Multi-agent based modeling of spatiotemporal dynamical urban growth in developing countries: simulating future scenarios of Lianyungang city, China
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Urbanization is the most typical form of land use/cover change, and exploration of the driving mechanism of urban growth and the prediction of its future changes are very important for achieving urban sustainable development. In view of the ability of a multi-agent system to simulate a complex spatial system and from the perspective of combining macroscopic and microscopic decision-making behaviors of agents, a spatiotemporal dynamical urban growth simulation model based on the multi-agent systems has been developed. In this model, macroscopic land use planning behaviors implemented by macroagents and microscopic land use selection behaviors autonomously generated by microagents interact within two-dimensional spatial cells. Furthermore, the urbanization process is promoted through joint decision-making by macroagents and microagents. Considering the central region of the coastal industrial city Lianyungang as the study area, we developed three target scenarios on the basis of current trends, economic development priorities, and environmental protection priorities. Moreover, the corresponding urban growth scenarios were simulated and analyzed. The simulation results show that by combining the macroscopic and microscopic decision-making behaviors of agents to simulate spatiotemporal dynamical urban growth based on the multi-agent systems, the proposed model can provide a useful spatial exploratory tool for explaining the driving mechanism of urbanization and providing decision-making support for urban management.
KeywordsUrban growth Spatiotemporal dynamical simulation Multi-agent systems Joint decision-making Scenario analysis China
This study is supported by the National Natural Science Foundation of China (No. 41201386, 41171326, 41101546) and the Postdoctoral Science Foundation of China (No. 2012M521045). We sincerely thank two anonymous reviewers for their constructive comments and suggestions.
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