TY - JOUR A1 - Lilienkamp, Henning A1 - von Specht, Sebastian A1 - Weatherill, Graeme A1 - Caire, Giuseppe A1 - Cotton, Fabrice T1 - Ground-Motion modeling as an image processing task BT - introducing a neural network based, fully data-driven, and nonergodic JF - Bulletin of the Seismological Society of America N2 - We construct and examine the prototype of a deep learning-based ground-motion model (GMM) that is both fully data driven and nonergodic. We formulate ground-motion modeling as an image processing task, in which a specific type of neural network, the U-Net, relates continuous, horizontal maps of earthquake predictive parameters to sparse observations of a ground-motion intensity measure (IM). The processing of map-shaped data allows the natural incorporation of absolute earthquake source and observation site coordinates, and is, therefore, well suited to include site-, source-, and path-specific amplification effects in a nonergodic GMM. Data-driven interpolation of the IM between observation points is an inherent feature of the U-Net and requires no a priori assumptions. We evaluate our model using both a synthetic dataset and a subset of observations from the KiK-net strong motion network in the Kanto basin in Japan. We find that the U-Net model is capable of learning the magnitude???distance scaling, as well as site-, source-, and path-specific amplification effects from a strong motion dataset. The interpolation scheme is evaluated using a fivefold cross validation and is found to provide on average unbiased predictions. The magnitude???distance scaling as well as the site amplification of response spectral acceleration at a period of 1 s obtained for the Kanto basin are comparable to previous regional studies. Y1 - 2022 U6 - https://doi.org/10.1785/0120220008 SN - 0037-1106 SN - 1943-3573 VL - 112 IS - 3 SP - 1565 EP - 1582 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Türker, Elif A1 - Cotton, Fabrice A1 - Pilz, Marco A1 - Weatherill, Graeme T1 - Analysis of the 2019 Mw 5.8 Silivri earthquake ground motions BT - evidence of systematic azimuthal variations associated with directivity effects JF - Seismological research letters N2 - The main Marmara fault (MMF) extends for 150 km through the Sea of Marmara and forms the only portion of the North Anatolian fault zone that has not ruptured in a large event (Mw >7) for the last 250 yr. Accordingly, this portion is potentially a major source contributing to the seismic hazard of the Istanbul region. On 26 September 2019, a sequence of moderate-sized events started along the MMF only 20 km south of Istanbul and were widely felt by the population. The largest three events, 26 September Mw 5.8 (10:59 UTC), 26 September 2019 Mw 4.1 (11:26 UTC), and 20 January 2020 Mw 4.7 were recorded by numerous strong-motion seismic stations and the resulting ground motions were compared to the predicted means resulting from a set of the most recent ground-motion prediction equations (GMPEs). The estimated residuals were used to investigate the spatial variation of ground motion across the Marmara region. Our results show a strong azimuthal trend in ground-motion residuals, which might indicate systematically repeating directivity effects toward the eastern Marmara region. Y1 - 2022 U6 - https://doi.org/10.1785/0220210168 SN - 0895-0695 SN - 1938-2057 VL - 93 IS - 2A SP - 693 EP - 705 PB - Seismological Society of America CY - Boulder, Colo. ER - TY - JOUR A1 - Nievas, Cecilia A1 - Pilz, Marco A1 - Prehn, Karsten A1 - Schorlemmer, Danijel A1 - Weatherill, Graeme A1 - Cotton, Fabrice T1 - Calculating earthquake damage building by building BT - the case of the city of Cologne, Germany JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - The creation of building exposure models for seismic risk assessment is frequently challenging due to the lack of availability of detailed information on building structures. Different strategies have been developed in recent years to overcome this, including the use of census data, remote sensing imagery and volunteered graphic information (VGI). This paper presents the development of a building-by-building exposure model based exclusively on openly available datasets, including both VGI and census statistics, which are defined at different levels of spatial resolution and for different moments in time. The initial model stemming purely from building-level data is enriched with statistics aggregated at the neighbourhood and city level by means of a Monte Carlo simulation that enables the generation of full realisations of damage estimates when using the exposure model in the context of an earthquake scenario calculation. Though applicable to any other region of interest where analogous datasets are available, the workflow and approach followed are explained by focusing on the case of the German city of Cologne, for which a scenario earthquake is defined and the potential damage is calculated. The resulting exposure model and damage estimates are presented, and it is shown that the latter are broadly consistent with damage data from the 1978 Albstadt earthquake, notwithstanding the differences in the scenario. Through this real-world application we demonstrate the potential of VGI and open data to be used for exposure modelling for natural risk assessment, when combined with suitable knowledge on building fragility and accounting for the inherent uncertainties. KW - Building exposure modelling KW - Seismic damage assessment KW - Scenario KW - earthquake KW - Seismic risk KW - Cologne Y1 - 2022 U6 - https://doi.org/10.1007/s10518-021-01303-w SN - 1570-761X SN - 1573-1456 VL - 20 IS - 3 SP - 1519 EP - 1565 PB - Springer CY - Dordrecht ER -