Multisource data fusion for landslide classification using generalized positive Boolean functions

NCUIR > Research Center > Center for Space and Remote Sensing Research > journal & Dissertation > Item 987654321/35877

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/35877

Title:	Multisource data fusion for landslide classification using generalized positive Boolean functions
Authors:	Chang,Yang-Lang;Liang,Long-Shin;Han,Chin-Chuan;Fang,Jyh-Perng;Liang,Wen-Yew;Chen,Kun-Shan
Contributors:	太空及遙測研究中心
Keywords:	HYPERSPECTRAL IMAGE CLASSIFICATION;SUBSPACE PROJECTION APPROACH;ABSOLUTE ERROR CRITERION;REMOTE-SENSING IMAGES;STACK FILTERS;MORPHOLOGICAL FILTERS;MULTISENSOR APPROACH;DECISION FUSION;SENSED DATA;DECOMPOSITION
Date:	2007
Issue Date:	2010-07-07 15:53:09 (UTC+8)
Publisher:	中央大學
Abstract:	In this paper, a novel technique is proposed for a supervised classification of multisource images for the purpose of landslide hazard assessment. The method, known as the generalized positive Boolean function (GPBF), is developed for land cover classific
Relation:	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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