Developing a Cellular Automaton Model of Urban Growth Incorporating Fuzzy Set Approaches

This is the first part of a two-paper series elaborating the development of a cellular automaton model of urban development using GIS and fuzzy set approaches. Under the paradigm of fuzzy set theory, this paper develops a cellular automaton model of urban development based on an understanding of the logistic trend of urban development processes. The model delimits urban areas as multiple states using a fuzzy membership function and applies transition rules with linguistic variables to represent the non-deterministic nature of urban development controls. By implementing the model in ARC/INFO using the Arc Macro Language (AML) in a GRID environment, experimental scenarios of development of a virtual city under various conditions are presented. Experimental application of the model to an artificial city showed realistic results and demonstrated the model is theoretically feasible and valid. Further work is needed to calibrate the model when applying it to simulate an actual urban development. In the second part of the two-paper series, application of the model in simulating the urban development of Sydney in space and over the last three decades will be demonstrated and discussed.