Incorporating Cellular Automata simulators as analytical engines in GIS

Contemporvy GIS suffer from a variety of problems. These include poor ability to handle dynamic spatial models, poor performance for many operations, and poor handling of the temporal dimension. Cellular Automata (CA) are dynamic mathematical systems based on discrete time and space. While CA have many similarities to GIS, and indeed excel in many areas in which GIS are deficient, they cannot themselves be considered as GIS since they lack the necessary sophisticated Capabilities in data input, data storage and retrieval, and data output. However, the advantages of CA in data analysis and modelling are significant. In order to exploit fully the advantages of each system - GIS and CA - we have developed a methodology and prototype system for coupling GIS and CA, in which the CA serves as an alternative analytical engine for the GIS. In the prototype system, spatial, temporal (i.e. time series), and spatio-temporal filters as well as spatial diffusion operators are developed. In addition, the integrated system provides a flexible framework for the programming and running of dynamic spatial models. We conclude that CA represent a viable alternate analytical engine for GIS and provide increased ability for dynamic spatial modelling within GIS.