A Workflow for Urban Heritage Digitization: From UAV Photogrammetry to Immersive VR Interaction with Multi-Layer Evaluation
Chengyun Zhang, Guiye Lin, Yuyang Peng, Yanshun Yu
Abstract
Urban heritage documentation often separates 3D data acquisition from immersive interaction, limiting both accuracy and user impact. This study develops and validates an end-to-end workflow that integrates UAV photogrammetry with terrestrial LiDAR and deploys the fused model in a VR environment. Applied to Piazza Vittorio Emanuele II in Rovigo, Italy, the approach achieves centimetre-level registration, completes roofs and upper façades that ground scanning alone cannot capture, and produces stable, high-fidelity assets suitable for real-time interaction. Effectiveness is assessed through a three-layer evaluation framework encompassing vision, behavior, and cognition. Eye-tracking heatmaps and scanpaths show that attention shifts from dispersed viewing to concentrated focus on landmarks and panels. Locomotion traces reveal a transition from diffuse roaming to edge-anchored strategies, with stronger reliance on low-visibility zones for spatial judgment. Post-VR interviews confirm improved spatial comprehension, stronger recognition of cultural values, and enhanced conservation intentions. The results demonstrate that UAV-enabled completeness directly influences how users perceive, navigate, and interpret heritage spaces in VR. The workflow is cost-effective, replicable, and transferable, offering a practical model for under-resourced heritage sites. More broadly, it provides a methodological template for linking drone-based data acquisition to measurable cognitive and cultural outcomes in immersive heritage applications.