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Biogas plants site selection integrating Multicriteria Decision Aid methods and GIS techniques: A case study in a Portuguese region

handle: 10316/43202
This work addresses the problem of determining the most suitable sites for locating biogas plants using dairy manure as feedstock, specifically in the Entre-Douro-e-Minho Region in Portugal. A Multicriteria Spatial Decision Support System is developed to tackle this complex multicriteria decision-making problem, involving constraints and many environmental, economic, safety, and social factors. The approach followed combines the use of a Geographic Information System (GIS) to manage and process spatial information with the flexibility of Multicriteria Decision Aid (MCDA) to assess factual information (e.g. soil type, slope, infrastructures) with more subjective information (e.g. expert opinion). The MCDA method used is ELECTRE TRI, an outranking-type method that yields a classification of the possible alternatives. The results of the performed analysis show that the use of ELECTRE TRI is suitable to address real-world problems of land suitability, leading towards a flexible and integrated assessment.
- Instituto Politécnico de Viana do Castelo Portugal
- Institute for Systems Engineering and Computers Portugal
- University of Coimbra Portugal
- Polytechnic Institute of Viana do Castelo Portugal
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).87 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
