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《Computer Engineering and Applications》 2006-31
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Analysis of Vegetation Spectral Features Based on Hyperspectral Imaging Data

YANG Ke-ming1,GUO Da-zhi1,CHEN Yun-hao2 (1.Institute of Survey and Land Science,China University of Mining & Technology(Beijing),Beijing 100083,China; 2.Institute of Resources Sciences,Beijing Normal University,Beijing 100875,China)  
This paper analyzes the spectral reflected features and diagnostic absorption features of vegetation based on the hyperspectral imaging data,and describes the probability of recognizing plant species and predicting its biochemical concentrations like the macronutrients in terms of the vegetation spectral features and the continuum-removed absorption features.By use of First Derivative Reflectance(FDR) and some variables derived from continuum-removed absorption features such as Band Depth(BD),Continuum-Removed Derivative Reflectance(CRDR),Band Depth Ratio(BDR),Nor-malized Band Depth Index(NBDI) and so on,also utilizing selected wavelengths by stepwise linear regression model according to the variables from the spectral absorption features,and combining correlation analysis,the vegetation canopy biochemicals can be predicted.
【Fund】: 国防科技工业民用专项科研技术研究项目;; 国家基础测绘经费资助项目
【CateGory Index】: TP75
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