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《Science of Surveying and Mapping》 2010-05
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Remote sensing information extraction based on object-oriented and support vector machines

XIAO Ao①,ZHAO Wen-ji①,HU De-yong①,LIU Lian-gang②,LI Jia-cun①(①Key Laboratory of 3D Information Acquisition and Applicatioin of Ministry of Education,College of Resource Environment&Tourism,Capital Normal University,Beijing 100048,China;②Beijing Institute of Geology,Beijing 100120,China)  
It is the important for remote sensing image processing to quickly,efficiently and accurately extract the land use/cover information.Traditional remote sensing classification makes use of the single-source spectral information to extract the land use/cover information without spatial information.In this paper,Object-oriented and Support Vector Machines are incorporated to extract the land use/cover information with spectral and texture information.Object-SVM model is set up for the extraction of land use/cover information in area coverage,comparing with Object-oriented fuzzy logic and SVM based on pixels.The research shows that Object-SVM can achieve better accuracies and efficiencies for actual applications.
【Fund】: 国家科技支撑计划课题“环北京区域地表环境遥感动态监测与评价技术研究”(2007BAH15B02) 国家科技支撑计划重点(2006BAC08B02);; 空间数据挖掘与信息共享教育部重点实验室开放基金“基于对象和SVM的遥感图像分类及精度分析”
【CateGory Index】: TP751
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【Citations】
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【Co-citations】
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