Relationships between Agent-Based Models and Geographic Information
Systems: An Illustrated Catalog 

William Rand1
wrand@umich.edu
Daniel G. Brown2,1
Michael North3
Rick Riolo1
Derek T. Robinson2,1

1Center for the Study of Complex Systems, University of Michigan
2School of Natural Resources and the Environment, University of Michigan
3Center for Complex Adaptive Agent Systems Simulation, Argonne
National Laboratory

      Spatial data models in geographic information systems (GIS) are
	  used to structure the (mostly static) geographic world so that
	  it can be represented within a database. Two conceptual data
	  models dominate GIS representations of the world, i.e., the
	  field and object views. Spatial process models are similarly
	  structured representations of dynamics within the geographic
	  world. Two dominant conceptual views of spatial processes,
	  borrowed from the Eulerian and Lagrangian views of fluid
	  dynamics, yield models of change and models of movement. In this
	  talk we argue that spatial extensions of object-based process
	  models require that these process models be closely coupled with
	  data models that can be used to explore, explain, and
	  interpolate the spatial data that results from the process
	  model. We discuss how alternative spatial data models constrain
	  or enable close coupling with alternative types of spatial
	  process models. We briefly examine past attempts to integrate
	  spatial data and process models. We then describe how
	  independent developments toward the object-oriented
	  computational paradigm within both geographic data modeling and
	  spatial process modeling provide a new opportunity for close
	  coupling. We discuss the scientific and practical advantages of
	  developing systems that closely couple spatial data models in
	  the form of GIS databases with spatial process models in the
	  form of agent-based models (ABM). The rest of this talk focuses
	  on developing a catalog of relationships between geographic data
	  (fields and objects) and agent-based process models, based on
	  whether the agents have an identity association with spatial
	  feature(s), whether or not such spatial features can move,
	  whether or not they can change, whether or not the agents can
	  change non-agent spatial features or be changed by these
	  features, and whether time is treated as time steps or discrete
	  events. These types of relationships are then illustrated with
	  examples from our work in coupling ABM and GIS. Moreover, there
	  is the question of implementation. We discuss several of the
	  issues that must be addressed when actually implementing the
	  connection between ABM and GIS. We illustrate these questions
	  with examples from our own work and discuss our plans for
	  further integration in the future.