Simulating urban dynamics using cellular antomata

Xia Li

doi:10.4018/978-1-59904-591-7.ch007

Simulating urban dynamics using cellular antomata

Xia Li^*

^*Corresponding author for this work

Sun Yat-Sen University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

This chapter introduces the concepts of cellular automata (CA) which have been increasingly used for simulating urban dynamics. Simulation and prediction of urban evolution can provide the useful inputs to crime models. However, calibration of urban cellular automata is crucial for simulating realistic cities. Simulation of multiple land use changes using CA is difficult because numerous spatial variables and parameters have to be utilized. The incorporation of neural networks with CA can alleviate the calibration problems. This chapter illustrates how complex land use dynamics can be simulated by the integration of CA and neural networks.

Original language	English
Title of host publication	Artificial Crime Analysis Systems
Subtitle of host publication	Using Computer Simulations and Geographic Information Systems
Publisher	IGI Global
Pages	125-139
Number of pages	15
ISBN (Print)	9781599045917
DOIs	https://doi.org/10.4018/978-1-59904-591-7.ch007
State	Published - 2008
Externally published	Yes

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10.4018/978-1-59904-591-7.ch007

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AB - This chapter introduces the concepts of cellular automata (CA) which have been increasingly used for simulating urban dynamics. Simulation and prediction of urban evolution can provide the useful inputs to crime models. However, calibration of urban cellular automata is crucial for simulating realistic cities. Simulation of multiple land use changes using CA is difficult because numerous spatial variables and parameters have to be utilized. The incorporation of neural networks with CA can alleviate the calibration problems. This chapter illustrates how complex land use dynamics can be simulated by the integration of CA and neural networks.

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Simulating urban dynamics using cellular antomata

Abstract

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