Terra-vision-the integration of scientific analysis into the decision-making process

Providing an effective tool for risk assessment of terrestrial environmental resources requires a decision support system which will combine scientific analysis and the decision-making process. The goal of such a system is to provide a scientifically-based method for establishing and evaluating the potential effects of a policy or decision. To meet this goal a computing platform must be established which can run interactively a diverse set of models representing environmental, atmospheric, economic and political issues, and provide an integrated visualized output for decision makers. The decision support tool must be able to manipulate and display disparate information at the appropriate scale, over time and space. Hierarchical modelling, integrated information management systems, geographical information systems, and visualization systems are enabling technologies which provide one possible framework for implementing an effective decision support system. An application-oriented approach was used to examine the requirements and relationships needed to integrate analytical models tightly into a general decision support system. Forest modelling and its relationships to global climate change were the specific application used to prototype such an integrated system. This article introduces the scope and goals established using this application- oriented approach to developing a decision support system for risk assessment of terrestrial environmental resources, TERRA-Vision. It identifies critical design issues, such as the scaling, inter-operability and presentation of information. The article presents a conceptual framework, a design methodology and software used to develop the TERRA-Vision proof-of-concept demonstration system. Lessons learned are provided as part of the conclusions and areas identify where prototype development validated the conceptual framework and provided valuable insight on key issues relating to the development of more generalized decision support platforms. Finally, the conceptual framework is extended to provide an effective method for the development of an integrated scientific analysis and decisionmaking process. © 1993 Taylor & Francis Group, LLC.

Duke Scholars

Author Dean L. Urban Environmental Sciences and Policy