TY - JOUR
T1 - A Workflow for Urban Heritage Digitization: From UAV Photogrammetry to Immersive VR Interaction with Multi-Layer Evaluation
AU - Zhang, Chengyun
AU - Lin, Guiye
AU - Peng, Y.
AU - Yu, Y.Y.
PY - 2025
Y1 - 2025
N2 - Highlights: What are the main findings? An end-to-end workflow integrates UAV photogrammetry, LiDAR, and VR for heritage. Three-layer evaluation shows focused attention, edge-anchored movement, and clearer cultural understanding. What is the implication of the main finding? UAV-enabled completeness improves both geometric fidelity and user experience in VR. The workflow is affordable and transferable, supporting under-resourced heritage sites. 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.
AB - Highlights: What are the main findings? An end-to-end workflow integrates UAV photogrammetry, LiDAR, and VR for heritage. Three-layer evaluation shows focused attention, edge-anchored movement, and clearer cultural understanding. What is the implication of the main finding? UAV-enabled completeness improves both geometric fidelity and user experience in VR. The workflow is affordable and transferable, supporting under-resourced heritage sites. 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.
KW - virtual reality (VR)
KW - cultural heritage
KW - eye-tracking
KW - LiDAR point cloud
KW - drones
KW - UAV photogrammetry
UR - http://www.scopus.com/inward/record.url?scp=105020021041&partnerID=8YFLogxK
U2 - 10.3390/drones9100716
DO - 10.3390/drones9100716
M3 - Article
SN - 2504-446X
VL - 9
JO - Drones
JF - Drones
IS - 10
M1 - 716
ER -