A Knowledge-Based Approach for the Implementation of a SDSS in the Partenio Regional Park (Italy)
The paper recommends a methodology for data gathering and processing through the spatial analysis techniques and the combinatorial multi-criteria procedure of Weighted Linear Combination (WLC). The purpose concerns the spatial problem structuring in a com
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Abstract. The paper recommends a methodology for data gathering and processing through the spatial analysis techniques and the combinatorial multi-criteria procedure of Weighted Linear Combination (WLC). The purpose concerns the spatial problem structuring in a complex decisional context lacking in the geographical dataset. The processing of data and information provided by VGIs and Open Systems is crucial for the enrichment of spatial datasets in these circumstances, but it is advisable to make attention about the data reliability and the known problems of the geographic dataset, i.e. Modifiable Areal Unit Problem (MAUP). The method was tested with the case study of 27 Municipalities around the Partenio Regional Park, in the South of Italy. Within the SDSS, the multidimensional landscape’s indicators were combined with data gathering on the field, in order to build an evolving informative system. A multidimensional approach, focused on the recognition of environmental, social, economic and cultural resources, was chosen providing some strategies of enhancement for the overviewed landscape of the Park. The evaluation of the policy and actions for the examined regions generated scenario-maps through multi-criteria procedures and GIS tools. Keywords: Landscape Spatial Decision Support System (SDSS) Volunteered Geographic Information (VGIs) Weighted Linear Combination (WLC) Spatial multi-criteria analysis
1 Introduction The paper introduces an application of a Spatial Decision Support System (SDSS) for the landscape evaluation, focused on the development of tourism and recreation services in a region around a natural park, the Partenio Regional Park, in the South of Italy. The decision problem examines many issues concerning the relationships and trade-off among economic, social, environmental and cultural values. In order to investigate the different components, the recent literature recommends gathering hard and soft data about the region, understanding the spatial effects of a decision on the landscape (Cerreta et al. 2014; Fusco Girard et al. 2014) and combining institutional data with open source. During the last twenty years, the progress in remote-sensing and power computing extended the spatial component evaluation to the decision-making © Springer International Publishing Switzerland 2016 O. Gervasi et al. (Eds.): ICCSA 2016, Part IV, LNCS 9789, pp. 111–124, 2016. DOI: 10.1007/978-3-319-42089-9_8
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process. Moreover the spatial analysis tools provided by Geographic Information System (GIS) aid the decision-maker (DM) in the data management and analysis of spatial features, in the solution of ill-structured problems in an iterative way, in the scenario evaluation, in report generation and visualization of spatial indicators (Sugumaran and de Groote 2010). Including the multidimensional landscape features within the SDSS procedures is a practice that can be continuously improved and empowered (Cerreta and Fusco Girard 2016). An open issue concerns the spatial problem structuring i
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