There are manyadvantages of applying cellular automata (CA) models to urban systems: realism, spatiality, resolution, presentation, and links with geographic information systems. The CA lattice can be generalized to represent urban spatial structures, networks of accessibility, or the physical infrastructure of the city. Not surprisingly, CA and the patterns that they generate exhibit many idiosyncrasies of complex adaptive systems, such as phase shifts, power laws, self-organization, self-similarity, and fractal dimensions. Spatial relationships, such as topologies and networks, are crutial parts of a GIS database. Topology is employed to manage common boundaries between features, define and enforce data integrity rules, and support topological queries and navigation (for example, to determine feature adjacency and connectivity). Topology is also used to support sophisticated editing and to construct features from unconstructed geometry (for example, to construct polygons from lines). Networks describe a connected graph of GIS objects that can be traversed. This is important for modeling pathways and navigation for transportation, utilities, and many other network-based applications. Practically, CA and GIS have several generalities indeed. First link between CA models and GIS can be observed on an initial stage of the modeling: CA pattem and raster data are cell-based (pixels). Second one is spatial relationships that depends on local connections. Third and the most promising link is that integrating them we can get more information about urban system development. As an example, we take a small raster drawing from GIS, use it in our Urban CA Model (URBACAM) as a pattern, reach relevant proportions; make some simulations and analysis.