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Proceedings Paper

Research on monocentric model of urbanization by agent-based simulation
Author(s): Ling Xue; Kaizhong Yang
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Paper Abstract

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

Paper Details

Date Published: 3 November 2008
PDF: 11 pages
Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 71431R (3 November 2008); doi: 10.1117/12.812592
Show Author Affiliations
Ling Xue, Peking Univ. (China)
Kaizhong Yang, Peking Univ. (China)

Published in SPIE Proceedings Vol. 7143:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Aijun Chen, Editor(s)

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