Response of fuzzy clustering on different threshold determination algorithms in spectral change vector analysis over Western Himalaya, India

doi:10.1007/s11629-016-4248-0

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > Journal of Mountain Science > Journal of Mountain Science-2017 > Vol14 No.7

	Response of fuzzy clustering on different threshold determination algorithms in spectral change vector analysis over Western Himalaya, India
	SINGH Sartajvir; TALWAR Rajneesh
刊名	Journal of Mountain Science
	2017-07
卷号	14 期号:7 页码:1391-1404
关键词	Change Vector Analysis (Cva) Fuzzy Maximum Likelihood Classification (Fmlc) Double-window Flexible Pace Search (Dfps) Interactive Trial And Error (t&e) Pixel Kernel Window (Pkw)
ISSN号	1672-6316
DOI	10.1007/s11629-016-4248-0
通讯作者	SINGH Sartajvir
文献子类	期刊论文
英文摘要	Change detection is a standard tool to extract and analyze the earth's surface features from remotely sensed data. Among the different change detection techniques, change vector analysis (CVA) have an exceptional advantage of discriminating change in terms of change magnitude and vector direction from multispectral bands. The estimation of precise threshold is one of the most crucial task in CVA to separate the change pixels from unchanged pixels because overall assessment of change detection method is highly dependent on selected threshold value. In recent years, integration of fuzzy clustering and remotely sensed data have become appropriate and realistic choice for change detection applications. The novelty of the proposed model lies within use of fuzzy maximum likelihood classification (FMLC) as fuzzy clustering in CVA. The FMLC based CVA is implemented using diverse threshold determination algorithms such as double-window flexible pace search (DFPS), interactive trial and error (T&E), and 3×3‒pixel kernel window (PKW). Unlike existing CVA techniques, addition of fuzzy clustering in CVA permits each pixel to have multiple class categories and offers ease in threshold determination process. In present work, the comparative analysis has highlighted the performance of FMLC based CVA over improved SCVA both in terms of accuracy assessment and operational complexity. Among all the examined threshold searching algorithms, FMLC based CVA using DFPS algorithm is found to be the most efficient method.
语种	英语
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/18932]
专题	Journal of Mountain Science _Journal of Mountain Science-2017_Vol14 No.7
推荐引用方式 GB/T 7714	SINGH Sartajvir,TALWAR Rajneesh. Response of fuzzy clustering on different threshold determination algorithms in spectral change vector analysis over Western Himalaya, India[J]. Journal of Mountain Science,2017,14(7):1391-1404.
APA	SINGH Sartajvir,&TALWAR Rajneesh.(2017).Response of fuzzy clustering on different threshold determination algorithms in spectral change vector analysis over Western Himalaya, India.Journal of Mountain Science,14(7),1391-1404.
MLA	SINGH Sartajvir,et al."Response of fuzzy clustering on different threshold determination algorithms in spectral change vector analysis over Western Himalaya, India".Journal of Mountain Science 14.7(2017):1391-1404.