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	Remote sensing data fusion using support vector machine
	Zhao, SH
	2004
关键词	SVM learning machine data fusion remote sensing data fusion CLASSIFICATION
英文摘要	The paper introduced support vector machine (SVM) into research of remote sensing data fusion, and a new approach of remote sensing data fusion based on SVM was Presented. Then to select a test area in Shaoxing City, Zhejiang Province, China, a data fusion experiment was conducted using Landsat TM multispectral data (30m) and SPOT-4 panchromatic (PAN) data (10m). The results show that the overall classification accuracy of the fusion data reached 76.8%. The new fusion method could detect effectively the ground objects, which haw close spectrum.; Geosciences, Multidisciplinary; Instruments & Instrumentation; Remote Sensing; Imaging Science & Photographic Technology; CPCI-S(ISTP); 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/312142]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Zhao, SH. Remote sensing data fusion using support vector machine. 2004-01-01.

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