GEOGRAPHICAL RESEARCH ›› 2009, Vol. 28 ›› Issue (4): 947-956.doi: 10.11821/yj2009040009

• Urban and Rural Studies • Previous Articles     Next Articles

Dynamic simulation of impact factors on mono-centric urbanization by using agent-based modeling

XUE Ling1, WENG Jing2, YANG Kai-zhong1, LI Guo-ping1   

  1. 1. School of Government, Peking University, Beijing 100871, China;
    2. Tourism Department, Fudan University, Shanghai 200433, China
  • Received:2008-11-17 Revised:2009-03-13 Online:2009-07-25 Published:2009-07-25
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In this paper, the UrbanSwarm, a computational environment, is developed for a better understanding of urbanization by agent-based modeling. UrbanSwarm contains multiple economic interactions between urban and rural agents that are crucial in urbanization process and mechanism because the basic force driving the urbanization is inherently microscopic. This paper gives a detailed discussion on the influencing factors such as migration policy, domestic demand, and negative effect of agglomeration on urbanization process in mono-centric scenario. (1) The segmentation policy not only limited the urban-rural migration but enlarged urban-rural income disparity as well. It simulates the household registration system (hukou) before 1978, which confined most Chinese citizens to their places of birth. (2) Raising urban-rural propensity to consumer contributes to both urban-rural income level and urbanization level. Meanwhile, it can narrow the urban-rural gap. (3) With the increase of the negative effect of agglomeration on urbanization, urbanization level drops gradually. The urbanization process loses its sustainability if the negative effect of agglomeration on urbanization exceeds some thresholds in mono-centric pattern. (4) The industrialization and urbanization level has a close relationship if the technology and preference are never changed. The process of industrialization is faster than the process of urbanization in simulation. This parallel processing agent-based approach has various advantages over existing economic approaches such as neoclassical model and equilibrium analysis. UrbanSwarm can be used for both simulation and computation purposes. MAS provides an exploratory platform to test hypotheses behind the space-time dynamics as well as to experiment with 'what-if' games within complex urbanization process, i.e. using the computer as an artificial laboratory for the study of urban and regional systems. Besides, it can be used to achieve some computational intensive tasks through the collective work of individual agents such as rural and urban households, local government, firms and so on. Future work should focus on removing the limitations of reactive agents, implementing the use of cognitive or deliberate agents and achieving their full integration into GIS environment.

Key words: agent-based modeling, urbanization, impact factors, dynamic simulation