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A Logistic Based Cellular Automata Model for Continuous Urban Growth Simulation: A Case Study of the Gold Coast City, Australia

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Agent-Based Models of Geographical Systems

Abstract

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. Specifically, 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.

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Authors and Affiliations

  1. Centre for Spatial Environmental Research and School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Queensland, Australia

    Yan Liu

  2. College of Marine Sciences, Shanghai Ocean University, Shanghai, P. R. China

    Yongjiu Feng

Authors
  1. Yan Liu
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  2. Yongjiu Feng
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Correspondence to Yan Liu .

Editor information

Editors and Affiliations

  1. School of Geography, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT, United Kingdom

    Alison J. Heppenstall

  2. , Department of Computational Social Scien, George Mason University, University Drive 4400, Fairfax, 22030, Virginia, USA

    Andrew T. Crooks

  3. International Institute of Applied Syste, Schlossplatz 1, Laxenburg, 2361, Austria

    Linda M. See

  4. Ctr. Advanced Spatial Analysis, University College London, Torrington Place 1-19, London, WC1E 6BT, United Kingdom

    Michael Batty

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Liu, Y., Feng, Y. (2012). A Logistic Based Cellular Automata Model for Continuous Urban Growth Simulation: A Case Study of the Gold Coast City, Australia. In: Heppenstall, A., Crooks, A., See, L., Batty, M. (eds) Agent-Based Models of Geographical Systems. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8927-4_32

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