Cellular automata modelling for urban planning in fast-growth regions

Abstract

The past three decades have witnessed the rapid development of geosimulation technology, such as cellular automata (CA) and agent-based modelling (ABM), for solving various geographical problems in rapidly growing regions. This chapter summarizes the main applications of CA for researchers and decision-makers to solve the environmental and planning problems associated with urban sprawl, illegal development and improper facility sitting. An integrated CA-based model, the Geographical Simulation and Optimization System (GeoSOS), has been applied to tackle a wide spectrum of environmental and resource management issues, such as the zoning of basic farmland protection areas, coupling land-use dynamics with facility sitting, and delineation of urban growth boundaries. Our studies have shown that CA models are capable of evaluating land-use policies and predicting illegal developments for early warning purposes. The simulation of using CA provides valuable experiences for urban researchers and planners to solve a series of simulation and planning problems in fast-growing regions.