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《Acta Geodaetica et Cartographica Sinica》 2006-03
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The BP Neural Network Classification Based on the Fusion of SAR and TM Images

ZHANG Hai-long~1,JIANG Jian-jun~1,WU Hong-an~1,XIE xiu-ping~2(1.The College of Geographical Science,Nanjing Normal University,Nanjing 210097,China;2.Institute of Earth Environment,Chinese Academy of Sciences,Xi'an 710075,China)  
The Radar SAR and Landsat TM images are selected as the experimental datum,after converting the DN value to backscatter coefficient and reflectance respectively,the improved SVR method is used to fuse the data.To compare with fusion result,the HIS,brovey and wavelet method are used in this article.Finally,the optimized back propagation model is used to classify the TM and the fusion images with the same training areas.The experiment results are analyzed in spectrum maintenance or in quantity and the accuracy of the classification,it shows that the improved SVR fusion method is superior to other commonly used fusion methods.
【Fund】: SustainableAgroecosystemManagementandDevelopmentofRural-UrbanInteractioninregionsandcitiesofChina(SUSDEV-CHINA)(ICA4-CT-2002-10004)
【CateGory Index】: TP183;TN957.51
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