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. ... Read more

Regional-scale assessment of the damage caused by earthquakes to structures is crucial for post-disaster management. While remote sensing techniques can be of great help for a quick post-event structural assessment of large areas, currently available methods are limited to the detection of severely-damaged buildings. Furthermore, remote sensing-based assessment methods typically provide only qualitative results, as they lack integration with information on the building's behaviour in response to seismic-induced ground shaking. In this study, we developed a new methodology that uses airborne Light Detection And Ranging (LiDAR) data in combination with structural indicators of building response to provide a quantitative assessment of earthquake-induced damage at a regional scale. LiDAR datasets collected before and after an earthquake are used to measure residual displacements of building roofs. The resulting lateral drift estimations are used to quantify the level of damage for a specific building typology. Application to the LiDAR datasets collected before and after the 2014 earthquake in Napa Valley, California, demonstrates the capability of the proposed method to detect moderate levels of structural damage, proving its potential for faster and more accurate support to post-disaster management. ... Read more

Earthquakes are natural hazards leading to the greatest human and economic losses, which are mostly due to structural collapses. Rapid identification and assessment of earthquake-induced damage to structures is therefore an essential component of the emergency response, and instrumental to effective reconstruction plans. Typically, structural damage assessment is conducted through building-by-building inspections during post-earthquake field reconnaissance missions. These missions are expensive and time-consuming, especially if large areas need to be investigated. Remote sensing techniques provide a relatively low-cost, wide-area alternative to in-situ monitoring. Classification and change detection based on pre- and post-event optical and synthetic aperture radar (SAR) satellite images are the most used approaches to detect damaged structures after earthquakes. However, these techniques only provide qualitative observations of collapsed or severely damaged structures. In this work, we present a new approach for the quantitative assessment of earthquake-induced structural damage based on displacement measurements acquired by Airborne Light Detection And Ranging (LiDAR). The approach is based on the integration between LiDAR-based observations and structural indicators of damage. The application to the analysis of 684 buildings affected by the 2014 Napa earthquake, in California, demonstrates a good agreement between the LiDAR-based results and independent in-situ observations. This work sets the basis for the innovative exploitation of remote sensing data in disaster management. ... Read more