An Agent-Based Approach to Environmental and Urban Systems within Geographic Information Systems

Abstract

Both environment and urban systems are complex systems that are intrinsically spatially and temporally organized. Geographic information systems (GIS) provide a platform to deal with such complex systems, both from modeling and visualization points of view. For a long time, cell-based GIS has been widely used for modeling urban and environment system from various perspectives such as digital terrain representation, overlay, distance mapping, etc. Recently temporal GIS (TGIS) has been challenged to model dynamic aspects of urban and environment system (e.g., Langran, Clifford and Tuzhilin, Egenhofer and Golledge), in pursuit of better understanding and perception of both spatial and temporal aspects of these systems. In regional and urban sciences, cellular automata (CA) provide useful methods and tools for studying how regional and urban systems evolve. Because of its conceptual resemblance to cell-based GIS, CA have been extensively used to integrate GIS as potentially useful qualitative forecasting models. This approach intends to look at urban and environment systems as self-organized processes; i.e., how coherent global patterns emerge from local interaction. Thus this approach differentiates it from TGIS in that there is no database support for space-time dynamics. An agent-based approach was initially developed from distributed artificial intelligence (DAI). The basic idea of agent-based approaches is that programs exhibit behaviors entirely described by their internal mechanisms. By linking an individual to a program, it is possible to simulate an artificial world inhabited by interacting processes. Thus it is possible to implement simulation by transposing the population of a real system to its artificial counterpart. Each member of population is represented as an agent who has built-in behaviors. Agent-based approaches provide a platform for modeling situations in which there are large numbers of individuals that can create complex behaviors. It is likely to be of particular interest for modeling space-time dynamics in environmental and urban systems, because it allows researchers to explore relationships between microlevel individual actions and the emergent macrolevel phenomena. An agent-based approach has great potential for modeling environmental and urban systems within GIS. Previous work has focused on modeling people environment interaction, virtual ecosystems, and integration of agent based approach and GIS.