A heuristic cellular automata approach for modelling urban land-use change based on simulated annealing

Feng, Yongjiu and Liu, Yan (2013) A heuristic cellular automata approach for modelling urban land-use change based on simulated annealing. International Journal of Geographical Information Science, 27 3: 449-466. doi:10.1080/13658816.2012.695377

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads

Author Feng, Yongjiu
Liu, Yan
Title A heuristic cellular automata approach for modelling urban land-use change based on simulated annealing
Journal name International Journal of Geographical Information Science   Check publisher's open access policy
ISSN 1365-8816
1365-8824
Publication date 2013-03
Year available 2012
Sub-type Article (original research)
DOI 10.1080/13658816.2012.695377
Open Access Status
Volume 27
Issue 3
Start page 449
End page 466
Total pages 18
Place of publication Colchester, Essex, United Kingdom
Publisher Taylor & Francis
Collection year 2013
Language eng
Abstract This article presents a novel cellular automata (CA) approach to simulate the spatio-temporal process of urban land-use change based on the simulated annealing (SA) algorithm. The SA algorithm enables dynamic optimisation of the CA's transition rules that would otherwise be difficult to configure using conventional mathematical methods. In this heuristic approach, an objective function is constructed based on a theoretical accumulative disagreement between the simulated land-use pattern and the actual land-use pattern derived from remotely sensed imagery. The function value that measures the mismatch between the actual and the simulated land-use patterns would be minimised randomly through the SA process. Hence, a set of attribution parameters that can be used in the CA model is achieved. An SA optimisation tool was developed using Matlab and incorporated into the cellular simulation in GIS to form an integrated SACA model. An application of the SACA model to simulate the spatio-temporal process of land-use change in Jinshan District of Shanghai Municipality, PR China, from 1992 to 2008 shows that this modelling approach is efficient and robust and can be used to reconstruct historical urban land-use patterns to assist with urban planning policy-making and actions. Comparison of the SACA model with a typical CA model based on a logistic regression method without the SA optimisation (also known as LogCA) shows that the SACA model generates better simulation results than the LogCA model, and the improvement of the SACA over the LogCA model is largely attributed to higher locational accuracy, a feature desirable in most spatially explicit simulations of geographical processes.
Keyword Simulated annealing
Urban modelling
Land-use change
Cellular automata
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online 27 July 2012.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2013 Collection
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 16 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 22 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 03 Aug 2012, 15:02:05 EST by Alexandra Simmonds on behalf of School of Geography, Planning & Env Management