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Remote Sensing Technology and Application  2007, Vol. 22 Issue (4): 492-496    DOI: 10.11873/j.issn.1004-0323.2007.4.492
    
Contrastive Analysis Based on Neural Network of Winter Wheat's Chlorophyll Concentration Inversion with Hyperspectral Data
SUN Yan-xin1,2,3, WANG Ji-hua2, LI Bao-guo1, LIU Liang-yun2,HUANG Wen-jiang2, ZHAO Chun-jiang2
(1.College of Resource and Environment,China Agriculutre University,Beijing100094,China;2.National Engineering Research Center for Information Technology in Agriculture,Beijing100097,China; 3.Institute of Plant Nutrition and Resource,Beijing Academy of Agricultural and Forestry Sciences,Beijing100097,China)
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Abstract  

Based on winter wheat' s canopy spectra data,the spectral parameters which are selected by linear regression method and Generalization Regression Neural Network(GRNN) method is as network input, canpoy chlorophyll Concentration as network output,we use three models,linear regression model, Back Propagation neural network(BPNN)and GRNN to inverse chlorophyll concentration. The result shows BPNN and GRNN have higher estimation precision than linear regression model, the RMSEP are 0.52、0.36 and 0.98 respectively. Due to adapation to small sample study and needless iterate repeatly, GRNN' s froecast abality,generalization and study speed is better than BPNN.

Key words:  Hyperspectral remote sensing      Neural network      Genertic algorithm      Chlorophyll inversion     
Received:  15 November 2006      Published:  25 November 2011
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SUN Yan-xin, WANG Ji-hua, LI Bao-guo, LIU Liang-yun,HUANG Wen-jiang. Contrastive Analysis Based on Neural Network of Winter Wheat's Chlorophyll Concentration Inversion with Hyperspectral Data. Remote Sensing Technology and Application, 2007, 22(4): 492-496.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2007.4.492     OR     http://www.rsta.ac.cn/EN/Y2007/V22/I4/492

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