Cellular Automata Based Temporal Process Understanding of Urban Growth

Understanding of urban growth process is highly crucial in making development plan and sustainable growth management policy. As the process involves multi-actors, multi-behavior and various policies, it is endowed with unpredictable spatial and temporal complexities, it requires the occurrence of new simulation approach, which is process-oriented and has stronger capacities of interpretation. In this paper, A cellular automata-based model is designed for understanding the temporal process of urban growth by incorporating dynamic weighting concept and project-based approach. We argue that this methodology is able to interpret and visualize the dynamic process more temporally and transparently.

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