SAR-based maps that can detect phase difference between satellite images have been utilized frequently in recent years to map damage after major natural and anthropogenic disasters. Some of the most popular and easily accessible such maps are Damage Proxy Maps (DPMs) which have been developed by the National Aeronautics and Space Administration – Jet Propulsion Laboratory (NASA-JPL). SAR-based maps like DPMs can be a great resource for emergency response and disaster reconnaissance teams, who need to know where significant damage has taken place shortly after a disaster has occurred. Although experience has shown that these maps can be produced quickly, DPMs have yet to be extensively validated in an objective manner. Timothy O’Donnell is a PhD candidate in the Civil and Environmental Engineering Department at UCLA. His research is focused on validating the ability of DPMs to detect damage after major disasters due to various types of damaging phenomenon such as liquefaction, structural damage, and surface fault rupture. To do this, he is utilizing DPMs and field reconnaissance data from three major disaster events: the 2016 Central Italy earthquake sequence, the 2019 Ridgecrest earthquake sequence, and the 2020 Port of Beirut, Lebanon explosion. The goal of his research is to quantify DPMs effectiveness and delineate DPMs strengths and limitations in a manner that is accessible for the civil engineering community.

Ground motion models (GMMs) are used by the engineering community to estimate ground motion intensity measures given the source earthquake and wave propagation path. The Next Generation Attenuation (NGA) projects have developed GMMs for the main areas of interest: NGA-sub for subduction earthquakes, NGA-West and NGA-West2 for active tectonic regions and NGA-East for stable continental regions. During the development of NGA-East, the GMMs were calibrated by correcting central and eastern North America (CENA) data to a reference site condition using a site amplification model appropriate for active tectonic regions since an equivalent model for stable continental regions had not been developed yet. Moreover, unlike in previous projects, the core GMM and the site amplification model were not developed iteratively and in a coordinated manner. We demonstrate that the combination of the NGA-East GMMs and CENA-specific site amplification factors leads to biased ground motions at short periods, whereas longer periods are relatively unbiased. New and original data will be used in mixed effects analysis, informed by new simulations of 1D ground response, to identify the primary sources of that bias (i.e., GMM or site amplification model) and provide the necessary adjustments to remove it.