Modeling urban growth in a metropolitan area based on bidirectional flows, an improved gravitational field model, and partitioned cellular automata

ABSTRACT

Simulating urban landscape dynamics in metropolitan areas has attracted much attention lately, but the difficulty remains. Although large-scale urban simulation studies consider spatial interaction as an important factor, spatial interaction cannot be accurately measured based on a single element flow, and its effects may not strictly follow a distance decay function. Furthermore, different cities may require different transition rules. In this study, we combined bidirectional flows of population and information and an improved gravitational field model to model the urban spatial interaction, and we then integrated a partitioned cellular automata (CA) model to simulate the urban growth for different cities in the Yangtze River middle reaches megalopolis. It was found that the simulation results generated by the CA model considering spatial interaction are significantly improved. Furthermore, partitioned conversion thresholds can effectively improve the model performance. The proposed model showed a much better performance in the simulation of subordinate cities surrounding the core cities, than for the core cities and fringe cities. We suggest that large-scale urban simulation should pay more attention to the development of partitioned transition rules. The effects of intercity urban flows should also be considered in the simulation of small- and medium-sized cities near the regional cores.

KEYWORDS:

• Urban bidirectional flows
• cellular automata model
• gravitational field model
• Yangtze River middle reaches megalopolis
• partitioned conversion thresholds

Acknowledgments

We would like to thank the anonymous reviewers for their helpful and insightful comments. Furthermore, we are very grateful to Professor Pinliang Dong for providing us the weighted Voronoi extension for ArcGIS 10.x.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41571384].

Notes on contributors

Chang Xia

Chang Xia is a PhD student at Department of Urban Planning and Design at University of Hong Kong. He received his master degree in land use management from Wuhan University. His research interests include urban growth modeling and urban landscape analysis.

Anqi Zhang

Anqi Zhang is a PhD student at Department of Urban Planning and Design at  University of Hong Kong. Her research interests are urban landscape, urban growth and land use planning.

Haijun Wang

Haijun Wang was a lecturer at Wuhan University from 2003 to 2008, and associate professor from 2008 to 2015. He studied as a visiting scholar at the University of Hong Kong from 2013 to 2014. He is currently a professor and PhD Tutor in the School of Resource and Environmental Sciences at Wuhan University, China. He is mainly engaged in geographical simulation, urban planning and land resource evaluation research.

Bin Zhang

Bin Zhang is a student in the School of Resource and Environmental Sciences at Wuhan University, China. He is studying for his Masters at Wuhan University from 2016 to 2019, and he will continue to pursue a doctorate at Wuhan University. His research  interests are geographical simulation and LUCC. He is especially interested in simulating urban expansion using cellular automata  models and optimization methods.