AUTHOR=Mahendra Rekha Apoorva , Nagarajan Vaani 

TITLE=3D reconstruction and morphological characteristic study of Abdullahpuram palace building in Vellore-Bangalore NH using terrestrial LiDAR data

JOURNAL=Frontiers in Remote Sensing

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1622210

DOI=10.3389/frsen.2025.1622210

ISSN=2673-6187

ABSTRACT=Effective preservation of cultural heritage structures requires precise, non-destructive, and scalable documentation techniques. However, conventional survey methods often fail to capture intricate geometric features and to quantify localized surface deterioration such as spalling and plaster loss. Terrestrial LiDAR scanning provides high-resolution point cloud data well-suited for such applications, though challenges persist in data registration, segmentation, and deterioration quantification. This study applies terrestrial LiDAR technology to the documentation of the Abdullahpuram Palace, a 19th-century heritage building located in Vellore, Tamil Nadu, India, which exhibits Indo-Saracenic architectural influences (as reported by the Tamil Nadu Heritage Commission, 2019). Multiple scans were registered using Cyclone 360, and the data were pre- and post-processed in CloudCompare for noise filtering, segmentation, and geometric refinement. Surface deterioration was assessed by extracting 3D surface profiles and quantifying volume of material loss using convex hull and raster-based analyses in MeshLab and ArcGIS, respectively. It is to be noted that material loss represents the surface-level deterioration rather than direct evidence of structural failure. Additionally, an octree-based downscaling approach was also implemented to facilitate multi-scale visualization and improve computational efficiency for large datasets. The methodology enhances heritage documentation, supports objective condition assessment, and aligns with sustainable conservation principles articulated in SDG 9 and 11.4. The findings highlight the potential of terrestrial LiDAR and advanced point cloud processing to develop accurate, scalable, and non-invasive documentation strategies for heritage conservation globally.