Περίληψη
								
								In land management issues, decision makers are often dealing with complex
        and multifaceted problems. They must ensure both the sustainable usage of natural resources
        and economic development. They have to balance conflicting objectives. They also face the
        ‘Never In My BackYard’ (NIMBY) phenomenon ?the citizens rising opposition when undesirable
        but indispensable interventions are concretized and touch upon their local societies. The
        combined use of Geographical Information Systems (GIS) based tools and decision analysis
        methods can help to overcome these difficulties. This approach provides a consistent
        framework for dealing with conflicting objectives, in structured or semi-structured
        problems, and at the same time, allows the analysis to take account of the stakeholders’
        preferences. Recent developments in both fields expand the abilities of the Boolean overlay
        procedures, which are supported by the comme ...
								In land management issues, decision makers are often dealing with complex
        and multifaceted problems. They must ensure both the sustainable usage of natural resources
        and economic development. They have to balance conflicting objectives. They also face the
        ‘Never In My BackYard’ (NIMBY) phenomenon ?the citizens rising opposition when undesirable
        but indispensable interventions are concretized and touch upon their local societies. The
        combined use of Geographical Information Systems (GIS) based tools and decision analysis
        methods can help to overcome these difficulties. This approach provides a consistent
        framework for dealing with conflicting objectives, in structured or semi-structured
        problems, and at the same time, allows the analysis to take account of the stakeholders’
        preferences. Recent developments in both fields expand the abilities of the Boolean overlay
        procedures, which are supported by the commercial GIS software packages, to the
        consideration of decision criteria as well. To maximize the efficiency of the whole
        analysis, particular interest presents the combined use of Multiple Criteria Decision
        Analysis Methods with GIS based tools, forming the so called MultiCriteria Spatial Decision
        Support Systems (MC-SDSS), in order to rank the acceptable locations according to their
        relative importance in satisfying the objectives of the analysis. Moreover, the development
        of methodological frameworks and tools that allow suitability analysis performance to deal
        with the decision makers vagueness is considered, proposing synergies with the fuzzy
        extensions of the multiattribute decision making methods. The present thesis is organized in
        seven chapters. Analytically: The first chapter provides an introduction to current GIS
        capabilities and their restrictions in supporting suitability analysis procedures. After a
        sort review in multiattribute decision analysis, the main features of the decision flowchart
        in MultiCriteria Spatial Decision Support Systems (MCSDSS) is presented, followed by an
        extended bibliographical survey. The second chapter provides the basic principles of
        preference modeling in multiattribute utility theory. Moreover the major procedures that are
        used in criterion maps weights estimation and standardization are presented. The above
        procedures are discussed in detail since they are components of the proposed decision
        support system. The third chapter consists of the decision rules that are used in raster
        based MC-SDSS, such as WLC, Compromise Programming, TOPSIS, OWA. Considering that decision
        rules provide the basis for alternatives ordering, this chapter aims to describe, on the one
        hand, the assumptions that underling each approach and, on the other hand, to provide
        explanations about the choice behavior for each one separately. Fourth chapter, focuses on
        the Analytic Hierarchy Process and its use in spatial related decision problems. The
        procedures that are followed in the standard version of the method for deriving local
        priorities are discussed in detail as well as the method’s fuzzy extensions. As a result,
        SF-AHP is proposed that enables suitability analysis implementation using fuzzy variables
        for the decision parameters evaluation. In the fifth chapter, the main features of the
        PROMETHEE methods are described and a comparative analysis with the multiattribute utility
        theory is provided. Considering the large number of evaluation alternatives in raster based
        multicriteria suitability analysis computational limitations in methods implementation
        arise. The proposed here methodological framework entitled “SFPROMETHEE” allows the complete
        ranking of alternatives through the combined use of method’s fuzzy extension and the by
        criterion net flows estimations. Moreover it is noticed that SFPROMETHEE can be further
        combined with SF-AHP using fuzzy additive weighting as decision rule. Chapter six consists
        of a case study regarding the wastewater treatment problem. Considering issues of the
        decentralized treatment strategy, two hierarchical decision models are formed. The first
        enables different treatment options evaluation considering both quantitative and qualitative
        data, while the second is used for performing GIS based suitability analysis for natural
        systems site selection. Suitability index is estimated using ten different evaluation
        options considering SF-AHP and the two versions of SF-PROMETHEE. Results interpretation is
        achieved through spatial correlation performance of alternatives rankings derived by each
        one of the evaluation options implementation. Chapter seven provides thesis conclusions and
        highlights various issues for further research. Appendix A presents the major features and
        the rational behind the MC-SDSS use that has been developed in ArcGIS environment. The
        proposed SDSS supports hierarchical decision structures with a variety of WLC options and
        SF-AHP. Appendix B consists of the pairwise comparison matrices and the corresponding
        priorities estimation of the examined wastewater treatment options evaluation.
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