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Article: Neural-network-based cellular automata for simulating multiple land use changes using GIS

TitleNeural-network-based cellular automata for simulating multiple land use changes using GIS
Authors
Issue Date2002
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, 2002, v. 16 n. 4, p. 323-343 How to Cite?
AbstractThis paper presents a new method to simulate the evolution of multiple land uses based on the integration of neural networks and cellular automata using GIS. Simulation of multiple land use changes using cellular automata (CA) is difficult because numerous spatial variables and parameters have to be utilized. Conventional CA models have problems in defining simulation parameter values, transition rules and model structures. In this paper, a three-layer neural network with multiple output neurons is designed to calculate conversion probabilities for competing multiple land uses. The model involves iterative looping of the neural network to simulate gradual land use conversion processes. Spatial variables are not deterministic because they are dynamically updated at the end of each loop. A GIS is used to obtain site attributes and training data, and to provide spatial functions for constructing the neural network. The parameter values for modelling are automatically generated by the training procedure of neural networks. The model has been successfully applied to the simulation of multiple land use changes in a fast growing area in southern China.
Persistent Identifierhttp://hdl.handle.net/10722/89781
ISSN
2015 Impact Factor: 2.065
2015 SCImago Journal Rankings: 1.156
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Xen_HK
dc.contributor.authorYeh, AGOen_HK
dc.date.accessioned2010-09-06T10:01:43Z-
dc.date.available2010-09-06T10:01:43Z-
dc.date.issued2002en_HK
dc.identifier.citationInternational Journal Of Geographical Information Science, 2002, v. 16 n. 4, p. 323-343en_HK
dc.identifier.issn1365-8816en_HK
dc.identifier.urihttp://hdl.handle.net/10722/89781-
dc.description.abstractThis paper presents a new method to simulate the evolution of multiple land uses based on the integration of neural networks and cellular automata using GIS. Simulation of multiple land use changes using cellular automata (CA) is difficult because numerous spatial variables and parameters have to be utilized. Conventional CA models have problems in defining simulation parameter values, transition rules and model structures. In this paper, a three-layer neural network with multiple output neurons is designed to calculate conversion probabilities for competing multiple land uses. The model involves iterative looping of the neural network to simulate gradual land use conversion processes. Spatial variables are not deterministic because they are dynamically updated at the end of each loop. A GIS is used to obtain site attributes and training data, and to provide spatial functions for constructing the neural network. The parameter values for modelling are automatically generated by the training procedure of neural networks. The model has been successfully applied to the simulation of multiple land use changes in a fast growing area in southern China.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.aspen_HK
dc.relation.ispartofInternational Journal of Geographical Information Scienceen_HK
dc.titleNeural-network-based cellular automata for simulating multiple land use changes using GISen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1365-8816&volume=16&issue=4&spage=323&epage=343&date=2002&atitle=Neural-network-based+cellular+automata+for+simulating+multiple+land+use+changes+using+GISen_HK
dc.identifier.emailYeh, AGO: hdxugoy@hkucc.hku.hken_HK
dc.identifier.authorityYeh, AGO=rp01033en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/13658810210137004en_HK
dc.identifier.scopuseid_2-s2.0-0036332937en_HK
dc.identifier.hkuros78417en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036332937&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume16en_HK
dc.identifier.issue4en_HK
dc.identifier.spage323en_HK
dc.identifier.epage343en_HK
dc.identifier.isiWOS:000176640200002-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLi, X=34872691500en_HK
dc.identifier.scopusauthoridYeh, AGO=7103069369en_HK
dc.identifier.citeulike7522861-

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