Cellular automata are therfore constrained in their cell space to finite dimensions. The regularity of this space is also questionable in urban contexts. There is little in the city, however, that is discrete. Therefore, cellular models of urban systems commonly contain several cell states simultaneously, and these states range in type from absolute to discrete and to continuous. The idea of the neighborhood in the formal cellular automaton is rather restrictive.
Urban neighborhoods come in many shapes, configurations, and sizes.
Cell neighborhoods consisting of 113 cells, have in some cases been used in simulations. It is here that cellular models of urban systems are generated with adherance to what we know in theory about cities. Recently, urban studies using cellular models have intriduced an innovative range of parameters into transition rules in a bid to enhance their realism. Challenges facing cellular models For all of their advantages, applications, and uses in urban geosimulation, cellular automata modelling of urban systems is still very much in its infancy. Indeed, their are early indications that the framework has some serious challenges facing it, particularly if cellular models are to step out of the realm of abstract academic experimentation and into the world of operational scenario simulation, planning support, and urban management.