Industrial development and employment growth are the important driving forces for urban growth. This paper simulates urban industrial spatial evolution by integrating Multi-agent systems (MAS), cellular automata (CA) and GIS. In this study, an agent-based system is developed based on CA to simulate complex urban systems by incorporating human factors and physical factors. Human factors are incorporated into the model by agents' decision actions, which embody uncertainties and complex behaviors in the simulation process. Government organizers and industrial investors are considered to be agents, which decide industrial spatial evolution in this model. Government agents and industrial investor agents are used to make decisions for determining the choice of new industrial locations and existing industrial allocation by considering a series of complex physical and economic factors. Urban industrial spatial development is shaped by interactions, competition, collaboration among different agents and between these agents and the environment.The agent-based modeling technique was applied to the simulation of the spatial evolution of industry in the Zhangmutou town of the Pearl River Delta in 1988-2004. The comparison analysis indicates that the proposed model has much better performance than pure CA models in simulating complex urban development in micro-levels. It is because the human and social factors can be well incorporated in the simulation process.
YANG Qing-sheng, LI Xia
. Agent-based micro-simulation of urban industrial spatial evolutiont[J]. SCIENTIA GEOGRAPHICA SINICA, 2009
, 29(4)
: 515
-522
.
DOI: 10.13249/j.cnki.sgs.2009.04.515
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