Use of post-earthquake point cloud data for forensic evaluation of failures in masonry structures

Abstract

Abstract Post-earthquake reconnaissance of engineering structures aims to collect the essential data required for forensic investigations of failures. These investigations inform time-critical repair, stabilisation and demolition decisions after an earthquake. Current reconnaissance procedures rely on visual observations and manual surveying, which do not provide adequate data for the forensic analysis of historic masonry structures. This study shows how an alternative form of data, point clouds from laser scanning and photogrammetry, can be used to conduct detailed forensic work. Case studies from the 2023 Turkey earthquakes are used to illustrate how point clouds were employed to 1) quantify the geometry of load-bearing systems, 2) assess construction quality, 3) detect geometric distortions and defects, and 4) provide data to generate and evaluate numerical models. The examples highlight the new insight provided by this alternative form of data. The dataset collected as a part of this study is shared open access to enable further investigations: https://github.com/Yilong-Yang/Shared-Data---BEE-2025.