News GEM and 100RC partnership to boost earthquake resilience By: Mar 1, 2019 Share Facebook LinkedIn Cities at risk to earthquakes are expected to directly benefit from the partnership between GEM and 100 Resilient Cities – Pioneered by The Rockefeller Foundation (100RC), which is dedicated to helping cities around the world become more resilient to the physical, social and economic shocks and stresses of the 21st century. (source: http://www.100resilientcities.org) The agreement signed in August provides an opportunity for 100RC member cities to understand and address their earthquake risk by working with GEM to incorporate earthquake risk reduction in their resilience strategies and capturing lessons learned to inform other cities. The Global Earthquake Model (GEM) will partner with motivated cities to build their capacity for long-term risk mitigation planning using GEM’s open source OpenQuake software and GEM’s other tools and services. “Our partnership with the 100RC is a great opportunity to share GEM’s open tools, data and technical expertise at the city level. Working together with 100RC is an important step toward achieving GEM’s vision of a world that is resilient to earthquakes.” John Schneider, GEM Secretary General. Cities will receive an ‘Earthquake Risk Thumbnail’, a report providing OpenQuake maps of the city’s or region’s seismic risk comprised of the hazard, and the physical, social and economic risk to the exposed assets and population. 'Thumbnail’ report will propose options for deeper engagement which may include collaboration on data collection, raining local city staff or partners to use GEM’s products and tools, and stakeholder engagement workshops including the Resilience Performance Scorecard (RPS) exercise. Rebecca Laberenne, Associate Director on the Solution Development and Innovation Team at 100RC, underscores the value of partnering with GEM saying, "We are delighted to have GEM Foundation as a 100RC Platform Partner to provide much needed information and technical advice to cities whose buildings and infrastructure are at risk to earthquakes. GEM's approach to collaboration and technical assistance will be very welcomed by cities to gain an understanding of their risks, as well as to assist in identifying appropriate and cost-effective mitigation and risk reduction measures as part of their resilience strategies." No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News Estimating fault slip rates in the Cascadia region of North America using joint geologic-geodetic block modeling By: Jun 3, 2021 Share Facebook LinkedIn Richard Styron, GEM hazard team, was recently invited to present at the Seismological Society of America (SSA) Conference held in April on the ongoing collaborative research between GEM, Natural Resources Canada, and other scientists to study earthquake faults in the northwestern US and western Canada. The authors of the conference paper were Richard Styron, Tiegan Hobbs (Natural Resources Canada), Zach Lifton (Idaho Geological Survey), Nick Harrichhausen (University of California, Santa Barbara) and Murray Journeay (Natural Resources Canada). The project uses a software program developed by Richard called Oiler , that estimates the long-term movement of faults and corresponding production of earthquakes. Oiler uses geodetic (mostly global positioning system or GPS) measurements of the movement of tectonic plates, as well as geologic data such as geologic mapping and paleoseismic studies, to solve for the slip rate (and therefore earthquake production rate) of all faults within a fault network. For this project, the researchers used existing fault data augmented with some new mapping in the US, and completely new mapping of possibly-active faulting in Canada, to build the fault network. Over the next year or two, the researchers hope to be able to incorporate all of this data into a comprehensive database of seismically active faults in order to evaluate the earthquake potential of previously-unstudied faults in western Canada and the northwestern US. Watch Richard’s SSA presentation here. [ VIDEO LINK ] About #SSA2021 Held on 19–23 April 2021, the virtual SSA Annual Meeting featured more than 750 technical presentations, including sessions co-sponsored by the Latin American and Caribbean Seismological Commission and the Seismological Society of China. For more about SSA, visit https://www.seismosoc.org/ . No images found. GALLERY 1/0 Gallery VIDEO RELATED CONTENTS

