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A novel approach to automata-based modeling for spatial systems is described: geographic automata and Geographic Automata Systems. We detail a framework that takes advantage of the formalism of automata theory and GI Science to unite cellular automata and multi-agent systems techniques, and provides a spatial approach to bottom-up modeling of complex geographic systems that are comprised of infrastructure and human objects. The suitability of the framework is also discussed with reference to existing cellular automata and multi-agent systems models used in urban studies. Practical implementation of the framework is illustrated with reference to an object-based urban simulation environment and implementation of a popular socio-spatial segregation model.

The dynamics of the ethnic residential distribution in the Yaffo area of Tel Aviv, which is jointly occupied by Arab and Jewish residents, is simulated by means of an entity-based (EB) model. EB models consider householders as separate entities, whose residential behavior is defined by the properties of the surrounding infrastructure and of other householders. The power of the EB approach lies in its ability to interpret directly different forms of decisionmaker behavior in the model's terms. Several scenarios of residential interactions between members of local ethnic groups are compared on the basis of detailed georeferenced data taken from Israel's 1995 Population Census. The model simulates very closely the residential dynamics during the period 1955–95; the importance of the qualitative aspects of residential choice, as captured by the EB approach, is demonstrated by this correspondence.

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The increasing interest in sustainable development has underlined the importance of accessibility as a key indicator to assess transport investments, urban policy, and urban form. From both the environmental and the equity component of sustainability, a comparison of accessibility by car versus public transport is of utmost importance. However, most studies in this direction have used rather rough estimates of travel time, especially by public transport. In this paper, we present Urban.Access, an ArcGIS extension for estimating car-based and transit-based accessibility to employment and other land uses. Urban.Access enables a detailed representation of travel times by transit and car and thus makes it possible to adequately compare accessibility levels by transport mode. The application of Urban.Access to the Tel Aviv metropolitan area shows that the gaps between car-based and transit-based accessibility are larger than those found in other studies. We argue that this is not the result of a poorer transit system, but rather of a more detailed description of travel by transit in the Urban.Access application. The larger gaps point to a greater need for adequate policy responses, both for reducing car dependence as well as for creating a more equitable