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《Geomatics & Spatial Information Technology》 2015-03
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Application of Aerial Image Classification in the Geographical Condition Monitoring

YIN Fan;PENG Shu-biao;LU Gang;Jiangsu Provincial Academy of Surveying and Mapping Engineering,Key Laboratory of Satellite Mapping Technology and Application State Bureau of Surveying and Mapping;  
The extraction of vegetation information from aerial imagery is the difficulty in the classification of remote sensing images,using only spectral information is difficult to extract the type of farmland. In this paper,taking Jiangsu as a typical area of farmland covers the major as the research object,select the image using the random forest algorithm to extract the information of different farmland. This study adopts multi-scale segmentation method,the feature information extraction of object oriented. According to the spectral,texture and shape features selected features more suitable as a parameter,the realization of the two class classification of vegetation using random forest algorithm,the classification accuracy of 84. 60%,KAPPA coefficient is 0. 753,which can provide some reference for the geographical conditions of production.
【Fund】: 江苏省测绘科研基金(JSCHKY201216);; 对地观测技术国家测绘地理信息局开放基金(k201211);; 国家科技支撑计划项目地理国情监测应用服务(2012BAH28B04)资助
【CateGory Index】: P231
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