A geospatial decision support system for ecotourism: a case study in the Campania region of Italy

Nowadays, the business of ecotourism and rural tourism is a very important activity for many inland areas, enabling them to both produce important income and sustain the rural economy. Moreover, sustainable tourism is included in the UN 17th Sustainable Development Goal, which is to be achieved by 2030 (SDG 8.9 and SDG 12). Recent progress in digital tourism promises to deliver important changes to this activity, but most of this progress is addressed at well-known tourist destinations, so not dealing with the challenge of inland, rural and ecotourism. It is within this framework that this paper attempts to demonstrate that a new type of geoSpatial Decision Support System (S-DSS), developed on a Geospatial Cyberinfrastructure (GCI) and with a substantial interdisciplinary core, could provide a valuable web-based operational tool which may be offered to both ecotourism and rural tourism end-users, planners and policy makers, so that they might better plan and manage this type of sustainable tourism. The S-DSS platform has also been designed to encourage use by the multi-user community (farmers, tourism enterprises, associations and public bodies). The methodology is linked to the creation of a GCI platform (www.landsupport.eu) that supports the acquisition, management, processing and analysis of both static (e.g. soil, geology) and dynamic data (e.g. environmental and daily climatic data), together with data visualization and computer on-the-fly applications, in order to perform modelling, all of which is potentially accessible via the Web. The S-DSS tool known as EcoSmarTour is demonstrated through a case study of the Campania region (South Italy) and, by connecting database and modelling, it aims to deliver a large amount of information that will improve knowledge of the territory, manage scenario analysis, produce maps and evaluate potential ecotourism footpaths or areas of interest, thus enabling the provision of better information on the entire ecotourism sector. The tool will also be demonstrated through reference to a short selection of additional use cases from elsewhere in Europe. Most importantly, the approach adopted is highly transferable because it relies on very general algorithms that can be easily applied wherever the necessary data are available.