A logistic based cellular automata model for continuous urban growth simulation: A case study of the Gold Coast city, Australia

Liu, Yan and Feng, Yongjiu (2012). A logistic based cellular automata model for continuous urban growth simulation: A case study of the Gold Coast city, Australia. In Alison J. Heppenstall, Andrew T. Crooks, Linda M. See and Michael Batty (Ed.), Agent-based models of geographical systems (pp. 643-662) Dordrecht, Netherlands: Springer.

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Author Liu, Yan
Feng, Yongjiu
Title of chapter A logistic based cellular automata model for continuous urban growth simulation: A case study of the Gold Coast city, Australia
Title of book Agent-based models of geographical systems
Place of Publication Dordrecht, Netherlands
Publisher Springer
Publication Year 2012
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1007/978-90-481-8927-4
ISBN 9789048189267
9789048189274
Editor Alison J. Heppenstall
Andrew T. Crooks
Linda M. See
Michael Batty
Chapter number 32
Start page 643
End page 662
Total pages 20
Total chapters 37
Collection year 2013
Language eng
Abstract/Summary This chapter presents a logistic based cellular automata model to simulate the continuous process of urban growth in space and over time. The model is constructed based on an understanding from empirical studies that urban growth is a continuous spatial diffusion process which can be described through the logistic function. It extends from previous research on cellular automata and logistic regression modelling by introducing continuous data to represent the progressive transition of land from rural to urban use. Specifi cally, the model contributes to urban cellular automata modelling by (1) applying continuous data ranging from 0 to 1 inclusive to represent the none-discrete state of cells from non-urban to urban, with 0 and 1 representing non-urban and urban state respectively, and all other values between 0 and 1 (exclusive) representing a stage where the land use is transiting from non-urban to urban state; (2) extending the typical categorical data based logistic regression model to using continuous data to generate a probability surface which is used in a logistic growth function to simulate the continuous process of urban growth. The proposed model was applied to a fast growing region in Queensland’s Gold Coast City, Australia.
Q-Index Code B1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Sun, 11 Dec 2011, 20:46:23 EST by Dr Yan Liu on behalf of School of Geography, Planning & Env Management