Global Earthquake Maps Global Economic Vulnerability Map VIEWER PDF PNG CONTRIBUTORS DOCUMENTATION References Briguglio, L., Cordina, G., Farrugia, N. & Vella, S. 2009. Economic Vulnerability and Resilience: Concepts and Measurements. Oxford Development Studies, 37:3, 229-247, DOI: 10.1080/13600810903089893. Cutter, S. L., J. T. Mitchell, and M. S. Scott. 2000. Revealing the Vulnerability of People and Place: A Case Study of Georgetown County, South Carolina. Annals of the Association of American Geographers 90(4): 713-737. TECHNICAL DESCRIPTION The Global Economic Vulnerability Map presents a composite index that was designed primarily to measure the potential for economic losses from earthquakes due to a country’s macroeconomic exposure. This index is also an appraisal of the ability of countries to respond to shocks to their economic systems. Relevant indicators include the density of exposed economic assets such as commercial and industrial infrastructure. Metrics used to measure the ability of a country to withstand shocks to its economic system include reliance on imports/exports, government debt, and purchasing power. The economic vulnerability category also considers the economic vitality of countries since the economic vitality of a country can be directly related to the vulnerability and resilience of its population. The latter includes measurements of single-sector economic dependence, income inequality, and employment status. Criteria for indicator selection To choose indicators contextually exclusive for use in each map, the starting point was an exhaustive review of the literature on earthquake social vulnerability and resilience. For a variable to be considered appropriate and selected, three equally important criteria were met: - variables were justified based on the literature regarding its relevance to one or more of the indices. - variables needed to be of consistent quality and freely available from sources such as the United Nations and the World Bank; and - variables must be scalable or available at various levels of geography to promote sub-country level analyses. This procedure resulted in a ‘wish list’ of approximately 300 variables of which 78 were available and fit for use based on the three criteria. Process for indicator selection For variables to be allocated to an index, a two-tiered validation procedure was utilized. For the first tier, variables were assigned to each of the respective indices based on how each variable was cited within the literature, i.e., as being part of an index of social vulnerability, economic vulnerability, or recovery/resilience. For the second tier, machine learning and a multivariate ordinal logistic regression modelling procedure was used for external validation. Here, focus was placed on the statistical association between the socio-economic vulnerability indicators and the adverse impacts from historical earthquakes on a country-by country-basis. The Global Significant Earthquake Database provided the external validation metrics that were used as dependent variables in the statistical analysis. To include both severe and moderate earthquakes within the dependent variables, adverse impact data was collected from damaging earthquake events that conformed to at least one of five criteria: 1) caused deaths, 2) caused moderate damage (approximately $1 million USD or more), 3) had a magnitude 7.5 or greater 4) had a Modified Mercalli Intensity (MMI) X or greater, or 5) generated a tsunami. This database was chosen because it considers low magnitude earthquakes that were damaging (e.g., MW >=2.5 & MW<=5.5) and contains socio-economic data such as the total number of fatalities, injuries, houses damaged or destroyed, and dollar loss estimates in $USD. Countries not demonstrating at least a minimal earthquake risk, i.e., seismicity <0.05 PGA (Pagani et al. 2018) and <$10,000 USD in predicted average annual losses (Silva et al. 2018) were eliminated from the analyses so as not to include countries with minimal to no earthquake risk. A total study area consists of 136 countries. The Global Earthquake Model (GEM) Foundation The Global Socio-Economic Vulnerability Maps 2020 is a product of the GEM Foundation’s collaborative work with the Department of Geography at the University of Connecticut, USA. GEM is a non-profit foundation in Pavia, Italy funded through a public-private partnership with a vision to create a world that is resilient to earthquakes. Formed in 2009 through the initiative of the Organization for Economic Co-operation and Development (OECD) Global Science Forum in 2006, GEM participants represent national research and disaster management institutions; private sector companies mainly in insurance, risk financing and engineering; and academic and international organizations. GEM’s OpenQuake Platform website (platform.openquake.org) provides access to all of the data, models, tools and software behind the maps. GEM’s open-source OpenQuake engine enables probabilistic hazard and risk calculations worldwide and at all scales, from global down to regional, national, local, and site-specific applications in a single software package. GEM supports the Sendai Framework for Disaster Risk Reduction (SFDRR) goals by contributing openly accessible products for hazard and risk assessment and capacity development through risk reduction projects. GEM also serves as a baseline or exemplar for the development of a broader multi-hazard framework for risk assessment in support of a holistic and comprehensive approach to disaster risk reduction. Technical details on the development and compilation of the socio-economic vulnerability maps, underlying models and the list of contributors can be found at https://www.globalquakemodel.org/svrmaps/Economic-Vulnerability-Index-Technical-Description. How to use and cite this work Please cite this work as: C Burton, M. Toquica (September 2020). Global Earthquake Model (GEM) Social Vulnerability Map (version 2020.1) DOI: 10.13117/GEM-ECONOMIC-VULNERABILITY-MAP. This work is licensed under the terms of the Creative Commons Attribution - Non Commercial-Share Alike 4.0 International License (CC BY-NC-SA). Acknowledgements This map is the result of a collaborative effort and extensively relies on the enthusiasm and commitment of various organisations to openly share and collaborate. The creation of this map would not have been possible without the support provided by several public and private organisations during GEM’s second and third working programmes, 2014-2018 and 2019-2021 respectively. None of this would have been possible without the extensive support of all GEM Secretariat staff. These key contributions are profoundly acknowledged. A complete list of the contributors can be found at: www. globalquakemodel.org/global-social-vulnerability. Legal statements This map is an informational product created by the GEM Foundation for public dissemination purposes. The information included in this map must not be used for the design of seismic socio-economic policies or to support any important decisions involving human life, capital and movable and immovable properties. The values of social vulnerability and risk values used in this map do not constitute an alternative nor do they replace any national government policy or actions defined in national codes or earthquake risk estimates derived nationally. Readers seeking this information should contact the national authorities tasked with socio economic and risk assessment. The socio-economic vulnerability maps are based on the results of an integration process that is solely the responsibility of the GEM Foundation. Contact GEM (Global Earthquake Model) Foundation Via Ferrata, 1 - 27100, Pavia, Italy info@globalquakemodel.org . More information available at: www. globalquakemodel.org/global-social-vulnerability MAJOR SPONSORS Verisk ARUP GEOSCIENCE AUSTRALIA CSSC NRCan EAFIT ETH ZURICH EUCENTRE FM GLOBAL GFZ GIROJ GNS SCIENCE HANNOVER RE MUNICH RE NTU ICRM NEPHILA NERC NIED NSET OYO PARTNER RE DPC SGC SWISS SER SWISS RE FOUNDATION SURAMERICANA TEM RCN USGS USAID WTW ZURICH INSURANCE

OpenQuake engine input model to perform hazard calculations for Australia Project Name Products Australia Hazard OpenQuake engine input model to perform hazard calculations for Australia Share Facebook LinkedIn Description The Global Hazard Mosaic coverage of the Australian continent uses the 2018 national model developed by Geoscience Australia, with input from the wider seismology community in Australia. More recently, GA have released a 2023 model. Both models have been implemented in the OpenQuake (OQ) engine format. How to cite this work Allen, T.I., Griffin, J.D., Clark, D.J., Cummins, P.R., Ghasemi, H., Ebrahimi, R., et al. (2023). The 2023 National Seismic Hazard Assessment for Australia: model overview. Geoscience Australia Record 2023/53. Canberra. https://dx.doi.org/10.26186/148969 Available Versions Two open versions (v2023.0.0 and v2018) are available for direct download under a CC BY 4.0 license. Users interested in any of the versions can click one of the "Open Version Download" buttons on the right panel to access the information. License information Both open versions are available under a Creative Commons CC BY 4.0 license, which requires: *Attribution (you must give appropriate credit, provide a link to the license, and indicate if changes were made) Any deviation from these terms incur in license infringement. Share License CC BY 4.0 Available