COASTAL WETLAND CLASSIFICATION BASED ON HIGH RESOLUTION SAR AND OPTICAL IMAGE FUSION

doi:10.1109/IGARSS.2016.7729224

	COASTAL WETLAND CLASSIFICATION BASED ON HIGH RESOLUTION SAR AND OPTICAL IMAGE FUSION
	Yang Junfang 1,2; Ren Guangbo 2; Ma Yi 2; Fan Yanguo 1
	2016
关键词	GF-1 SAR image fusion SVM coastal wetland
DOI	10.1109/IGARSS.2016.7729224
页码	886-889
英文摘要	In this paper, the data source are GF-1 WFV image and Radarsat-2 SAR image covering the Yellow River Estuary wetland eastern area. The paper first uses Gram-Schmidt algorithm for fusing GF-1 image and different polarimetric mode SAR images, and then uses the method of SVM for supervised classification. Finally, the accuracy of the classification results and the capacity of information extraction are compared. The experiment results show:(1) the classification accuracy of fusing the VV polarimetric mode of SAR image and GF-1 image is better than other fusion image, reaching 83.78%, closing to the classification accuracy of GF-1 image. The classification accuracy of tidal flat reed in VV polarimetric fusion image is better than that of GF-1.(2) Tidal flat, river and aquaculture pond have the highest classification accuracy in all the fusion images.
会议录	2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
资助项目	Fundamental Research Funds Project of The First Institute of Oceanography, SOA[2013G21]
WOS研究方向	Engineering ; Geology ; Remote Sensing
WOS记录号	WOS:000388114601004
WOS关键词	LANDSAT-TM
内容类型	会议论文
源URL	[http://ir.fio.com.cn:8080/handle/2SI8HI0U/27148]
专题	自然资源部第一海洋研究所
通讯作者	Ren Guangbo
作者单位	1.China Univ Petr, Sch Geosci, Qingdao 266061, Peoples R China 2.SOA, Inst Oceanog 1, Qingdao 266061, Peoples R China
推荐引用方式 GB/T 7714	Yang Junfang,Ren Guangbo,Ma Yi,et al. COASTAL WETLAND CLASSIFICATION BASED ON HIGH RESOLUTION SAR AND OPTICAL IMAGE FUSION[C]. 见:.