Natural Resources, School of


Date of this Version



Originally published online by the Department of Geography, University of California, Santa Barbara, at Copyright 2008 Qingfeng (Gene) Guan.


SLEUTH1 is a Cellular Automata (CA) model of urban growth and land use change simulation and forecasting, developed in the Department of Geography, University of California, Santa Barbara (Clarke, Hoppen, and Gaydos 1997; Clarke and Gaydos 1998; Silva and Clarke 2002).

A classical Cellular Automata model is a set of identical elements, called cells, each one of which is located in a regular, discrete space, called cellspace. Each cell is associated with a state from a finite set. The model evolves in discrete time steps, changing the states of all its cells according to a transition rule, homogeneously and synchronously applied at every step. The new state of a certain cell depends on the previous states of a set of cells, which include the cell itself, and constitutes its neighborhood.

The urban growth model SLEUTH, uses a modified CA to simulate the spread of urbanization across a landscape. Its name comes from the GIS layers required by the model: Slope, Land-use, Exclusion (where growth cannot occur, e.g., the oceans and national parks), Urban, Transportation, and Hillshade. The complex transition rules, the multiple parameters involved in the rules, and the potential vast volume of the datasets, have made SLEUTH a massive computing system.

A compressed file of the source code for pSleuth is attached (below) as a related file.

Guan pSLEUTH_v1.0.tar.gz (1672 kB)
Source code for pSLEUTH