Multi-Temporal 3D Point Cloud Analysis for Heritage Site Monitoring and Preservation

Dear Colleagues,

Three-dimensional (3D) point clouds have become an essential resource for documenting and analysing cultural heritage, seeing widespread adoption over the past two decades. Recent advances in active remote sensing (e.g., terrestrial and aerial LiDAR) and photogrammetry (including drone-based imaging) now enable the efficient acquisition of high-resolution 3D models of heritage sites. Moving beyond static documentation, the emerging practice of multi-temporal 3D point cloud analysis—comparing repeat surveys of structures over time—offers a powerful means to detect subtle changes, deterioration, or damage. This capability is increasingly vital as heritage sites worldwide face threats from both human actions and environmental factors. Conflicts, looting, deliberate destruction, and uncontrolled urban expansion have inflicted severe damage on archaeological sites and monuments in many regions, while natural weathering and climate-related events further endanger these irreplaceable resources. Timely multi-temporal monitoring of structural changes can thus inform more proactive and targeted preservation efforts.

This Special Issue aims to showcase cutting-edge research on multi-temporal 3D point cloud techniques for heritage monitoring, aligning with the scope of Remote Sensing by highlighting how geospatial technologies contribute to real-world heritage conservation. We welcome contributions that demonstrate the innovative use of 3D remote sensing data to safeguard archaeological sites, historic buildings, and cultural landscapes. Such studies underscore the broader value of remote sensing, which allows multitemporal data acquisition at increasingly high resolutions and across global scales, making it possible to monitor even hard-to-access or widespread heritage assets. Interdisciplinary approaches that integrate 3D point clouds with other data (e.g., multispectral imagery, thermal scans or historical records) or that apply novel algorithms (machine learning, change detection, etc.) are encouraged, as these reflect the state-of-the-art in heritage science and align with the journal’s mission to advance remote sensing applications.

We invite the submission of original research articles, review papers, technical notes, and case studies on topics including, but not limited to, the following:

• Multi-temporal LiDAR or photogrammetric surveys for change detection in cultural heritage sites;
• Monitoring climate change impacts (e.g., erosion, weathering) on monuments and archaeological landscapes;
• Assessing damage from conflicts, wars, or vandalism using 3D point cloud comparisons;
• Techniques for detecting and quantifying structural degradation (cracks, deformations, material loss) over time;
• Data fusion of 3D point clouds with optical, multispectral, or thermal remote sensing data for enhanced monitoring;
• Development of digital twins, HBIM (Historic Building Information Modelling), or other 3D documentation tools to support conservation decisions;
• Evaluation of approaches to point cloud processing in relation to cultural heritage analysis;
• Innovative applications of machine learning or deep learning for automated point cloud analysis in heritage preservation.

Dr. Nicodemo Abate
Dr. Antonio Minervino Amodio
Guest Editors

Dr. Alessia Frisetti
Guest Editor Assistant

Manuscript Submission Information

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