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Title: MULTICRITERIA SPATIAL DECISION SUPPORT SYSTEMS FOR AGRICULTURE: OVERVIEW, APPLICATIONS, AND FUTURE RESEARCH DIRECTIONS

Author
item Ascough Ii, James
item RECTOR, HARRIET - 5401-00-00
item HOAG, DANA - COLORADO STATE UNIVERSITY
item McMaster, Gregory
item Vandenberg, Bruce
item Shaffer, Marvin
item Weltz, Mark
item Ahuja, Lajpat

Submitted to: Environmental Modeling International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/24/2002
Publication Date: 6/24/2002
Citation: Ascough II, J.C., Rector, H.D., Hoag, D.L., Mcmaster, G.S., Vandenberg, B.C., Shaffer, M.J., Weltz, M.A., Ahuja, L.R. 2002. Multicriteria spatial decision support systems for agriculture: overview, applications, and future research directions. Environmental Modeling International Conference Proceedings. IN: A.E. Rizzoli and A.J. Jakeman (Eds.), Integrated Assessment and Decision Support Proceedings of the 1st Biennial Meeting of the IEMSS. June 24-27, 2002, Lugano, Switzerland. Vol. 3, pp. 175-180.

Interpretive Summary: Decision makers historically have indicated that inaccessibility of required geographic data and difficulties in synthesizing various recommendations are primary obstacles to spatial problem solving. Studies have shown that the quality of decisions (i.e., the ability to produce meaningful solutions) can be improved if these obstacles are lessened or removed through an integrated systems approach, such as a spatial decision support system (SDSS). In addition, multicriteria decision making (MCDM) and a wide range of related methodologies offer a variety of techniques and practices to uncover and integrate decision makers? preferences in order to solve "real-world" GIS-based planning and management problems. However, because of conceptual difficulties (i.e., dynamic preference structures and large decision alternative and evaluation criteria sets) involved in formulating and solving spatial decision problems, researchers have developed multicriteria-spatial decision support systems (MC-SDSS). In this paper, we present a general overview of MC-SDSS, briefly review applications of MC-SDSS to a broad range of decision problems, and provide direction for future trends and research in this area.

Technical Abstract: Decision makers historically have indicated that inaccessibility of required geographic data and difficulties in synthesizing various recommendations are primary obstacles to spatial problem solving. Studies have shown that the quality of decisions (i.e., the ability to produce meaningful solutions) can be improved if these obstacles are lessened or removed through an integrated systems approach, such as a spatial decision support system (SDSS). In addition, multicriteria decision making (MCDM) and a wide range of related methodologies offer a variety of techniques and practices to uncover and integrate decision makers? preferences in order to solve "real-world" GIS-based planning and management problems. However, because of conceptual difficulties (i.e., dynamic preference structures and large decision alternative and evaluation criteria sets) involved in formulating and solving spatial decision problems, researchers have developed multicriteria-spatial decision support systems (MC-SDSS). In this paper, we present a general overview of MC-SDSS, briefly review applications of MC-SDSS to a broad range of decision problems, and provide direction for future trends and research in this area.