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Article: Integration of principal components analysis and cellular automata for spatial decisionmaking and urban simulation

TitleIntegration of principal components analysis and cellular automata for spatial decisionmaking and urban simulation
Authors
Li, XYeh, GO
KeywordsCellular automata
Geographical information systems
Principal components analysis
Urban simulation
Issue Date2002
PublisherScience in China Press. The Journal's web site is located at http://link.springer.com.eproxy1.lib.hku.hk/journal/11430
Citation
Science In China, Series D: Earth Sciences, 2002, v. 45 n. 6, p. 521-529 How to Cite?
DOI: http://dx.doi.org/10.1360/02yd9054
AbstractThis paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause the malfunction of MCE. In urban simulation, spatial factors often exhibit a high degree of correlation which is considered as an undesirable property for MCE. This study uses principal components analysis (PCA) to remove data redundancy among a large set of spatial variables and determine 'ideal points' for land development. PCA is integrated with cellular automata and geographical information systems (GIS) for the simulation of idealized urban forms for planning purposes.
Persistent Identifierhttp://hdl.handle.net/10722/89891
ISSN
1006-9313
2011 Impact Factor: 1.588
ISI Accession Number ID
WOS:000175593200005
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorLi, Xen_HK
dc.contributor.authorYeh, GOen_HK
dc.date.accessioned2010-09-06T10:03:04Z-
dc.date.available2010-09-06T10:03:04Z-
dc.date.issued2002en_HK
dc.identifier.citationScience In China, Series D: Earth Sciences, 2002, v. 45 n. 6, p. 521-529en_HK
dc.identifier.issn1006-9313en_HK
dc.identifier.urihttp://hdl.handle.net/10722/89891-
dc.description.abstractThis paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause the malfunction of MCE. In urban simulation, spatial factors often exhibit a high degree of correlation which is considered as an undesirable property for MCE. This study uses principal components analysis (PCA) to remove data redundancy among a large set of spatial variables and determine 'ideal points' for land development. PCA is integrated with cellular automata and geographical information systems (GIS) for the simulation of idealized urban forms for planning purposes.en_HK
dc.languageengen_HK
dc.publisherScience in China Press. The Journal's web site is located at http://link.springer.com.eproxy1.lib.hku.hk/journal/11430en_HK
dc.relation.ispartofScience in China, Series D: Earth Sciencesen_HK
dc.subjectCellular automataen_HK
dc.subjectGeographical information systemsen_HK
dc.subjectPrincipal components analysisen_HK
dc.subjectUrban simulationen_HK
dc.titleIntegration of principal components analysis and cellular automata for spatial decisionmaking and urban simulationen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0036-8237&volume=45&issue=6&spage=521&epage=529&date=2002&atitle=Integration+of+principal+components+analysis+and+cellular+automata+for+spatial+decisionmaking+and+urban+simulationen_HK
dc.identifier.emailYeh, GO: hdxugoy@hkucc.hku.hken_HK
dc.identifier.authorityYeh, GO=rp01033en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1360/02yd9054-
dc.identifier.scopuseid_2-s2.0-0036618832en_HK
dc.identifier.hkuros78348en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036618832&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume45en_HK
dc.identifier.issue6en_HK
dc.identifier.spage521en_HK
dc.identifier.epage529en_HK
dc.identifier.isiWOS:000175593200005-
dc.publisher.placeChinaen_HK
dc.identifier.scopusauthoridLi, X=34872691500en_HK
dc.identifier.scopusauthoridYeh, GO=7103069369en_HK
dc.identifier.issnl1006-9313-

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