Simulation of dynamic urban growth with partial least squares regression-based cellular automata in a GIS environment

Feng, Yongjiu, Liu, Miaolong, Chen, Lijun and Liu, Yu (2016) Simulation of dynamic urban growth with partial least squares regression-based cellular automata in a GIS environment. ISPRS International Journal of Geo-Information, 5 12: . doi:10.3390/ijgi5120243


Author Feng, Yongjiu
Liu, Miaolong
Chen, Lijun
Liu, Yu
Title Simulation of dynamic urban growth with partial least squares regression-based cellular automata in a GIS environment
Journal name ISPRS International Journal of Geo-Information   Check publisher's open access policy
ISSN 2220-9964
Publication date 2016-12-16
Sub-type Article (original research)
DOI 10.3390/ijgi5120243
Open Access Status DOI
Volume 5
Issue 12
Total pages 16
Place of publication Basel, Switzerland
Publisher M D P I AG
Language eng
Abstract We developed a geographic cellular automata (CA) model based on partial least squares (PLS) regression (termed PLS-CA) to simulate dynamic urban growth in a geographical information systems (GIS) environment. The PLS method extends multiple linear regression models that are used to define the unique factors driving urban growth by eliminating multicollinearity among the candidate drivers. The key factors (the spatial variables) extracted are uncorrelated, resulting in effective transition rules for urban growth modeling. The PLS-CA model was applied to simulate the rapid urban growth of Songjiang District, an outer suburb in the Shanghai Municipality of China from 1992 to 2008. Among the three components acquired by PLS, the first two explained more than 95% of the total variance. The results showed that the PLS-CA simulated pattern of urban growth matched the observed pattern with an overall accuracy of 85.8%, as compared with 83.5% of a logistic-regression-based CA model for the same area. The PLS-CA model is readily applicable to simulations of urban growth in other rapidly urbanizing areas to generate realistic land use patterns and project future scenarios.
Keyword Urban growth
Dynamic simulation
Cellular automata
Partial least squares (PLS) regression
Geographical information systems (GIS)
Accuracy analysis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
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