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Article: Simulating land-use dynamics under planning policies by integrating artificial immune systems with cellular automata

TitleSimulating land-use dynamics under planning policies by integrating artificial immune systems with cellular automata
Authors
KeywordsArtificial immune system
Urban planning
Cellular automata
Urban simulation
Issue Date2010
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp
Citation
International Journal of Geographical Information Science, 2010, v. 24 n. 5, p. 783-802 How to Cite?
AbstractCellular automata (CA) have been increasingly used in simulating urban expansion and land-use dynamics. However, most urban CA models rely on empirical data for deriving transition rules, assuming that the historical trend will continue into the future. Such inertia CA models do not take into account possible external interventions, particularly planning policies, and thus have rarely been used in urban and land-use planning. This paper proposes to use artificial immune systems (AIS) as a technique for incorporating external interventions and generating alternatives in urban simulation. Inspired by biological immune systems, the primary process of AIS is the evolution of a set of 'antibodies' that are capable of learning through interactions with a set of sample 'antigens'. These 'antibodies' finally get 'matured' and can be used to identify/classify other 'antigens'. An AIS-based CA model incorporates planning policies by altering the evolution mechanism of the 'antibodies'. Such a model is capable of generating different scenarios of urban development under different land-use policies, with which the planners will be able to answer 'what if' questions and to evaluate different options. We applied an AIS-based CA model to the simulation of urban agglomeration development in the Pearl River Delta in southern China. Our experiments demonstrate that the proposed model can be very useful in exploring various planning scenarios of urban development.
Persistent Identifierhttp://hdl.handle.net/10722/131088
ISSN
2015 Impact Factor: 2.065
2015 SCImago Journal Rankings: 1.156
ISI Accession Number ID
Funding AgencyGrant Number
National Natural Science Foundation of China40901187
Key National Natural Science Foundation of China40830532
National Outstanding Youth Foundation of China40525002
LREIS, CAS4106298
Funding Information:

This study was supported by the National Natural Science Foundation of China (Grant No. 40901187), the Key National Natural Science Foundation of China (Grant No. 40830532), the National Outstanding Youth Foundation of China (Grant No. 40525002), and the Research Fund of LREIS, CAS (Grant No. 4106298).

 

DC FieldValueLanguage
dc.contributor.authorLiu, X-
dc.contributor.authorLi, X-
dc.contributor.authorShi, X-
dc.contributor.authorZhang, X-
dc.contributor.authorChen, Y-
dc.date.accessioned2011-01-28T02:05:08Z-
dc.date.available2011-01-28T02:05:08Z-
dc.date.issued2010-
dc.identifier.citationInternational Journal of Geographical Information Science, 2010, v. 24 n. 5, p. 783-802-
dc.identifier.issn1365-8816-
dc.identifier.urihttp://hdl.handle.net/10722/131088-
dc.description.abstractCellular automata (CA) have been increasingly used in simulating urban expansion and land-use dynamics. However, most urban CA models rely on empirical data for deriving transition rules, assuming that the historical trend will continue into the future. Such inertia CA models do not take into account possible external interventions, particularly planning policies, and thus have rarely been used in urban and land-use planning. This paper proposes to use artificial immune systems (AIS) as a technique for incorporating external interventions and generating alternatives in urban simulation. Inspired by biological immune systems, the primary process of AIS is the evolution of a set of 'antibodies' that are capable of learning through interactions with a set of sample 'antigens'. These 'antibodies' finally get 'matured' and can be used to identify/classify other 'antigens'. An AIS-based CA model incorporates planning policies by altering the evolution mechanism of the 'antibodies'. Such a model is capable of generating different scenarios of urban development under different land-use policies, with which the planners will be able to answer 'what if' questions and to evaluate different options. We applied an AIS-based CA model to the simulation of urban agglomeration development in the Pearl River Delta in southern China. Our experiments demonstrate that the proposed model can be very useful in exploring various planning scenarios of urban development.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp-
dc.relation.ispartofInternational Journal of Geographical Information Science-
dc.rightsThis is an electronic version of an article published in International Journal of Geographical Information Science, 2010, v. 24 n. 5, p. 783-802. International Journal of Geographical Information Science is available online at: http://www.informaworld.com/smpp/ with the open URL of your article.-
dc.subjectArtificial immune system-
dc.subjectUrban planning-
dc.subjectCellular automata-
dc.subjectUrban simulation-
dc.titleSimulating land-use dynamics under planning policies by integrating artificial immune systems with cellular automataen_US
dc.typeArticleen_US
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1365-8816&volume=24&issue=5&spage=783&epage=802&date=2010&atitle=Simulating+land-use+dynamics+under+planning+policies+by+integrating+artificial+immune+systems+with+cellular+automata-
dc.identifier.emailLiu, X: liuxp3@mail.sysu.edu.cn-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/13658810903270551-
dc.identifier.scopuseid_2-s2.0-77951197505-
dc.identifier.hkuros182567-
dc.identifier.volume24-
dc.identifier.issue5-
dc.identifier.spage783-
dc.identifier.epage802-
dc.identifier.isiWOS:000276642200008-

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