Calibration of stochastic cellular automata: the application to rural-urban land conversions

Despite the recognition of cellular automata (CA) as a exible and powerful tool for urban growth simulation, the calibration of CA had been largely heuristic until recent eVorts to incorporate multi-criteria evaluation and arti cial neural network into rule de nition. This study developed a stochastic CA model, which derives its initial probability of simulation from observed sequential land use data. Furthermore, this initial probability is updated dynamically through local rules based on the strength of neighbourhood development. Consequentially the integration of global (static) and local (dynamic) factors produces more realistic simulation results. The procedure of calibrated CA can be applied in other contexts with minimum modi cation. In this study we applied the procedure to simulate rural-urban land conversions in the city of Guangzhou, China. Moreover, the study suggests the need to examine the result of CA through spatial, tabular and structural validation.

• Type: Journal
• Year: 2002
• Where: GIS
• Authors: Fulong Wu
• Keywords: Automated Reasoning, GIS 2002, Initial Probability, Stochastic Ca Model, Urban Growth Simulation