Spatial clustering-based method for Italian marginal areas toward the sustainable regeneration

Abstract

In Italy, there is a clear disparity between cities and villages located in marginal areas. The progressive depopulation of inland areas and the urban polarization represent consolidated dynamics difficult to adapt to the new paradigm of sustainable development. The post-Covid-19 pandemic scenario offers the opportunity to redefine new parameters of intervention and new visions for the regeneration of villages in accord with the new challenges of decentralization and distancing. The project «Renaissance of villages for the revitalization of marginal areas» (2021) aims to create the conditions to repopulate and rebalance shrinking territories by establishing new centres of attractiveness. This project envisages the active involvement of municipalities to implement multi-sectoral analysis and spatial assessment approaches in planning processes. It intends to develop an interactive web dashboard for local authorities and spatial planners to create both a learning environment and a participative spatial decision support system for future local policy actions toward sustainable local development. This study presents the project’s preliminary phase which aims to create the general framework of the web dashboard. A reconstruction of the village definition and the spatial selection of villages throughout Italy are presented as innovative aspects since the absence of an agreed definition of the village in the national and international level documents. Moreover, this study provides a quantitative spatial multivariate analysis cluster that analyzes, and groups Italian territories based on socioeconomic dynamics. The result of this analysis allows us to divide the territory into archetypes and to structure a framework that supports the definition of future scenarios for the regeneration of small urban areas considering the diversified needs and potential of the villages belonging to specific archetypes analyzed in the study.