In this paper is described a model of residential mobility, built to simulate individual households, their perception of and reaction to varying conditions across different scales of interaction, and their movements to occupy housing in a physical, social, and economic environment. The methodology underpinning the model is based on an automata core, which leverages the advantages it offers in terms of representing individual entities and their rule-based interactions. This methodology is extended, however, to incorporate geography-specific functionality, with advantages for the modeling of human systems. The applicability of the methodology is demonstrated through the development of a rich model of residential mobility, in which individual households interact with other households and real-estate infrastructure, dynamically in space and time, to form synthetic communities and artificial property submarkets. Use of the model for what-if experimentation is demonstrated with synthetic economic and sociodemographic simulation scenarios.