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《Science of Surveying and Mapping》 2008-S3
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BP neural network usedin classfication of land cover

YU Feng-ming①,ZHUO Yi②,BAO Yu-hai③(①Inner Mongolia Climate Center,Hohehot 010051,China; ②Remote Sensing and Geography Information System,Hohehot 010010,China; ③Glassland Research Institute of Chinese Academy of Agricultural Sciences,Hohehot 010022,China)  
This article has regarded matlab as the platform and designed BP neural network procedure ,thus used for drawing surface feature information automatically from the remote sensing image ,that this kind of method not only can be applied to the high-resolution remote sensing image of the micro area,can also apply to the low resolution ratio remote sensing image of the macroscopical area has been proved in the experiment. This article carry on the test for MODIS images with 1000 meters resolution and ETM images with 15 meter resolution,the inspection result of the precision shows ,the overall-accuracy is higher than 70% ,kappa coefficient is higher than 70%. While classifying MODIS image ,have dealt with MODIS image in the whole year of 2006 into the array collection of exponential time from EVI vegetation index,uesing the exponential time on land use classify is the front where recent land utilizes the categorised method to study.
【CateGory Index】: F301;P237
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