Abstract
This paper describes specific points of simulation models in the urban simulation domain. Most of the agent-based models in this domain are made with using the cellular automaton methodology, but lack of considering life spaces, such as houses, offices, schools and so on. In this paper, we make two similar infection models. One is based on the cellular automaton and the geographic information system without considering life spaces, while the other is with life spaces considered. From simulation results, we find that simulation results become significantly different due to the differences between ways of model construction, and realize that life spaces are very important for some social phenomena that focus on interactions between human and human, and human and spaces, such as a spreading infection phenomenon.
