Unsupervised Object-Based Differencing for Land-Cover Change Detection

doi:10.1111/gcb.13372

CORC > 植物研究所 > 中国科学院植物研究所 > 植被与环境变化国家重点实验室

	Unsupervised Object-Based Differencing for Land-Cover Change Detection
	Zhu, Jinxia ; Su, Yanjun ; Guo, Qinghua 1; Harmon, Thomas C.
刊名	PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
	2017
卷号	83 期号:3 页码:225-236
ISSN号	0099-1112
DOI	10.1111/gcb.13372
文献子类	Article
英文摘要	One main problem of the spectral decomposition-based change detection method is the lack of efficient automatic techniques for developing the difference image. Traditional techniques generally assume that gray-level values in a difference image are independent and multitemporal images are co-registered/rectified perfectly without error. However, such assumptions are often violated because of the inevitable image misregistration and the interference of correlations between spectral bands. This study proposes an automated method based on the object-based multivariate alteration detection/maximum autocorrelation factor approach and the Gaussian mixture model-expectation maximization algorithm to obtain unsupervised difference images. This procedure is applied to bi-temporal (2005 and 2006) SPOT-HRV images at Panyu District Ponds, China. Results show that the proposed method successfully excludes the correlations of spectral bands and the influence of misregistration, as evidenced by a higher accuracy (up to 93.6 percent). These unique technical characteristics make this analytical framework suitable for detecting changes.
学科主题	Biodiversity & Conservation ; Environmental Sciences & Ecology
电子版国际标准刊号	2374-8079
出版地	BETHESDA
WOS关键词	CHANGE VECTOR ANALYSIS ; DIGITAL CHANGE DETECTION ; PRINCIPAL COMPONENT ANALYSIS ; REMOTELY-SENSED IMAGES ; RADIOMETRIC NORMALIZATION ; CLASSIFICATION ACCURACY ; MISREGISTRATION ; SATELLITE ; FRAMEWORK ; FUSION
语种	英语
出版者	AMER SOC PHOTOGRAMMETRY
WOS记录号	WOS:000390218300038
资助机构	Zhejiang Provincial Natural Science Foundation Of ChinaNatural Science Foundation of Zhejiang Province [LQ14D010003] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41501190] ; Zhejiang Provincial Social Science Foundation Of China [16NDJC145YB] ; Zhejiang Provincial Academy of Social Sciences of China [2015N076]
内容类型	期刊论文
源URL	[http://ir.ibcas.ac.cn/handle/2S10CLM1/22086]
专题	植被与环境变化国家重点实验室
作者单位	1.Su, Yanjun; Guo, Qinghua; Harmon, Thomas C.] Univ Calif Merced, Sierra Nevada Res Inst, Sch Engn, 5200 North Lake Rd, Merced, CA 95343 USA 2.Zhejiang Univ Finance & Econ, Inst Land & Urban Rural Dev, 18 Xueyuan Rd, Hangzhou 310019, Zhejiang, Peoples R China 3.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Jinxia,Su, Yanjun,Guo, Qinghua,et al. Unsupervised Object-Based Differencing for Land-Cover Change Detection[J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING,2017,83(3):225-236.
APA	Zhu, Jinxia,Su, Yanjun,Guo, Qinghua,&Harmon, Thomas C..(2017).Unsupervised Object-Based Differencing for Land-Cover Change Detection.PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING,83(3),225-236.
MLA	Zhu, Jinxia,et al."Unsupervised Object-Based Differencing for Land-Cover Change Detection".PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING 83.3(2017):225-236.