Replication of Spatio-temporal Land Use Patterns at Three Levels of Aggregation by an Urban Cellular Automata

The SLEUTH urban growth model [1] is a cellular automata model that has been widely applied throughout the geographic literature to examine the historic settlement patterns of cities and to forecast their future growth. In this research, the ability of the model to replicate historical patterns of land use is examined by calibrating the model to fit historical data with 5, 10, and 15 different land use classes. The model demonstrates it robustness in being able to correctly replicate 72-93% of the land use transitions over an eight-year time period, in both space and time.