resources Open Version 2018 Download Documentation version 2018 Open Version 2023 Download Documentation version 2023 License Request Facebook LinkedIn text Map View Search Popup title Close Country/Region Available Resources Afghanistan Exposure Africa Exposure Alaska Exposure Albania Exposure Algeria Exposure American Samoa Exposure Andorra Exposure Angola Exposure Anguilla Exposure Antigua and Barbuda Exposure Arabia Exposure Argentina Exposure Armenia Exposure Aruba Exposure Australia Exposure Austria Exposure Azerbaijan Exposure Bahamas Exposure Bahrain Exposure Bangladesh Exposure Barbados Exposure Belarus Exposure Belgium Exposure Belize Exposure Benin Exposure Bhutan Exposure Bolivia Exposure Bosnia and Herzegovina Exposure Botswana Exposure Brazil Exposure British Virgin Islands Exposure Brunei Exposure Bulgaria Exposure Burkina Faso Exposure Burundi Exposure Cambodia Exposure Cameroon Exposure Canada Exposure Cape Verde Exposure Caribbean Central America Exposure Cayman Islands Exposure Central African Republic Exposure Central Asia Exposure Chad Exposure Chile Exposure China Exposure Colombia Exposure Comoros Exposure Congo Exposure Conterminous US Exposure Cook Islands Exposure Costa Rica Exposure Croatia Exposure Cuba Exposure Cyprus Exposure Czechia Exposure Democratic Republic of the Congo Exposure Denmark Exposure Djibouti Exposure Dominica Exposure Dominican Republic Exposure East Asia Exposure Ecuador Exposure Egypt Exposure El Salvador Exposure Equatorial Guinea Exposure Eritrea Exposure Estonia Exposure Eswatini Exposure Ethiopia Exposure Europe Exposure Fiji Exposure Finland Exposure France Exposure French Guiana Exposure Gabon Exposure Gambia Exposure Georgia Exposure Germany Exposure Ghana Exposure Gibraltar Exposure Greece Exposure Grenada Exposure Guadeloupe Exposure Guam Exposure Guatemala Exposure Guinea Exposure Guinea Bissau Exposure Guyana Exposure Haiti Exposure Hawaii Exposure Honduras Exposure Hong Kong Exposure Hungary Exposure Iceland Exposure India Exposure Indonesia Exposure Iran Exposure Iraq Exposure Ireland Exposure Isle of Man Exposure Israel Exposure Italy Exposure Ivory Coast Exposure Jamaica Exposure Japan Exposure Jordan Exposure Kazakhstan Exposure Kenya Exposure Kiribati Exposure Kosovo Exposure Kuwait Exposure Kyrgyzstan Exposure Laos Exposure Latvia Exposure Lebanon Exposure Lesotho Exposure Liberia Exposure Libya Exposure Liechtenstein Exposure Lithuania Exposure Luxembourg Exposure Macao Exposure Madagascar Exposure Malawi Exposure Malaysia Exposure Mali Exposure Malta Exposure Marshall Islands Exposure Martinique Exposure Mauritania Exposure Mauritius Exposure Mexico Exposure Micronesia Exposure Middle East Exposure Moldova Exposure Monaco Exposure Mongolia Exposure Montenegro Exposure Montserrat Exposure Morocco Exposure Mozambique Exposure Myanmar Exposure Namibia Exposure Nauru Exposure Nepal Exposure Netherlands Exposure New Caledonia Exposure New Zealand Exposure Nicaragua Exposure Niger Exposure Nigeria Exposure Niue Exposure North Africa Exposure North America Exposure North Asia Exposure North Korea Exposure North Macedonia Exposure North and South Korea Exposure Northeast Asia Exposure Northern Mariana Islands Exposure Northwest Asia Exposure Norway Exposure Oceania Exposure Oman Exposure Pacific Islands Exposure Pakistan Exposure Palau Exposure Palestine Exposure Panama Exposure Papua New Guinea Exposure Paraguay Exposure Peru Exposure Philippines Exposure Poland Exposure Portugal Exposure Puerto Rico Exposure Qatar Exposure Romania Exposure Russia Exposure Rwanda Exposure Saint Kitts and Nevis Exposure Saint Lucia Exposure Saint Vincent and the Grenadines Exposure Samoa Exposure Sao Tome and Principe Exposure Saudi Arabia Exposure Senegal Exposure Serbia Exposure Seychelles Exposure Sierra Leone Exposure Singapore Exposure Slovakia Exposure Slovenia Exposure Solomon Islands Exposure Somalia Exposure South Africa Exposure South America Exposure South Asia Exposure South Korea Exposure Country/Region Available Resources Afghanistan Vulnerability Africa Vulnerability Alaska Vulnerability Albania Vulnerability Algeria Vulnerability American Samoa Vulnerability Andorra Vulnerability Angola Vulnerability Anguilla Vulnerability Antigua and Barbuda Vulnerability Arabia Vulnerability Argentina Vulnerability Armenia Vulnerability Aruba Vulnerability Australia Vulnerability Austria Vulnerability Azerbaijan Vulnerability Bahamas Vulnerability Bahrain Vulnerability Bangladesh Vulnerability Barbados Vulnerability Belarus Vulnerability Belgium Vulnerability Belize Vulnerability Benin Vulnerability Bhutan Vulnerability Bolivia Vulnerability Bosnia