Publications OpenQuake engine installation guide Share Facebook LinkedIn Download 2018 | User manual The OpenQuake Engine software provides calculation and assessment of seismic hazard, risk and decision-making tools via the data, methods and standards that are being developed by GEM (Global Earthquake Model) and its collaborators. The seismic hazard calculations of the OpenQuake Engine are powered by the OpenQuake Hazard Library and OpenQuake Risk Library Both libraries were built by the OpenQuake team to serve as a fast, stable, and lightweight alternative to existing risk and hazard libraries. To get involved in OpenQuake, join us on IRC (irc.freenode.net) in the #openquake channel by using an IRC client or via web at http://webchat.freenode.net. You can also submit questions, comments, or support requests to our OpenQuake users mailing list: http://groups.google.com/group/openquake-users. You can find more information about the project at http://www.globalquakemodel.org/tools-products

Country model to assess potential financial losses to commercial, industrial and residential buildings due to earthquakes Products South Africa Financial Loss Model Country model to assess potential financial losses to commercial, industrial and residential buildings due to earthquakes Share Facebook LinkedIn Description The GEM Colombia model is based upon GEM’s regional model for South America first developed from 2013 to 2015 within the South America Risk Assessment (SARA) project funded by the Swiss Re Foundation and updated in 2018. The development process involved dozens of local scientists and engineers from earthquake-prone countries in South America, resulting in an open product for analyzing ground-up loss from ground shaking for residential, commercial, and industrial buildings. This model has been further improved with local information, such as local construction practices, replacement costs and level of enforcement of the seismic regulations. Further technical information can be found in the documentation. GEM extensively collaborated with its private and public partners to test and validate the model against industry standards in order to produce a new model that represents GEM’s view of risk. The model is available in Oasis LMF format. How to cite this work N.A. Available Versions The latest version (v2021) created by GEM can be requested by clicking on the "License Request", where a specific license will be provided, depending on the use case. The model is also available through Verisk's Model Exchange platform by clicking on the links in the right panel. License information Currently, the model is only available under a restricted license that has to be tailored for each specific use case. Facebook LinkedIn Share Latest Version v2021 License Custom License Available resources OASIS Model License Request text Map View Search Popup title Close Country/Region Available Resources Afghanistan Exposure Africa Exposure Alaska Exposure Country/Region Available Resources Afghanistan Vulnerability Africa Vulnerability Alaska Vulnerability Country/Region Resource Url Afghanistan Risk Profile Africa Risk Profile Alaska Risk Profile Search Found Country/Region Resource Url Afghanistan Exposure Africa Exposure Alaska Exposure Preview Preview is not available. Search Found Country/Region Resource Url Afghanistan Vulnerability Africa Vulnerability Alaska Vulnerability Preview Preview is not available. Search Found Country/Region Resource Url Afghanistan Risk Profile Africa Risk Profile Alaska Risk Profile Preview Preview is not available. Related products China Financial Loss Model Colombia Financial Loss Model Related publications For downloading or accessing detailed product information like PNG/PDF maps, datasets, license request, shapefiles and more, please switch to a desktop or laptop computer. Thank you for your understanding.

Publications Critical Issues in Earthquake Scenario Loss Modeling Share Facebook LinkedIn Download 2016 | Peer-reviewed The assessment of human or economic losses due to single events (scenario) may effectively support decision makers in the development of important risk mitigation actions. The study presented herein sheds light on several problems and limitations in the current practice of scenario loss modeling, such as: the number of simulations required to achieve convergence; epistemic and aleatory uncertainty in the ground motion prediction and vulnerability models; and consideration of the earthquake rupture geometry. These issues are investigated using the Metropolitan Area of Lisbon (Portugal), and it has been observed that distinct assumptions in the loss modeling can lead to considerably different results. The findings of this study are also pertinent for probabilistic seismic risk analyses in which a large number of stochastically generated events are employed to assess probabilistic losses.

