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Decision support systems for environmental management: a case study on wastewater from agriculture.
Massei, Gianluca; Rocchi, Lucia; Paolotti, Luisa; Greco, Salvatore; Boggia, Antonio.
Afiliação
  • Massei G; Dept. of Agricultural, Environmental and Food Sciences, University of Perugia, Borgo XX Giugno, 74, 06121 Perugia, Italy. Electronic address: agr.gianluca.massei@gmail.com.
  • Rocchi L; Dept. of Agricultural, Environmental and Food Sciences, University of Perugia, Borgo XX Giugno, 74, 06121 Perugia, Italy. Electronic address: lucia.rocchi@unipg.it.
  • Paolotti L; Dept. of Agricultural, Environmental and Food Sciences, University of Perugia, Borgo XX Giugno, 74, 06121 Perugia, Italy. Electronic address: luisa.paolotti@gmail.com.
  • Greco S; Dept. of Economics and Enterprise, Corso Italia, 55, 95129 Catania CT, Italy; Portsmouth Business School, Operations & Systems Management University of Portsmouth, Portsmouth PO1 3DE, United Kingdom. Electronic address: salgreco@unict.it.
  • Boggia A; Dept. of Agricultural, Environmental and Food Sciences, University of Perugia, Borgo XX Giugno, 74, 06121 Perugia, Italy. Electronic address: antonio.boggia@unipg.it.
J Environ Manage ; 146: 491-504, 2014 Dec 15.
Article em En | MEDLINE | ID: mdl-25217251
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Técnicas de Apoio para a Decisão / Sistemas de Informação Geográfica / Águas Residuárias Tipo de estudo: Prognostic_studies País/Região como assunto: Europa Idioma: En Revista: J Environ Manage Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Técnicas de Apoio para a Decisão / Sistemas de Informação Geográfica / Águas Residuárias Tipo de estudo: Prognostic_studies País/Região como assunto: Europa Idioma: En Revista: J Environ Manage Ano de publicação: 2014 Tipo de documento: Article