Gemelli, A., Mancini, A., Diamantini, C., Longhi, S.
2013, IX, 84 p. 34 illus., 14 illus. in color.
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Presents a Geographic Information System (GIS) dedicated to the cost effectiveness analysis of a renewable energy source, the low temperature geothermal energy, which is used for heating domestic and public environments
Focuses on the design of system components that transform geographic data into knowledge useful for analysis and decision-making on the economic exploitation of geothermal energy
Provides a multidisciplinary approach to GIS design, which mixes the contribution from engineering, science and economics
Through the results of a developed case study of information system for low temperature geothermal energy, GIS to Support Cost-effective Decisions on Renewable Sources addresses the issue of the use of Geographic Information Systems (GIS) in evaluating cost-effectiveness of renewable resource exploitation regional scale. Focusing on the design of a Decision Support System, a process is presented aimed to transform geographic data into knowledge useful for analysis and decision-making on the economic exploitation of geothermal energy. This detailed description includes a literature review and technical issues related to data collection, data mining, decision analysis for the informative system developed for the case study. A multi-disciplinary approach to GIS design is presented which is also an innovative example of fusion of georeferenced data acquired from multiple sources including remote sensing, networks of sensors and socio-economic censuses. GIS to Support Cost-effective Decisions on Renewable Sources is a pratical reference for engineers, managers and researchers involved in the design of GIS, decision support systems, investment planning/strategy in renewable energy and ICT innovation in this field.
Content Level »Research
Keywords »Building with Renewable Energy - Geographic Information System - Geospatial Data Fusion - Geospatial Decision Support System - Low Temperature Geothermal Energy - Remote Sensing
PART I.- Preliminary Study.- 1.Decision environment of renewable energy: the case of geothermal energy.- 2.GIS supported decision making..- PART II. Case Study.- 3.GIS supported decision making for low temperature geothermal energy in Central Italy.- 4.Data collection.- 5.Feature analysis: selecting decision criteria.- 6.Decision analysis: choosing the right plant.- 7.Regional atlas supporting the decision-making process.- 8.Conclusive remarks