Enhancing quarry landscape interpretation with UAV LiDAR and morphometric clustering: A case study from the Euganean Hills, Italy

This study presents a methodological framework for early-stage archaeological landscape interpretation using light detection and ranging sensors (LiDAR) mounted to an unmanned aerial vehicle (UAV). By integrating high-resolution digital terrain models (DTMs), topographic measurements, k-means clustering, and field validation, the approach moves beyond traditional LiDAR applications for feature detection and towards a usage in preliminary classification and interpretation. Applied to the Euganean Hills in northeastern Italy, a geochemically diverse volcanic region with an extensive history of stone material procurement, this method enabled the identification of 89 potential quarry features, of which 84.9 % of surveyed features were validated as quarries or anthropogenic cuts. Analysis of the region's quarry morphologies and distribution produced several distinct quarry groupings suggestive of phases of exploitation and two case study sites ideal for future provenance research on Euganean volcanic breccias, whose use in Roman construction is known but whose sourced quarries have yet to be identified. Clustering analysis of spatial and morphometric variables indicated the heterogeneity of quarries in the region, differentiated modern and premodern sites, and provided statistical support for the grouping of quarries. These findings demonstrate the interpretive potential of UAV LiDAR in contexts where manned airborne laser scanning (ALS) data is insufficient for confident archaeological analysis and where comprehensive archaeological surveys are impeded by terrain. Beyond this regional case study, the framework offers a high-resolution, cost-effective workflow applicable to rugged, forested landscapes where rapid interpretation of anthropogenic features is needed to inform broader research design like geoarchaeological research or excavation strategies.