Inderscience Publishers

An urban model using complex constrained cellular automata: long-term urban form prediction for Beijing

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In recent years, simulating urban growth using cellular automata (CA) has attracted extensive attention for investigating the dynamic urban system. Distinguished from the pure CA, the CA model applied for urban growth simulation should not only include the neighbourhood influence, but other factors related with urban developments. We proposed the term 'complex constrained CA' (CC-CA), which integrates constraints of neighbourhood, macro socioeconomic, spatial and institutional types. Particularly, the constructing constrained zoning planning, as an institutional constraint, is introduced into the CC-CA model. We applied the CC-CA model for the Beijing Metropolitan Area. Parameters of constraints are calibrated for various historical phases of Beijing, with which the baseline scenario with current developing trend is build to simulate the long-term urban form of Beijing. In addition, we set the planning controlled scenario via adjusting institutional constraints' parameters, and compare the results with the baseline scenario. The impact of institutional constraints on future urban form is then visualised for policy makers. The CC-CA is proved to have its policy implications for Beijing.

Keywords: cellular automata, Beijing, institutional constraints, China, urban models, constrained automata, complex automata, long-term predictions, urban forms, cities, urban systems, urban growth simulation, neighbourhood influences, urban developments, macro socioeconomic constraints, metropolitan areas, spatial constraints, zoning, town planning, zones, constraint parameters, historical phases, baseline scenarios, policy makers, society, systems science, assessment methods, social systems

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