Sep 2026· Advances in Engineering and Information Sciences· Vol 2· 0 citations· 4 references
Abstract
The Caraga Region, contributing only 2.3% of total domestic tourist arrivals, requires data-driven spatial planning. This study applied the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to 8,081 tourism-related Points of Interest (POIs) from the Humanitarian OpenStreetMap (HOTOSM) Philippines repository to identify and map tourism hotspots across Caraga's five provinces. Using optimal parameters of ε = 1.0 km and MinPts = 4, the algorithm identified 196 spatially distinct clusters validated by a Silhouette Score of 0.7555 and Davies-Bouldin Index of 0.2009. Results reveal three spatial patterns coastal concentration, urban hub, and dispersed minor clusters alongside a core-periphery inequality across provinces. Five data-driven development insights are generated for the Department of Tourism, Regional Development Council XIII, and Local Government Units to guide evidence-based, spatially informed, and sustainable regional tourism planning in Caraga.
Contemporary tourism is increasingly shifting from a volume-based model toward a quality-oriented approach that
emphasizes sustainability, local identity, and the redistribution of tourism activities to secondary cities and rural areas. This study
aims to quantitatively assess the spatial distribution patterns and clus...
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