In your text (Chapter 16) you will find a comprehensive overview of models and a discussion on the various ways that models can be integrated with a GIS. There is also a discussion on how the term model, as used in Chapters 3 and 8 [Representing Geography] is being used in a very different manner in this chapter. You should ensure that you are aware of the differences [a template versus an expression of process], and of the variety of models that traditionally have been used (e.g., analog versus digital; static vs dynamic simulation, agent-based, cellular).

For the purposes of this lecture, and in order to provide some additional background on a methodology that many students use in their projects, I will concentrate on one important group of spatial modeling methods: multi-criteria methods. Although multi-criteria / multi-objective decision analysis is a complex topic, given how useful these methods are in so many situations, you should become familiar with them. The NCGIA I note on decision making using multiple criteria covers one aspect of the subject; there is an NCGIA II note on spatial decision support systems that is also well worth reading. As noted above, your text provides a broad review of spatial modeling in general.

Multi-criteria decision analysis (MDA) is one form of spatial decision support.  Other forms of decision making include boolean overlay, linear programming (a general intro -- in particular, chapter 2), network analysis, agent-based modelling, cellular automata, and spatial interaction modeling.  Idrisi has extensive MDA capabilities--to see what kinds of modeling it allows, check here) and here (a G470 project which used MDA to look at birds and cattle conflicts in the south Okanagan).

Here you'll find a document that provides a very good overview of multi-criteria analysis (not from a GIS perspective, but the concepts are similar) (the source for that document; one that links MCA with GIS). A paper in which the author provides a thorough review of GIS and MCA. A good example of Optimal site planning: Fuzzy set membership, multi-criteria evaluation and multi-objective land allocation.

A web site that enables you to calculate AHP scores.

Learning objectives

• Know what modeling means in the context of GIS;
• Be familiar with the important types of models and their applications;
• Be familiar with the software environments in which modeling takes place;
• Understand the needs of modeling and how these needs are being addressed
  by current trends in GIS software.

Text: Chapter 16 Spatial modeling with GIS [Overheads: 1 per page; 3 per page]

Keywords: analytical hierarchy process, boolean {logic, analysis}, factors & constraints, factor standardization / normalization, heuristic (a GIS example), multi-criteria / multi-objective evaluations, sensitivity analysis

References

Cohon, Jared l., 1978. Multiobjective Programming and Planning, Academic Press, Mathematics in Science and Engineering, Vol. 140

Courtney, J.F., Jr., T.D. Klastorin and T.W. Ruefli, 1972. "A Goal Programme Approach to Urban-Suburban Location Preference, " Management Science 18:258-268.

Dane. C.W., N.C. Meador and J.B. White, 1977. "Goal Programming in Land Use Planning," Journal of Forestry 75:325-329.

Diamond, J.T. and Wright, J.R., 1988. Design of an integrated spatial system for multiobjective land-use planning, Environment and Planning B: Planning and Design, Vol. 15, pp 205-214.

Fisher, P., 1995. (Ed.). Diffusion and Use of Geographic Information Technologies, Kluwer Academic Publishers.

Lee, S.M., 1972. Goal Programming for Decision Analysis, Auerbach, Philadelphia. A general introduction to Goal Programming.

Malczewski, Jacek, 1999. GIS and Multicriteria decision analysis, John Wiley & Sons, New York.

Nijkamp, P. and Rietveld, P., 1986. Multiple Objective decision analysis in regional economics. In P. Nijkamp (Ed.). Handbook of Regional Economics, North Holland Publishing Co., Amsterdam.

Voogd, H., 1983. Multicriteria Evaluation for Urban and Regional Planning, Pion, London.