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《System Sciences and Comprehensive Studies in Agriculture》 2005-01
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Study on the hyperspectral remote sensing estimation model for aboveground biomass of corn with canopy reflectance

SONG Kai-shan,ZHANG Bai,YU Lei,WANG Zong-ming (Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences,Changchun 130012, China)  
Canopy reflectance of corn is measured with ASD FieldSpec during different corn growth stages; and simultaneously, aboveground biomass are collected.The relationship between canopy reflectance and aboveground biomass are analyzed with single variant, multivariate regression and BP neural network.It found that reflectance in green waveband, red waveband and red edge region have direct relation to corn aboveground biomass while reflectance in other wavelength have a loose relation to corn aboveground biomass in different growing stages.By our study, it found that hyperspectral remote sensing reflectance could greatly improve remote sensing ability for estimation corn aboveground biomass.By comparison, it can be drawn that BP neural network is the best method for estimating corn aboveground biomass with remote sensing data.
【Fund】: 中国科学院知识创新工程重大项目(KZCX1-SW-19)
【CateGory Index】: S513.01
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