Greenways for rural sustainable development: An integration between geographic information systems and group analytic hierarchy process

Policy makers have recently begun to agree on environmental, economic and social aspects of rural areas that are enhanced according to the European Union (EU) Common Agricultural Policy (CAP), and in particular in the national Rural Development Programmes (RDPs).Greenways are an acknowledged tool within the CAP because they help to protect and manage environmental heritage, promote economic activities and enhance the social assets of rural areas; furthermore, given their natural ability to simultaneously connect these resources, greenways promote Rural Sustainable Development (RSD).Nevertheless, several issues can create difficulties for policy makers in the implementation of greenways for promoting RSD, and the research about greenway planning shows that government agencies do not adopt a collaborative approach with each other or with stakeholders.Thus, our research aims to provide a common decision making framework enabling both greenway implementations by policy makers (top-down strategy), and the choice among various alternatives evaluated by different stakeholders (bottom-up strategy). This helps policy makers to identify the greenway that best promotes the objectives of RSD, and therefore facilitates planning and management of the 2014-2020 RDP funds reserved for greenway implementation. This decision making framework consists of a Multiple Criteria Spatial Decision Support System (MC-SDSS) that integrates a Geographic Information System (GIS) with the Multiple Criteria Decision Aiding (MCDA) technique "Group Analytic Hierarchy Process" (GAHP). The validity of this MC-SDSS was tested on three rural municipalities of Apulia Region (Southern Italy). In particular, a GIS was used to detect the rural resources and existing linear elements, which were used to perform overlay mapping to identify four greenways. We then established a hierarchy consisting of four groups of stakeholders, seven criteria and twenty-one sub-criteria. Finally, GAHP was applied to aggregate the preferences of stakeholders and obtain the ranking. Specifically, Greenway 4 is the preferred alternative for every stakeholder, because it best connects cultural heritage, land use and urban centers and it scored the highest preference concerning route characteristics. The second alternative is Greenway 1, because it best links the interchange nodes, and the third alternative is Greenway 3, preferred for its panoramic scenery. Greenway 2 is the last alternative, because it performs worst in connecting urban centers, land use and interchange nodes, and scored the lowest preference for route characteristics. The above results were easily understood and accepted by the stakeholders and Local Action Groups (LAG) policy makers, because the methodology provided clear outcomes that completely reflect their opinions.