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Original Articles

Simulating urban growth in a metropolitan area based on weighted urban flows by using web search engine

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Pages 1721-1736 | Received 19 Oct 2014, Accepted 23 Mar 2015, Published online: 23 Apr 2015
 

Abstract

As a consequence of rapid and immoderate urbanization, simulating urban growth in metropolitan areas effectively becomes a crucial and yet difficult task. Cellular automata (CA) model is an attractive tool for understanding complex geographical phenomena. Although intercity urban flows, the key factors in metropolitan development, have already been taken into consideration in CA models, there is still room for improvement because the influences of urban flows may not necessarily follow the distance decay relationship and may change over time. A feasible solution is to define the weights of intercity urban flows. Therefore, this study presents a novel method based on weighted urban flows (CAWeightedFlow) with the support of web search engine. The relatedness measured by the co-occurrences of the cities’ names (toponyms) on massive web pages can be deemed as the weights of intercity urban flows. After applying the weights, the gravitational field model is integrated with Logistic-CA to fulfill the modeling task. This method is employed to the urban growth simulation in the Pearl River Delta, one of the most urbanized metropolitan areas in China, from 2005 to 2008. The results indicate that our method outperforms traditional methods with respect to two measures of calibration goodness-of-fit. For example, CAWeightedFlow can yield the best value of ‘figure of merit’. Moreover, the proposed method can be further used to explore various development possibilities by simply changing the weights.

Acknowledgements

This study was supported by the National Natural Science Foundation of China (Grant No. 41371376). We thank the editor and three anonymous reviewers for their useful comments and suggestions that greatly improved this paper.

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 41371376). We thank the editor and three anonymous reviewers for their useful comments and suggestions that greatly improved this paper.

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