Reports and Papers

Fedra, K. (1995)

Decision support for natural resources management:
Models, GIS and expert systems.
AI Applications, 9/3 (1995) pp 3-19.

A Decision Support Framework

The ultimate objective of a computer based decision support system for natural resources management is, or should be, to improve planning and decision making processes by providing useful and scientifically sound information to the actors involved in these processes, including public officials, planners and scientists, and the general public.

Decision support is a very broad concept, and involves both rather descriptive information systems as well as more formal normative, prescriptive optimization approaches. Any decision problem can be understood as revolving around a choice between alternatives. These alternatives are analyzed and ultimately ranked according to a number of criteria by which they can be compared; these criteria are checked against the objectives and constraints (our expectations), involving possible trade-offs between conflicting objectives. An alternative that meets the constraints and scores highest on the objectives is then chosen. If no such alternative exists in the choice set, the constraints have to be relaxed, criteria have to be deleted (or possibly added), and the trade-offs redefined.

However, the key to an optimal choice is in having a set of options to choose from that does indeed contain an optimal solution. Thus, the generation or design of alternatives is a most important, if not the most important step. In a modeling framework, this means that the generation of scenarios must be easy so that a sufficient repertoire of choices can be drawn upon.

The selection process is then based on a comparative analysis of the ranking and elimination of (infeasible) alternatives from this set. For spatially distributed and usually dynamic models -- natural resource management problems most commonly fall into this category -- this process is further complicated, since the number of dimensions (or criteria) that can be used to describe each alternative is potentially very large. Since only a relatively small number of criteria can usefully be compared at any one time (due to the limits of the human brain rather than computers), it seems important to be able to choose almost any subset of criteria out of this potentially very large set of criteria for further analysis, and modify this selection if required.

Modeling for decision support, or model based decision support systems for environmental and resource management problems have been discussed and advocated for a considerable time (de Wispelaere, Schiermeier and Gillani, 1986; Fedra and Reitsma, 1990; Fedra, 1991; Heatwole, 1993; Holcomb Research Institute, 1976; Labadie et al., 1989 and Loucks, Kindler and Fedra, 1985). Success stories of actual use in the public debate and policy making process are somewhat more rare, in particular at the societal rather than commercial end of the spectrum of possible applications.

The specific role of integrated DSS, including models integrated with expert systems and GIS wrapped into interactive graphical user interfaces is primarily in their heuristic and didactic value. Graphical displays such as topical maps are an easy to understand form of communicating complex information. They can generate a widely accepted and familiar format for a shared information basis supporting an open debate.

Because of the complexity and high dimensionality of alternatives that include spatially distributed variables -- for example, the concentration of air pollution in a city or downwind of a major power plant (project) or soil erosion in a river basin affected by changing landuse -- the effective display eg., as a topical map, is an important component of providing decision relevant information, and understanding the physical aspects of the decision problem. Similarly, the ability of expert systems to describe their function in terms of near-natural language rules and explain, step by step, their reasoning, supports understanding, and thus acceptance.