Simulating urban expansion using a cloud-based cellular automata model: A case study of Jiangxia, Wuhan, China

Abstract

Because of the complexity of urban systems, the dynamic process of urban expansion is filled with uncertainty. Although many studies have been done on cellular automata (CA)-based urban expansion models, the measurements of uncertainties and uncertainty propagation were commonly neglected when constructing CA models. The cloud model can express uncertainty and its propagation, and coherently integrates fuzziness and randomness as well as overcoming the limitations of fuzzy theory and the Monte Carlo method. A cloud-based CA (cloud-CA) model is presented in this paper to represent uncertainty propagation and show the dependence of simulation results on different degrees of uncertainty represented by hyper-entropy (He). We implemented the cloud-CA model and applied it on the simulation of the urban expansion in Jiangxia, Wuhan, China. After constructing the appropriate parameter settings for the cloud-CA model, a comparison of cloud-CA with the fuzzy-set-based CA (fuzzy-CA) model, and the hybrid CA model based on fuzzy set and the Monte Carlo method (FSMC-CA) was made by simulating spatial patterns of urban growth in Jiangxia from 2002 to 2007. The experiment indicated that the cloud-CA model has a better performance than the other two CA models, with higher kappa indices and figure of merit, proving the effectiveness of the cloud-CA model. © 2012.