Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones. Issue 10 (2nd October 2020)
- Record Type:
- Journal Article
- Title:
- Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones. Issue 10 (2nd October 2020)
- Main Title:
- Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones
- Authors:
- Liang, Xun
Liu, Xiaoping
Chen, Guangliang
Leng, Jiye
Wen, Youyue
Chen, Guangzhao - Abstract:
- ABSTRACT: Modeling 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.
- Is Part Of:
- International journal of geographical information science. Volume 34:Issue 10(2020)
- Journal:
- International journal of geographical information science
- Issue:
- Volume 34:Issue 10(2020)
- Issue Display:
- Volume 34, Issue 10 (2020)
- Year:
- 2020
- Volume:
- 34
- Issue:
- 10
- Issue Sort Value:
- 2020-0034-0010-0000
- Page Start:
- 1930
- Page End:
- 1952
- Publication Date:
- 2020-10-02
- Subjects:
- Economic development zone -- urban emergence simulation -- fuzzy C-means algorithm -- cellular automata
Geography -- Data processing -- Periodicals
Information storage and retrieval systems -- Periodicals
Géomatique -- Périodiques
Systèmes d'information -- Périodiques
910.285 - Journal URLs:
- http://www.tandfonline.com/loi/tgis20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/13658816.2020.1741591 ↗
- Languages:
- English
- ISSNs:
- 1365-8816
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.266150
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13945.xml