Publications Extensible Data Schemas for Multiple Hazards, Exposure and Vulnerability Data Share Facebook LinkedIn Download 2019 | Report The data required for assessing disaster risk can generally be divided into three categories: hazard, exposure and vulnerability. To date there is no widely accepted approach for storing and sharing such risk-related data using a common data structure. As a result, using risk-related data often requires a significant amount of upfront work to collect, extract and transform data before it can be used for purposes such as a risk assessment. In addition, the lack of a consistent data structure hinders the development of tools that can be used for more than one set of data. In practice, this situation introduces a significant amount of friction in efforts to quantify and manage disaster risk. Here we report on an effort by three consortia to develop extensible, internally consistent schemas for hazard, exposure and vulnerability data. The consortia coordinated their efforts so the three schemas are compatible. For example, the intensity measure types used to define the hazard datasets are compatible with the intensity measures used by the vulnerability models. Similarly, the asset attributes used in the exposure data taxonomy are compatible with the asset attributes used for the vulnerability data. Hazard data can be provided as either event footprints or stochastic catalogs. Exposure classes include buildings, infrastructure, agriculture, livestock, forestry and socio-economic data. The vulnerability component includes fragility and vulnerability functions and indicators for physical and social vulnerability. The schemas also provide the ability to define uncertainties associated with the hazard data and allows the scoring of vulnerability data for relevance and quality. As a proof of concept, the schemas were populated with data covering the three components for Tanzania and with additional exposure data for several other countries.

News New Frontiers in Seismic Risk Modelling: Using AI and Google Street View for Detailed Exposure Models By: Jul 8, 2024 Jun 13, 2024 Share Facebook LinkedIn In a recent webinar focused on the May 2024 issue of Earthquake Spectra, Vitor Silva presented a promising solution to a longstanding frustration in seismic risk assessment: acquiring detailed building data. Traditionally, modellers have relied on limited datasets like housing census information, which lack the granularity needed for accurate risk assessments. Vitor highlighted the potential of combining artificial intelligence with Google Street View imagery to automatically generate detailed exposure models for entire cities. However, a major hurdle lies in the scarcity of open-source, labelled building image datasets for training these machine learning algorithms. To address this gap, Vitor presented his research on creating a database of geo-located building photos specifically designed for this purpose. This database allows researchers to train algorithms that can automatically assign vulnerability classes to buildings based on their visual characteristics. During the webinar, Vitor walked through the creation process of the database of building photos and explained how it was used to calibrate machine learning models for classifying the vulnerability of 3,000 buildings in Lisbon, Portugal. This research holds significant promise for enhancing the accuracy and level of detail in exposure models, leading to more robust seismic risk assessments. To learn more about Vitor’s paper “A building imagery database for the calibration of machine learning algorithms” : https://doi.org/10.1177/87552930241229103 . No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News Spanish language is now supported in IDCT Android data collection tool courtesy of Corporación OSSO Colombia By: Jun 27, 2018 Share Facebook LinkedIn Corporación OSSO Colombia released the IDCT Android data collection tool with Spanish language support on 30th March. Through the generous contribution and support of Corporación OSSO, it is now possible to collect building inventory data by selecting Spanish terms from the form interface and to view help pages in Spanish. (Read Spanish version below) The app can be installed on Android phones and tablets via Google Play (link). The source code is available from GitHub. Users test the Android app in 2014 The GEM Android data collection tool was first released in 2014 as part of GEM’s objective to develop a suite of open-source software and protocols to support participatory population of a global exposure database (GED) of structural information. This tool allows users of Android tablets and smartphones to collect information about individual buildings for use in seismic or multi-hazard risk assessment. The tool was tested in Greece, Italy, UK, USA and Kyrgyzstan.The creation of this tool required the collaboration of many professionals and involved 11 international organizations. ------------------------------------- Espanol ahora puede elegirse como lengua en los ajustes de la herramienta IDCT Android data collection, gracias a Corporación OSSO Colombia El 30 de Marzo, Corporación OSSO Colombia lanzó la herramienta IDCT Android data collection con posibilidad de elegir el idioma Español en los ajustes. Gracias a la grande contribución y al apoyo de la Corporación OSSO, ahora es posible coleccionar información sobre edificios en el inventario seleccionando términos en Español del interfaz, así como ver paginas de ayuda. La aplicación se puede instalar en teléfono Android y tabletas mediante Google Play (link). El código fuente se encuentra en Github. La herramienta GEM Android data collection se lanzó en 2014 en el marco del objetivo de GEM de desarrollar un conjunto de software de código abierto y protocolos para apoyar la población participativa de una base de datos de exposición global (GED) de datos estructurales. Esta herramienta les permite a los usuarios de tabletas y smartphones Android coleccionar información sobre cada edificio para ser utilizadas en la evaluación del riesgo sísmico o del multi-riesgo . La herramienta fue puesta a prueba en Grecia, Italia, Reino Unido, EEUU y Kirguistán. La creación de esta herramienta vio la colaboración de muchos profesionales y involucró a 11 organizaciones internacionales. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

