ABSTRACT
One popular urban growth model is the SLEUTH, created by Dr. Keith Clarke at UCSB Geography (Clarke et al., 1996, 1997). SLEUTH is composed of a series of growth rules, which form modified Cellular Automata (CA). When running SLEUTH, the rules of the CAs (the growth rules) are calibrated to historical urban spatial data. SLEUTH can then be used to forecast urban extent under different scenarios. Due to its scale independence, transportability, and transparency, SLEUTH has become a popular tool in modeling the spread of urban extent over time, be it recreating the past or forecasting growth into the future (Yang and Lo, 2003). Yang and Lo also cite the ability of SLEUTH’s growth rules to self-modify as it models a region into the future, deviating from monotonically increasing, line-fitting urban growth models. SLEUTH has been used as an alternative to the demographics-driven urban growth models, which are frequently custom built for a particular regions, or too cumbersome (and expensive) to understand or implement. While the lack of demographic and economic output is a drawback to SLEUTH, some efforts have been made to coupling SLEUTH to demographic models of city growth (UCIME, 2001). Lastly, SLEUTH can be used as a powerful planning tool by incorporating different human perceptions or planning options into the model in order to forecast different scenarios of the growing footprint of a city.