and Herzegovina Vulnerability Botswana Vulnerability Brazil Vulnerability British Virgin Islands Vulnerability Brunei Vulnerability Bulgaria Vulnerability Burkina Faso Vulnerability Burundi Vulnerability Cambodia Vulnerability Cameroon Vulnerability Canada Vulnerability Cape Verde Vulnerability Caribbean Central America Vulnerability Cayman Islands Vulnerability Central African Republic Vulnerability Central Asia Vulnerability Chad Vulnerability Chile Vulnerability China Vulnerability Colombia Vulnerability Comoros Vulnerability Congo Vulnerability Conterminous US Vulnerability Cook Islands Vulnerability Costa Rica Vulnerability Croatia Vulnerability Cuba Vulnerability Cyprus Vulnerability Czechia Vulnerability Democratic Republic of the Congo Vulnerability Denmark Vulnerability Djibouti Vulnerability Dominica Vulnerability Dominican Republic Vulnerability East Asia Vulnerability Ecuador Vulnerability Egypt Vulnerability El Salvador Vulnerability Equatorial Guinea Vulnerability Eritrea Vulnerability Estonia Vulnerability Eswatini Vulnerability Ethiopia Vulnerability Europe Vulnerability Fiji Vulnerability Finland Vulnerability France Vulnerability French Guiana Vulnerability Gabon Vulnerability Gambia Vulnerability Georgia Vulnerability Germany Vulnerability Ghana Vulnerability Gibraltar Vulnerability Greece Vulnerability Grenada Vulnerability Guadeloupe Vulnerability Guam Vulnerability Guatemala Vulnerability Guinea Vulnerability Guinea Bissau Vulnerability Guyana Vulnerability Haiti Vulnerability Hawaii Vulnerability Honduras Vulnerability Hong Kong Vulnerability Hungary Vulnerability Iceland Vulnerability India Vulnerability Indonesia Vulnerability Iran Vulnerability Iraq Vulnerability Ireland Vulnerability Isle of Man Vulnerability Israel Vulnerability Italy Vulnerability Ivory Coast Vulnerability Jamaica Vulnerability Japan Vulnerability Jordan Vulnerability Kazakhstan Vulnerability Kenya Vulnerability Kiribati Vulnerability Kosovo Vulnerability Kuwait Vulnerability Kyrgyzstan Vulnerability Laos Vulnerability Latvia Vulnerability Lebanon Vulnerability Lesotho Vulnerability Liberia Vulnerability Libya Vulnerability Liechtenstein Vulnerability Lithuania Vulnerability Luxembourg Vulnerability Macao Vulnerability Madagascar Vulnerability Malawi Vulnerability Malaysia Vulnerability Mali Vulnerability Malta Vulnerability Marshall Islands Vulnerability Martinique Vulnerability Mauritania Vulnerability Mauritius Vulnerability Mexico Vulnerability Micronesia Vulnerability Middle East Vulnerability Moldova Vulnerability Monaco Vulnerability Mongolia Vulnerability Montenegro Vulnerability Montserrat Vulnerability Morocco Vulnerability Mozambique Vulnerability Myanmar Vulnerability Namibia Vulnerability Nauru Vulnerability Nepal Vulnerability Netherlands Vulnerability New Caledonia Vulnerability New Zealand Vulnerability Nicaragua Vulnerability Niger Vulnerability Nigeria Vulnerability Niue Vulnerability North Africa Vulnerability North America Vulnerability North Asia Vulnerability North Korea Vulnerability North Macedonia Vulnerability North and South Korea Vulnerability Northeast Asia Vulnerability Northern Mariana Islands Vulnerability Northwest Asia Vulnerability Norway Vulnerability Oceania Vulnerability Oman Vulnerability Pacific Islands Vulnerability Pakistan Vulnerability Palau Vulnerability Palestine Vulnerability Panama Vulnerability Papua New Guinea Vulnerability Paraguay Vulnerability Peru Vulnerability Philippines Vulnerability Poland Vulnerability Portugal Vulnerability Puerto Rico Vulnerability Qatar Vulnerability Romania Vulnerability Russia Vulnerability Rwanda Vulnerability Saint Kitts and Nevis Vulnerability Saint Lucia Vulnerability Saint Vincent and the Grenadines Vulnerability Samoa Vulnerability Sao Tome and Principe Vulnerability Saudi Arabia Vulnerability Senegal Vulnerability Serbia Vulnerability Seychelles Vulnerability Sierra Leone Vulnerability Singapore Vulnerability Slovakia Vulnerability Slovenia Vulnerability Solomon Islands Vulnerability Somalia Vulnerability South Africa Vulnerability South America Vulnerability South Asia Vulnerability South Korea Vulnerability Country/Region Resource Url Afghanistan Risk Profile Africa Risk Profile Alaska Risk Profile Albania Risk Profile Algeria Risk Profile American Samoa Risk Profile Andorra Risk Profile Angola Risk Profile Anguilla Risk Profile Antigua and Barbuda Risk Profile Arabia Risk Profile Argentina Risk Profile Armenia Risk Profile Aruba Risk Profile Australia Risk Profile Austria Risk Profile Azerbaijan Risk Profile Bahamas Risk Profile Bahrain Risk Profile Bangladesh Risk Profile Barbados Risk Profile Belarus Risk Profile