LiDAR-based assessment of earthquake-induced building damage
The Napa case study
F. Foroughnia (TU Delft - Civil Engineering & Geosciences)
V. Macchiarulo (TU Delft - Civil Engineering & Geosciences)
L. Berg (University of California)
M. DeJong (University of California)
P. Milillo (University of Houston, Deutsches Zentrum für Luft- und Raumfahrt (DLR))
K.W. Hudnut (Southern California Edison, Rosemead, United States)
K. Gavin (TU Delft - Civil Engineering & Geosciences)
G. Giardina (TU Delft - Civil Engineering & Geosciences)
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Abstract
Earthquakes can result in significant human and economic losses, primarily caused by building collapses over vast areas. It is crucial to identify and assess structural damage on a regional scale to effectively respond to emergencies and manage post-disaster scenarios. Typically, the evaluation of structural damage involves labour-intensive inspections of individual buildings during field reconnaissance missions conducted after earthquakes. These missions can be costly and time-consuming, particularly when large areas require investigation Remote sensing techniques offer a cost-effective alternative to on-site inspections by providing frequent observations over vast regions. However, existing remote sensing techniques have limitations in identifying damage beyond severe or complete building collapses. These techniques typically rely on qualitative observations of building shape and regularity derived from satellite imagery, failing to incorporate structural information about the building response. As a result, quantitative assessment of damage and the detection of moderate levels of damage remain challenging. In this study, we propose a new methodology that uses building displacements as key indicators of the building response to earthquakes, enabling a quantitative assessment of damage. Airborne Light Detection And Ranging (LiDAR) data acquired before and after an earthquake were used to estimate seismic-induced building displacements. Then, the LiDAR-based building displacements were integrated with structural damage indicators to quantify building damage levels. To validate the proposed approach, we applied it to analyse 684 buildings affected by the 2014 South Napa earthquake in California. Results showed that most structures experienced slight to moderate damage, indicating good agreement with in-situ observations. This work highlights the potential of remote sensing LiDAR data in accurately quantifying damage levels and facilitating effective disaster management.