Publications Modeling distributed seismicity for probabilistic seismic_hazard analysis: Implementation and insights with the OpenQuake engine Share Facebook LinkedIn Download 2014 | Peer-reviewed In any probabilistic seismic‐hazard model, the earthquake activity that cannot be associated with well‐characterized fault structures is taken into account as seismicity distributed over a geographical region. Ground‐motion prediction equations (GMPEs) are generally based on predictor variables describing the spatial extension of a rupture. The approach taken to model rupture finiteness can therefore bias the estimation of seismic hazard. We study the effect of rupture finiteness in modeling distributed seismicity using the OpenQuake (OQ) engine, the open‐source software for seismic hazard and risk assessment promoted by the Global Earthquake Model initiative. For a simple test case we show how the inclusion of rupture finiteness, with respect to the point‐rupture approximation, leads to a significant increase in the probabilities of exceedance for a given level of motion. We then compare the OQ engine with the calculation software developed by the U.S. Geological Survey‐National Seismic Hazard Mapping Project. By considering a gridded seismicity model for California, we show how different approaches for modeling finite ruptures affect seismic‐hazard estimates. We show how sensitivity to rupture finiteness depends not only on the spatial distribution of activity rates but also on the GMPE model. Considering two sites in Los Angeles and San Francisco, we show that for a return period of 475 years, the percent difference in the associated ground‐motion levels when using point and finite ruptures ranges from 19% to 46%; for a return period of 2475 years the difference ranges from 29% to 58%.

Publications Global Geodetic strain rate model Share Facebook LinkedIn Download 2014 | Report ThisisthefinalreportproducedinthecontextoftheGEMStrainRateProject,oneoftheglobalcomponents of the GEM Foundation. The project was charged to analyse and synthesize all available geodetic data in order tocreateaglobaldatasetofgeodeticvelocities thatcanbeused tomodelplatemotionsandstrain ratesinplateboundaryzones.To thisend,weestimated6533velocities fromposition time-series thatwe derived fromtheanalysisofRINEXdatathatwaseither freelyavailableormadeavailabletousspecifically forthisproject.Allbut 15ofthesevelocitieswereusedinthemodelling.Inaseparateanalysis,wealsoreanalysed all RINEX data in China and effectively added 1143 velocities to the data set. Finally, we added 13,318velocitiesfrom216studiesinthepublishedliterature(orfrompersonalcommunications)toachievea grandtotalof20,979velocitiesat17,491uniquelocationsusedinthemodelling.Ofallvelocities, 16,325are inplateboundaryzones(asdefinedbyus)andtheremaining4654velocitiesareforpointson,predefined, rigidtectonicplatesorblocks.Wecreatedaglobalmeshthathas144,827deformingcellsof0.2°(latitudinal) by 0.25° (longitudinal) dimension covering the plate boundary zones,with the remaining cells covering 50 rigidplatesandblocks.For36oftheseplates,weestimatedtherigid-bodyrotation fromourdataset,and the rotations of the remaining plates are taken from the literature. The rigid-body rotations are used as boundaryconditionsinthestrainratecalculations.ThestrainratefieldismodelledusingtheHainesandHolt method,whichusessplinestoobtainaninterpolatedvelocitygradienttensorfield,fromwhichstrainrates, vorticityrates,andexpectedvelocitiesarederived.Wealsoestimatedmodeluncertainties,specificforthis high-resolution mesh, which indicates that there still are many areas with large strain rate uncertainties where the data spacing is often much larger than the cell dimensions. Nevertheless, the model and data input are a tremendous improvement to the previous global strain rate model from 2004. All results are transferred to GEM and are also archived and displayed by a dedicated server hosted by UNAVCO (gsrm2.unavco.org), one of the project's partners. In addition, we created a kmz-layer of contour's of the secondinvariantofthemodelstrainrates,andwecreatedanonlinetoolthatwouldallowausertoupload hisownvelocitiesandplotthemwiththevelocitiesintheGEMdatasetin53differentreferenceframes.

