Decision Support Systems for environmental management: A case study on wastewater from agriculture

JOURNAL OF ENVIRONMENTAL MANAGEMENT

卷:146

Article

Massei, Gianluca¹  Rocchi, Lucia¹  Paolotti, Luisa¹  Greco, Salvatore^2,3  Boggia, Antonio¹ 

[1] Univ Perugia, Dept Agr Environm & Food Sci, I-06121 Perugia, Italy

[2] Corso Italia, Dept Econ & Enterprise, I-95129 Catania, CT, Italy

[3] Operat & Syst Management Univ Portsmouth, Portsmouth Business Sch, Portsmouth PO1 3DE, Hants, England

关键词: GIS;    Multicriteria analysis;    GIS-MCDA integration;    Spatial Decision Support Systems;    Modular package;   

DOI  :  10.1016/j.jenvman.2014.08.012

来源: Elsevier

【 摘 要 】

Dealing with spatial decision problems means combining and transforming geographical data (input) into a resultant decision (output), interfacing a Geographical Information System (GIS) with Multi-Criteria Decision Analysis (MCDA) methods. The conventional MCDA approach assumes the spatial homogeneity of alternatives within the case study area, although it is often unrealistic. On the other side, GIS provides excellent data acquisition, storage, manipulation and analysis capabilities, but in the case of a value structure analysis this capability is lower. For these reasons, several studies in the last twenty years have given attention to MCDA-GIS integration and to the development of Spatial Decision Support Systems (SDSS). Hitherto, most of these applications are based only on a formal integration between the two approaches. In this paper, we propose a complete MCDA-GIS integration with a plurality of MCDA methodologies, grouped in a suite. More precisely, we considered an open-source GIS (GRASS GIS 6.4) and a modular package including five MCDA modules based on five different methodologies. The methods included are: ELECTRE I, Fuzzy set, REGIME analysis, Analytic Hierarchy Process and Dominance-based Rough Set Approach. Thanks to the modular nature of the package, it is possible to add new methods without modifying the existing structure. To present the suite, we applied each module to the same case study, making comparisons. The strong points of the MCDA-GIS integration we developed are its open-source setting and the user friendly interface, both thanks to GRASS GIS, and the use of raster data. Moreover, our suite is a genuine case of perfect integration, where the spatial nature of criteria is always present. (C) 2014 Elsevier Ltd. All rights reserved.

【 授权许可】

Free