A New Method to Model Neighborhood Interaction in Cellular Automata-Based Urban Geosimulation

Local spatial interaction (i.e. neighborhood interaction) between land-use types is an important component in Cellular Automata -based urban geosimulation models. Herein a new method based on the integration of Tobler’s First Law of Geography with Reilly’s gravity model and coupled with logistical regression approach is proposed to model and calibrate the neighborhood interaction. This method is embedded into a constrained CA model to simulate the spatial process of urban growth in the Tokyo metropolitan area. The results indicate that this method captures the main characteristics of neighborhood interactions in the spatial process of urban growth. Further, this method provides an alternative and extensive approach to present local spatial interactions for “bottom-up” urban models.