Publications User guide Android mobile tool for field data collection Share Facebook LinkedIn Download 2014 | User manual TheGlobalEarthquakeModel(GEM)aimstoprovideasetoftoolsandmodelsforhazardandriskanalysis. ThefundamentalaimoftheGEMInventoryDataCaptureTools(IDCT)riskglobalcomponentistoprovidea set of software and accompanying user protocols toenable users to collect andmodify buildingexposure information,whichcanbeinputintotheGlobalExposureDatabaseandtheGlobalEarthquakeConsequences Database. ThisreportformstheuserguideforIDCTAndroidInventoryDataMobileTool, whichisavailablefromGoogle Play.Itdetailstheusageofthemobiletoolforsettingupdatacapture,utilisingthemapinterface,marking surveypoints,captureofbuildingattributes,exportofsurveydataandimportofofflinemapdata.

Publications Colombia Seismic Model Share Facebook LinkedIn Download 2020 | Report Colombia occupies a territory in which the forces of nature and their geological expression produce events that can be dangerous for the population. This environment is a challenge that demands the country (and us, as citizens) the best efforts to understand the dynamics of the earth, so that we can design our cities and infrastructure in the best possible way, using the available knowledge.

Publications Exploring benefit cost analysis to support earthquake risk mitigation in Central America Share Facebook LinkedIn Download 2022 | Peer-reviewed We performed benefit-cost analysis to identify optimum retrofitting interventions for the two most vulnerable building typologies in Central America, unreinforced masonry and adobe, considering the direct costs due to building damage and the indirect costs associated with the injured and fatalities. We reviewed worldwide retrofitting techniques, selected those that could be applied in the region for these building types, and derived vulnerability functions considering the impact of each retrofitting intervention in the strength, stiffness, and ductility of the structures. Probabilistic seismic risk analyses were performed considering the original configuration of each building class, as well as the retrofitted version. We calculated average annual losses to estimate the annual savings due to the different structural interventions, and benefit cost ratios were estimated based on the associated cost of each retrofitting technique. Based on the benefit-cost analyses, for a 50-year time horizon and a 4% discount rate, retrofitting these building classes could be economically viable along the western coast of Central America.

OpenQuake Engine certified user page This is to certify that Lisselyn Cordova Arias has successfully completed the requirements to become a Certified OpenQuake Engine User for Scenario Assessment demonstrating the required knowledge and skills as assessed by the Global Earthquake Model (GEM) Foundation. GEM Foundation Secretary General Helen Crowley (signed) Date of Completion: Valid until: September 11, 2026 September 11, 2029

Publications Automating building typology identification for seismic risk assessment using deep learning Share Facebook LinkedIn Download 2025 | Peer-reviewed Driven by rapid urbanization and heightened seismic risk concerns, efficient methods for developing regional seismic exposure assessments are advantageous. By leveraging deep learning and computer vision techniques, this study presents a novel approach for automating the identification of building typologies. The detailed building stock required for seismic exposure assessment has been traditionally achieved through time-consuming and costly in-person inspections. Recently, virtual inspections have emerged as a more efficient alternative, but they still require significant manual effort. This study proposes a methodology for automating the characterization of buildings, including details such as the number of stories, structural system, and construction period (pre-code or code), by implementing a convolutional neural network model that processes labeled images from Google Street View. A key innovation of this study is the integration of pre-processing techniques, including an object detector to isolate building façades and perspective correction using a keypoint model and homography transformation, enabling robust performance even with a small data set. This research advances prior methods by classifying individual stories rather than grouping them into broad taxonomic ranges, providing greater precision and applicability for seismic exposure modeling. The results show an 88% accuracy for structural system identification, a 78% accuracy for the number of stories, and a 69% accuracy for construction period determination. These characteristics are integrated into a probabilistic distribution model of building taxonomy that informs about their potential seismic vulnerability. The proposed procedures streamline the development of building stock and seismic exposure models, thus facilitating their use for seismic risk modeling at a regional scale.

Publications Tipologías constructivas en Quito, Cali and Santiago de los Caballeros Share Facebook LinkedIn Download 2021 | Report Reporte sobre tipologías constructivas en las ciudades del Proyecto TREQ.

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