A cellular automata model for urban land-use simulation

This paper presents an urban land-use simulation model using cellular automata (CA). In the model urban growth is regarded as the result of a global process underpinned by local actions and land-use change as the joint action of three different effects: attribute, heterogeneity, and gravity. The attribute and heterogeneity effects are regarded as different aspects of a local driving force for change constituted by changing accessibility and other attributes resulting from the interaction of land use and transport at the neighborhood level. The gravity effect is a universal resistance to change as a result of inertia and agglomeration of compatible land uses in the vicinity. To ensure that local actions would lead to global behavior, a multipass, in addition to a single-pass, land-use-allocation algorithm is designed to mimic land-use changes. With metropolitan Melbourne in Australia as a case study, the performance of the model in replicating land-use changes is compared with that of an alternative model developed by using only a distance function. The results of the comparison show that the proposed CA model outperforms the alternative model with only a distance function, confirming the importance of incorporating local attributes in modeling land-use changes.