Mara Franco

By Ana Vulevic, Stabak Roy, Rui Alexandre Castanho, Mara Franco and Gualter Couto

Geo-tourism, an emerging field that focuses on the natural and cultural heritage of a region, offers a unique opportunity to promote sustainable tourism and foster local economic development. This study aims to assess the geo-tourism potential Danube region in Serbia, a natural diverse and culturally rich region of Serbia, Western Balkan, and Southeastern Europe, using a comprehensive methodology that incorporates geo-statistical and machine learning tools. A dataset comprising various geographical, and cultural factors was collected from reliable sources, including, protected areas, tourism statistics, cultural heritage inventories and satellite imagery. Geo-statistical analyses were performed to identify spatial patterns and relationships among the collected variables. Techniques such as spatial autocorrelation, hotspot analysis, and interpolation methods were employed to reveal concentrations of geo-tourism resources, hotspots, clusters, and areas in need of conservation. The results of this study provided valuable insights into the geo-tourism potential of the Danube region. The spatial analysis revealed several hotspots. Machine learning models accurately predicted tourism demand based on variables such as accessibility, cultural heritage, and natural landscapes. These findings can guide policymakers that, using the power of geo-statistical and machine learning tools, the Danube region in Serbia can unlock its full geo-tourism potential.

Part of the book: Urban Agglomeration - Extracting Lessons for Sustainable Development [Working title]