Abstract
Cellular automata provide a high-resolution representation of urban spatial dynamics.Consequently they give the most realistic predictions of urban structural evolution, and in particular they are able to replicate the various fractal dimensionalities of actual cities. However, since these models do not readily incorporate certain phenomena like density measures and long-distance (as opposed to neighbourhood) spatial interactions, their performance may be enhanced by integrating them with other types of urban models.Cellular automata based models promise deeper theoretical insights into the nature of cities as self-organizing structures.