Belgium Risk Profile Belize Risk Profile Benin Risk Profile Bhutan Risk Profile Bolivia Risk Profile Bosnia and Herzegovina Risk Profile Botswana Risk Profile Brazil Risk Profile British Virgin Islands Risk Profile Brunei Risk Profile Bulgaria Risk Profile Burkina Faso Risk Profile Burundi Risk Profile Cambodia Risk Profile Cameroon Risk Profile Canada Risk Profile Cape Verde Risk Profile Caribbean Central America Risk Profile Cayman Islands Risk Profile Central African Republic Risk Profile Central Asia Risk Profile Chad Risk Profile Chile Risk Profile China Risk Profile Colombia Risk Profile Comoros Risk Profile Congo Risk Profile Conterminous US Risk Profile Cook Islands Risk Profile Costa Rica Risk Profile Croatia Risk Profile Cuba Risk Profile Cyprus Risk Profile Czechia Risk Profile Democratic Republic of the Congo Risk Profile Denmark Risk Profile Djibouti Risk Profile Dominica Risk Profile Dominican Republic Risk Profile East Asia Risk Profile Ecuador Risk Profile Egypt Risk Profile El Salvador Risk Profile Equatorial Guinea Risk Profile Eritrea Risk Profile Estonia Risk Profile Eswatini Risk Profile Ethiopia Risk Profile Europe Risk Profile Fiji Risk Profile Finland Risk Profile France Risk Profile French Guiana Risk Profile Gabon Risk Profile Gambia Risk Profile Georgia Risk Profile Germany Risk Profile Ghana Risk Profile Gibraltar Risk Profile Greece Risk Profile Grenada Risk Profile Guadeloupe Risk Profile Guam Risk Profile Guatemala Risk Profile Guinea Risk Profile Guinea Bissau Risk Profile Guyana Risk Profile Haiti Risk Profile Hawaii Risk Profile Honduras Risk Profile Hong Kong Risk Profile Hungary Risk Profile Iceland Risk Profile India Risk Profile Indonesia Risk Profile Iran Risk Profile Iraq Risk Profile Ireland Risk Profile Isle of Man Risk Profile Israel Risk Profile Italy Risk Profile Ivory Coast Risk Profile Jamaica Risk Profile Japan Risk Profile Jordan Risk Profile Kazakhstan Risk Profile Kenya Risk Profile Kiribati Risk Profile Kosovo Risk Profile Kuwait Risk Profile Kyrgyzstan Risk Profile Laos Risk Profile Latvia Risk Profile Lebanon Risk Profile Lesotho Risk Profile Liberia Risk Profile Libya Risk Profile Liechtenstein Risk Profile Lithuania Risk Profile Luxembourg Risk Profile Macao Risk Profile Madagascar Risk Profile Malawi Risk Profile Malaysia Risk Profile Mali Risk Profile Malta Risk Profile Marshall Islands Risk Profile Martinique Risk Profile Mauritania Risk Profile Mauritius Risk Profile Mexico Risk Profile Micronesia Risk Profile Middle East Risk Profile Moldova Risk Profile Monaco Risk Profile Mongolia Risk Profile Montenegro Risk Profile Montserrat Risk Profile Morocco Risk Profile Mozambique Risk Profile Myanmar Risk Profile Namibia Risk Profile Nauru Risk Profile Nepal Risk Profile Netherlands Risk Profile New Caledonia Risk Profile New Zealand Risk Profile Nicaragua Risk Profile Niger Risk Profile Nigeria Risk Profile Niue Risk Profile North Africa Risk Profile North America Risk Profile North Asia Risk Profile North Korea Risk Profile North Macedonia Risk Profile North and South Korea Risk Profile Northeast Asia Risk Profile Northern Mariana Islands Risk Profile Northwest Asia Risk Profile Norway Risk Profile Oceania Risk Profile Oman Risk Profile Pacific Islands Risk Profile Pakistan Risk Profile Palau Risk Profile Palestine Risk Profile Panama Risk Profile Papua New Guinea Risk Profile Paraguay Risk Profile Peru Risk Profile Philippines Risk Profile Poland Risk Profile Portugal Risk Profile Puerto Rico Risk Profile Qatar Risk Profile Romania Risk Profile Russia Risk Profile Rwanda Risk Profile Saint Kitts and Nevis Risk Profile Saint Lucia Risk Profile Saint Vincent and the Grenadines Risk Profile Samoa Risk Profile Sao Tome and Principe Risk Profile Saudi Arabia Risk Profile Senegal Risk Profile Serbia Risk Profile Seychelles Risk Profile Sierra Leone Risk Profile Singapore Risk Profile Slovakia Risk Profile Slovenia Risk Profile Solomon Islands Risk Profile Somalia Risk Profile South Africa Risk Profile South America Risk Profile South Asia Risk Profile South Korea Risk Profile Search Found Country/Region Resource Url Afghanistan Exposure Africa Exposure Alaska Exposure Albania Exposure Algeria Exposure American Samoa Exposure Andorra Exposure Angola Exposure Anguilla Exposure Antigua and Barbuda Exposure Arabia Exposure Argentina Exposure Armenia Exposure Aruba Exposure Australia Exposure Austria Exposure Azerbaijan Exposure Bahamas Exposure Bahrain Exposure Bangladesh Exposure Barbados Exposure Belarus Exposure Belgium Exposure Belize Exposure Benin Exposure Bhutan Exposure Bolivia Exposure Bosnia and Herzegovina Exposure Botswana Exposure Brazil