This research presents the methodology for ‘situating’ simulation of the modeling of human spatiotemporal interactions through the use of a new modeling tool, Agent Analyst, which integrates agent-based modeling (ABM) and geographic information systems (GIS).
Many social phenomena have a spatio-temporal dimension and involve dynamic decisions made by individuals. In the past, researchers have often turned to geographic information systems (GIS) to model these interactions. Although GIS provide a powerful tool for examining the spatial aspects of these interactions, they are unable to model the dynamic, individual-level interactions across time and space. In an attempt to address these issues, some researchers have begun to use simulation models; however, these models rely on artificial landscapes that do not take into account the environment in which humans move and interact. In the research reported in this article, three versions of a model of street robbery are presented to illustrate the importance of using ‘real’ data to inform agent activity spaces and movement. The successful implementation of this model demonstrates that: (1) agents can move along existing street networks; (2) land-use patterns can be used to realistically distribute agent's homes and activities across a city; and (3) the incidence and pattern of street robberies is significantly different when ‘real’ data are used. (Publisher abstract provided)