objects were maize.First of all,conventional method was used for remote sensing image preprocessing and then measured LAI was considered to build the empirical expressions between the extracted information from multi\|spectral data and radar data.Secondly,the least squares method that combined with Regression Model from different data was used to build the joint inversion model.At last,the joint inversion model was used to estimate the LAI based on iteration method and assess the result by the verification data.For comparison,the empirical model using vegetation index or backscattering coefficient as predicted variable,the weighted averaging model using multi\|source data and the Look\|up table method from physical model were also considered for LAI estimation.The result shows the better fit result was found between the predicted LAI from Partial Least Squares method and measured LAI (R2=0.5442,RMSE=0.81).Moreover,partial least squares method also couldimprove the overestimated and underestimated phenomenon from empirical method or weight fusion model due to the data quality,system error or saturation of remote sensing data.

Key words:  Leaf Area Index(LAI);Least squares algorithm;Landsat8 multi\      spectral data;Radarsat 2 microwave radar data;Iteration method     
Received:  10 August 2015      Published:  14 October 2016
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Lin Yuefeng
Liu Qiuhuo
Li Jing
Zhao Jing

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Lin Yuefeng,Liu Qiuhuo,Li Jing,Zhao Jing. Estimation of Corn LAI by Synergy Multi-spectral and SAR Remote Sensing Data based on Least Squares Method. Remote Sensing Technology and Application, 2016, 31(4): 691-701.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2016.4.0691     OR     http://www.rsta.ac.cn/EN/Y2016/V31/I4/691

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