Exposure British Virgin Islands Exposure Brunei Exposure Bulgaria Exposure Burkina Faso Exposure Burundi Exposure Cambodia Exposure Cameroon Exposure Canada Exposure Cape Verde Exposure Caribbean Central America Exposure Cayman Islands Exposure Central African Republic Exposure Central Asia Exposure Chad Exposure Chile Exposure China Exposure Colombia Exposure Comoros Exposure Congo Exposure Conterminous US Exposure Cook Islands Exposure Costa Rica Exposure Croatia Exposure Cuba Exposure Cyprus Exposure Czechia Exposure Democratic Republic of the Congo Exposure Denmark Exposure Djibouti Exposure Dominica Exposure Dominican Republic Exposure East Asia Exposure Ecuador Exposure Egypt Exposure El Salvador Exposure Equatorial Guinea Exposure Eritrea Exposure Estonia Exposure Eswatini Exposure Ethiopia Exposure Europe Exposure Fiji Exposure Finland Exposure France Exposure French Guiana Exposure Gabon Exposure Gambia Exposure Georgia Exposure Germany Exposure Ghana Exposure Gibraltar Exposure Greece Exposure Grenada Exposure Guadeloupe Exposure Guam Exposure Guatemala Exposure Guinea Exposure Guinea Bissau Exposure Guyana Exposure Haiti Exposure Hawaii Exposure Honduras Exposure Hong Kong Exposure Hungary Exposure Iceland Exposure India Exposure Indonesia Exposure Iran Exposure Iraq Exposure Ireland Exposure Isle of Man Exposure Israel Exposure Italy Exposure Ivory Coast Exposure Jamaica Exposure Japan Exposure Jordan Exposure Kazakhstan Exposure Kenya Exposure Kiribati Exposure Kosovo Exposure Kuwait Exposure Kyrgyzstan Exposure Laos Exposure Latvia Exposure Lebanon Exposure Lesotho Exposure Liberia Exposure Libya Exposure Liechtenstein Exposure Lithuania Exposure Luxembourg Exposure Macao Exposure Madagascar Exposure Malawi Exposure Malaysia Exposure Mali Exposure Malta Exposure Marshall Islands Exposure Martinique Exposure Mauritania Exposure Mauritius Exposure Mexico Exposure Micronesia Exposure Middle East Exposure Moldova Exposure Monaco Exposure Mongolia Exposure Montenegro Exposure Montserrat Exposure Morocco Exposure Mozambique Exposure Myanmar Exposure Namibia Exposure Nauru Exposure Nepal Exposure Netherlands Exposure New Caledonia Exposure New Zealand Exposure Nicaragua Exposure Niger Exposure Nigeria Exposure Niue Exposure North Africa Exposure North America Exposure North Asia Exposure North Korea Exposure North Macedonia Exposure North and South Korea Exposure Northeast Asia Exposure Northern Mariana Islands Exposure Northwest Asia Exposure Norway Exposure Oceania Exposure Oman Exposure Pacific Islands Exposure Pakistan Exposure Palau Exposure Palestine Exposure Panama Exposure Papua New Guinea Exposure Paraguay Exposure Peru Exposure Philippines Exposure Poland Exposure Portugal Exposure Puerto Rico Exposure Qatar Exposure Romania Exposure Russia Exposure Rwanda Exposure Saint Kitts and Nevis Exposure Saint Lucia Exposure Saint Vincent and the Grenadines Exposure Samoa Exposure Sao Tome and Principe Exposure Saudi Arabia Exposure Senegal Exposure Serbia Exposure Seychelles Exposure Sierra Leone Exposure Singapore Exposure Slovakia Exposure Slovenia Exposure Solomon Islands Exposure Somalia Exposure South Africa Exposure South America Exposure South Asia Exposure South Korea Exposure Preview Preview is not available. Search Found Country/Region Resource Url Afghanistan Vulnerability Africa Vulnerability Alaska Vulnerability Albania Vulnerability Algeria Vulnerability American Samoa Vulnerability Andorra Vulnerability Angola Vulnerability Anguilla Vulnerability Antigua and Barbuda Vulnerability Arabia Vulnerability Argentina Vulnerability Armenia Vulnerability Aruba Vulnerability Australia Vulnerability Austria Vulnerability Azerbaijan Vulnerability Bahamas Vulnerability Bahrain Vulnerability Bangladesh Vulnerability Barbados Vulnerability Belarus Vulnerability Belgium Vulnerability Belize Vulnerability Benin Vulnerability Bhutan Vulnerability Bolivia Vulnerability Bosnia and Herzegovina Vulnerability Botswana Vulnerability Brazil Vulnerability British Virgin Islands Vulnerability Brunei Vulnerability Bulgaria Vulnerability Burkina Faso Vulnerability Burundi Vulnerability Cambodia Vulnerability Cameroon Vulnerability Canada Vulnerability Cape Verde Vulnerability Caribbean Central America Vulnerability Cayman Islands Vulnerability Central African Republic Vulnerability Central Asia Vulnerability Chad Vulnerability Chile Vulnerability China Vulnerability Colombia Vulnerability Comoros Vulnerability Congo Vulnerability Conterminous US Vulnerability Cook Islands Vulnerability Costa Rica Vulnerability Croatia Vulnerability Cuba Vulnerability Cyprus Vulnerability Czechia Vulnerability Democratic