News OpenQuake in the Shaky Isles By: Jul 2, 2018 Share Facebook LinkedIn New Zealand, often referred to colloquially as the “shaky isles” due to its position on the boundary between the Pacific and Australian plates, has been involved in a long-term partnership with GEM through GNS Science representatives on the Governing and Science Boards, leading the development of the GEM Faulted Earth Database and collaborating on regional initiatives. It will now be the first country to run an end-to-end calculation using the OpenQuake-Engine. The researcher’s team led by Nick Horspool and Andrew King converted the existing national hazard model (dated back 2012) in a format compatible with the Engine, while adding new specific NZ Ground Motion Prediction Equations and Fault Scaling Laws to the OpenQuake repository. Initial results of the hazard comparison are promising (Figure 1) and if all goes well the team will soon be keen to share the model on the OpenQuake platform.In addition to at the hazard level, GNS Science has also converted all of its vulnerability and exposure models from the RiskScape project into OpenQuake formats, in order to enable risk calculations using the Engine. This will provide a continuous and uniform pathway from seismic hazard to risk modeling for New Zealand (Figure 2). As part of the risk work, GNS has also shared the consequence data on physical damage and losses to the building stock of Christchurch in the GEM Consequences Database, for use by the whole community. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

Publications Modelo Probabilístico de Amenaza Sísmica para la República Dominicana Share Facebook LinkedIn Download 2022 | Report Descripción del modelo probabilístico de amenaza sísmica desarrollado para La República Dominicana

News Canada’s new earthquake science: Learning from loss models By: Mar 26, 2021 Share Facebook LinkedIn The Institute for Catastrophic Loss Reduction (ICLR) recently organized a webinar and invited leaders from the loss modeling community to present and discuss their views about seismic risk in Canada. Participants from RMS, AIR, CoreLogic and NRCan presented their estimates of the expected consequences of a catastrophic earthquake and participated in a discussion about the differences in the findings between the models. More than 200 participants with an interest in Canadian catastrophe risk participated from across sectors including insurance and risk finance, government, and academia. This workshop really brought together insurers, government policy makers and researchers to look at what the latest earthquake risk science is telling us about Canada, and to determine how to manage it from public and private perspectives." Paul Kovacs, ICLR Director. The webinar tackled three current issues – preparedness for extreme earthquake hazards, new science anticipating increased shaking, and analysis of the risk of fire following a major earthquake. For the first time, Canadian earthquake modelers across public and private sectors came together to discuss how models support action to manage and address these issues. In a panel led by ICLR Director Paul Kovacs, Lori Medders (Professor of Insurance, Appalachian State University in Boone, North Carolina, USA) and GEM Secretary General John Schneider closed the meeting with a conversation about the importance of loss models in serving the public interest and how important transparent and open models and methodologies are to gaining trust and managing risk. “For GEM, I think the open approach has been fundamental in developing partnerships, and in developing the capacity to do hazard and risk assessments across sectors and stakeholder groups.” John said. He added that “Ultimately it has greatly accelerated the transition from research to application and has broadened the scope of applications. We're fast tracking research directly into models and their use. As we've seen in the presentations today on the development of Canadian earthquake risk models, information is being taken up and digested very quickly if it's openly available.” About ICLR The Institute for Catastrophic Loss Reduction (ICLR), is a world-class center for multi-disciplinary disaster prevention research and communication. ICLR was established by Canada’s property and casualty (p&c) insurance industry as an independent, not-for-profit research institute affiliated with Western University. ICLR has been leading a conversation about the new science about earthquakes in Canada. The 2020 Canadian seismic hazard model predicts much stronger shaking than the 2015 model and ICLR research shows that the risk of extensive fire damage following an earthquake also increases. Models help insurers and other decision makers understand the evolving knowledge about earthquakes. For more information about ICLR, visit https://www.iclr.org . No images found. GALLERY 1/0 Gallery VIDEO RELATED CONTENTS

