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Article: Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones

TitleCoupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones
Authors
Keywordscellular automata
Economic development zone
fuzzy C-means algorithm
urban emergence simulation
Issue Date2020
Citation
International Journal of Geographical Information Science, 2020, v. 34, n. 10, p. 1930-1952 How to Cite?
AbstractModeling urban growth in Economic development zones (EDZs) can help planners determine appropriate land policies for these regions. However, sometimes EDZs are established in remote areas outside of central cities that have no historical urban areas. Existing models are unable to simulate the emergence of urban areas without historical urban land in EDZs. In this study, a cellular automaton (CA) model based on fuzzy clustering is developed to address this issue. This model is implemented by coupling an unsupervised classification method and a modified CA model with an urban emergence mechanism based on local maxima. Through an analysis of the planning policies and existing infrastructure, the proposed model can detect the potential start zones and simulate the trajectory of urban growth independent of the historical urban land use. The method is validated in the urban emergence simulation of the Taiping Bay development zone in Dalian, China from 2013 to 2019. The proposed model is applied to future simulation in 2019–2030. The results demonstrate that the proposed model can be used to predict urban emergence and generate the possible future urban form, which will assist planners in determining the urban layout and controlling urban growth in EDZs.
Persistent Identifierhttp://hdl.handle.net/10722/330409
ISSN
2023 Impact Factor: 4.3
2023 SCImago Journal Rankings: 1.436
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiang, Xun-
dc.contributor.authorLiu, Xiaoping-
dc.contributor.authorChen, Guangliang-
dc.contributor.authorLeng, Jiye-
dc.contributor.authorWen, Youyue-
dc.contributor.authorChen, Guangzhao-
dc.date.accessioned2023-09-05T12:10:20Z-
dc.date.available2023-09-05T12:10:20Z-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Geographical Information Science, 2020, v. 34, n. 10, p. 1930-1952-
dc.identifier.issn1365-8816-
dc.identifier.urihttp://hdl.handle.net/10722/330409-
dc.description.abstractModeling urban growth in Economic development zones (EDZs) can help planners determine appropriate land policies for these regions. However, sometimes EDZs are established in remote areas outside of central cities that have no historical urban areas. Existing models are unable to simulate the emergence of urban areas without historical urban land in EDZs. In this study, a cellular automaton (CA) model based on fuzzy clustering is developed to address this issue. This model is implemented by coupling an unsupervised classification method and a modified CA model with an urban emergence mechanism based on local maxima. Through an analysis of the planning policies and existing infrastructure, the proposed model can detect the potential start zones and simulate the trajectory of urban growth independent of the historical urban land use. The method is validated in the urban emergence simulation of the Taiping Bay development zone in Dalian, China from 2013 to 2019. The proposed model is applied to future simulation in 2019–2030. The results demonstrate that the proposed model can be used to predict urban emergence and generate the possible future urban form, which will assist planners in determining the urban layout and controlling urban growth in EDZs.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Geographical Information Science-
dc.subjectcellular automata-
dc.subjectEconomic development zone-
dc.subjectfuzzy C-means algorithm-
dc.subjecturban emergence simulation-
dc.titleCoupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/13658816.2020.1741591-
dc.identifier.scopuseid_2-s2.0-85083375824-
dc.identifier.volume34-
dc.identifier.issue10-
dc.identifier.spage1930-
dc.identifier.epage1952-
dc.identifier.eissn1362-3087-
dc.identifier.isiWOS:000524205600001-

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