Dynamic Spatial Modeling of Urban Growth through Cellular Automata in a GIS Environment

Abstract

Urban settlements and their connectivity will be the dominant driver of global change during the twenty-first century. In an attempt to assess the effects of urban growth on available land for other uses and its associated impacts on environmental parameters, we modeled the change in the extent of Gorgan City, the capital of the Golestan Province of Iran. We used Landsat TM and ETM+ imagery of the area and evaluated possible scenarios of future urban sprawl using the SLEUTH method. The SLEUTH is a cellular automaton dynamic urban-growth model that uses geospatial data themes to simulate and forecast change in the extent of urban areas. We successfully modeled and forecasted the likely change in extent of the Gorgan City using slope, land use, exclusion zone, transportation network, and hillshade predictor variables. The results illustrated the utility of modeling in explaining the spatial pattern of urban growth. We also showed the method to be useful in providing timely information to decision makers for adopting preventive measures against unwanted change in extent and location of the built-up areas within in the city limits.