News Seismic Moment: From Rupture to Recovery By: Sep 15, 2022 Share Facebook LinkedIn Close to 200 online and in-person participants from 70+ countries joined the International Symposium on Hazard, Risk and Recovery Modelling: Seismic Moment – From Rupture to Recovery. The event, held at the Department of Civil Engineering of the University of Aveiro, Portugal on July 14th discussed cutting-edge science and ground-breaking technology in earthquake engineering. Vitor Silva - GEM Seismic Risk Coordinator and Xavier Romao - FEUP/CONSTRUCT moderated the discussions on new advancements in seismic hazard modelling in Europe, latest developments in vulnerability and risk assessment and factors influencing long-term impact and recovery after an earthquake. Vice Rector of the University of Aveiro Artur Silva, and Director of RISCO Romeu Vicente opened the symposium. It was followed by presentations on the new European seismic hazard model (Laurentiu Danciu, ETHZ); and the new European seismic risk model (Helen Crowley, EUCENTRE). The second part of the morning session focused on earthquake early warning in Europe (Carmine Galasso and Gemma Cremen, UCL); and the NASA Insight Mission - Seismicity of Mars ( John Clinton, ETHZ). The afternoon sessions explored more on the experiences of the presenters in vulnerability and risk assessments such as addressing the issues and challenges in clustered seismicity risk assessment (Paolo Bazzurro, IUSS Pavia); the impact of and recovery from the Croatian Earthquakes of 2020 (Mario Uros, University of Zagreb); and research and implementation of seismic risk mitigation in schools through low-cost sliding foundations (Anastasios Sextos, University of Bristol). Speakers shared more on the ground experiences in post-earthquake community recovery processes and modelling (Laurie Johnson, Laurie Johnson Consulting USA); and changes in the upcoming update of the Eurocode 8 (Antonio Correia, National Laboratory of Civil Engineering, Portugal). The event was capped with a discussion on what’s missing in earthquake risk assessment, which featured a presentation on future directions in earthquake risk assessment: high-fidelity optimization, a numerical modelling approach for predicting the seismic wave of complex earthquake scenarios from the fault to the epicentre site. The topic was presented by a surprise speaker - Professor Jack Baker of Stanford University. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News Make Exposure Great Again: Understanding Risk Forum 2018 By: Jul 12, 2018 Share Facebook LinkedIn The fifth global Understanding Risk forum took place from May 14-18, 2018 in Mexico City, Mexico at the Palacio de Minería. The annual event organized by The World Bank/GFDRR with support from Coca-Cola FEMSA, World Vision México, and Compromiso Social Citibanamex kicked off with two days of dedicated side events, followed by three days (May 16 – 18) of main conference plenaries and technical sessions. The 2018 Understanding Risk Forum (UR2018) broadly focused on understanding the risk of disasters in order to better prepare and create more resilient societies. This year, the UR community convened to specifically examine the critical role of risk communication and disruptive technologies in disaster risk management. More than 1000 experts and practitioners from more than 100 countries and 550+ organizations participated in more than 20 technical sessions and close to 60 side events. GEM’s Vitor Silva, Risk Team coordinator presented in the side event ‘Discussions on DRR Tools and the Exchange of Hazard, Exposure and Vulnerability Data’. His presentation, MEGA or Make Exposure Great Again focused on exposure data developed by GEM as part of the DFID/GFDRR Challenge Fund 2 (creating a data schema and global exposure database to fill the gap between data providers and users of exposure information for disaster risk assessment and reduction). Vitor also highlighted the importance of open exposure data in the pursuit of better global access to risk information. “Historically exposure data has been collected and developed at large scale by the private sector. GEM in partnership with GFDRR is changing this by breaking the walls between data providers and decision-makers, advocating openness and collaboration, and promoting the sharing of information,” Vitor remarked during the discussion. Vitor also discussed GEM’s worldwide work on earthquake hazard, risk and social vulnerability assessments, and key features of GEM’s online data-sharing tool: the OpenQuake Platform. The forum also seeks to redefine the goal of risk communication from merely informing to inspiring action: a goal that GEM will actively pursue with the upcoming release of the first Global Earthquake Hazard and Risk Model (GRM2018) on 5th December 2018 in Pavia, Italy. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS