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. @en

This paper discusses centrifuge modelling challenges when exploring the response of surface structures to tunnelling in sand. The model tunnel employed consists of an interior brass cylinder surrounded by water inside a sealed flexible latex lining. Prior to extracting water to simulate tunnelling volume loss, soil displacements obtained during centrifuge acceleration indicate that this flexible tunnel can lead to differential settlements during spin-up. These ground movements are triggered by a change of the tunnel shape due to a stress imbalance between the tunnel and the surrounding soil. Additionally, it was found that surface structures interact with the model tunnel during the spin-up, and thus can change the amount of differential surface settlements, depending on the structure location. As a consequence, some differential settlements may be imposed on the structures as the g-level increases. Results indicate the necessity to consider these effects when interpreting the results of the subsequent tunnelling simulation.@en