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Application of multi-agent models to urban expansion in medium and small cities: A case study in Fuyang City, Zhejiang Province, China

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Abstract

In this study, three-phase satellite images were used to define rules for the allocation of time and space in construction land resources based on a complex adaptive system and game theory. The decision behavior and rules of government agent, enterprise agent and resident agent in construction land growth were explored. A distinctive and dynamic simulation model of construction land growth was built, which integrated multi-agent, GIS technology and RS data and described the interaction among influencing agents. Taking Fuyang City in the Changjiang River Delta as an example, an assessment process for the remote sensing data in construction land and scenario planning was constructed. Repast and ArcGIS were used as simulation platforms. A simulation of the spatial pattern in land-use planning and the setting of scenario planning were conducted by using the incomplete active game, which was based on different natural, social and economic levels. Through this model, a simulation of urban planning space and decision-making for Fuyang City was created. Relevant non-structured problems arising from urban planning management could be identified, and the process and logic of urban planning spatial decision-making could thus be improved. Cel1-by-cel1 comparison showed that the simulation accuracy was over 72%. This model has great potential for use by government and town planners in decision support and technique support in the policy-making process.

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Correspondence to Ke Wang.

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Foundation item: Under the auspices of National Science and Technology Support Program of China (No. 2012BAH29B04-00)

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Zhang, J., Wang, K., Song, G. et al. Application of multi-agent models to urban expansion in medium and small cities: A case study in Fuyang City, Zhejiang Province, China. Chin. Geogr. Sci. 23, 754–764 (2013). https://doi.org/10.1007/s11769-013-0636-3

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  • DOI: https://doi.org/10.1007/s11769-013-0636-3

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