Republic of the Congo Vulnerability Denmark Vulnerability Djibouti Vulnerability Dominica Vulnerability Dominican Republic Vulnerability East Asia Vulnerability Ecuador Vulnerability Egypt Vulnerability El Salvador Vulnerability Equatorial Guinea Vulnerability Eritrea Vulnerability Estonia Vulnerability Eswatini Vulnerability Ethiopia Vulnerability Europe Vulnerability Fiji Vulnerability Finland Vulnerability France Vulnerability French Guiana Vulnerability Gabon Vulnerability Gambia Vulnerability Georgia Vulnerability Germany Vulnerability Ghana Vulnerability Gibraltar Vulnerability Greece Vulnerability Grenada Vulnerability Guadeloupe Vulnerability Guam Vulnerability Guatemala Vulnerability Guinea Vulnerability Guinea Bissau Vulnerability Guyana Vulnerability Haiti Vulnerability Hawaii Vulnerability Honduras Vulnerability Hong Kong Vulnerability Hungary Vulnerability Iceland Vulnerability India Vulnerability Indonesia Vulnerability Iran Vulnerability Iraq Vulnerability Ireland Vulnerability Isle of Man Vulnerability Israel Vulnerability Italy Vulnerability Ivory Coast Vulnerability Jamaica Vulnerability Japan Vulnerability Jordan Vulnerability Kazakhstan Vulnerability Kenya Vulnerability Kiribati Vulnerability Kosovo Vulnerability Kuwait Vulnerability Kyrgyzstan Vulnerability Laos Vulnerability Latvia Vulnerability Lebanon Vulnerability Lesotho Vulnerability Liberia Vulnerability Libya Vulnerability Liechtenstein Vulnerability Lithuania Vulnerability Luxembourg Vulnerability Macao Vulnerability Madagascar Vulnerability Malawi Vulnerability Malaysia Vulnerability Mali Vulnerability Malta Vulnerability Marshall Islands Vulnerability Martinique Vulnerability Mauritania Vulnerability Mauritius Vulnerability Mexico Vulnerability Micronesia Vulnerability Middle East Vulnerability Moldova Vulnerability Monaco Vulnerability Mongolia Vulnerability Montenegro Vulnerability Montserrat Vulnerability Morocco Vulnerability Mozambique Vulnerability Myanmar Vulnerability Namibia Vulnerability Nauru Vulnerability Nepal Vulnerability Netherlands Vulnerability New Caledonia Vulnerability New Zealand Vulnerability Nicaragua Vulnerability Niger Vulnerability Nigeria Vulnerability Niue Vulnerability North Africa Vulnerability North America Vulnerability North Asia Vulnerability North Korea Vulnerability North Macedonia Vulnerability North and South Korea Vulnerability Northeast Asia Vulnerability Northern Mariana Islands Vulnerability Northwest Asia Vulnerability Norway Vulnerability Oceania Vulnerability Oman Vulnerability Pacific Islands Vulnerability Pakistan Vulnerability Palau Vulnerability Palestine Vulnerability Panama Vulnerability Papua New Guinea Vulnerability Paraguay Vulnerability Peru Vulnerability Philippines Vulnerability Poland Vulnerability Portugal Vulnerability Puerto Rico Vulnerability Qatar Vulnerability Romania Vulnerability Russia Vulnerability Rwanda Vulnerability Saint Kitts and Nevis Vulnerability Saint Lucia Vulnerability Saint Vincent and the Grenadines Vulnerability Samoa Vulnerability Sao Tome and Principe Vulnerability Saudi Arabia Vulnerability Senegal Vulnerability Serbia Vulnerability Seychelles Vulnerability Sierra Leone Vulnerability Singapore Vulnerability Slovakia Vulnerability Slovenia Vulnerability Solomon Islands Vulnerability Somalia Vulnerability South Africa Vulnerability South America Vulnerability South Asia Vulnerability South Korea Vulnerability Preview Preview is not available. Search Found Country/Region Resource Url Afghanistan Risk Profile Africa Risk Profile Alaska Risk Profile Albania Risk Profile Algeria Risk Profile American Samoa Risk Profile Andorra Risk Profile Angola Risk Profile Anguilla Risk Profile Antigua and Barbuda Risk Profile Arabia Risk Profile Argentina Risk Profile Armenia Risk Profile Aruba Risk Profile Australia Risk Profile Austria Risk Profile Azerbaijan Risk Profile Bahamas Risk Profile Bahrain Risk Profile Bangladesh Risk Profile Barbados Risk Profile Belarus Risk Profile Belgium Risk Profile Belize Risk Profile Benin Risk Profile Bhutan Risk Profile Bolivia Risk Profile Bosnia and Herzegovina Risk Profile Botswana Risk Profile Brazil Risk Profile British Virgin Islands Risk Profile Brunei Risk Profile Bulgaria Risk Profile Burkina Faso Risk Profile Burundi Risk Profile Cambodia Risk Profile Cameroon Risk Profile Canada Risk Profile Cape Verde Risk Profile Caribbean Central America Risk Profile Cayman Islands Risk Profile Central African Republic Risk Profile Central Asia Risk Profile Chad Risk Profile Chile Risk Profile China Risk Profile Colombia Risk Profile Comoros Risk Profile Congo Risk Profile Conterminous US Risk Profile Cook Islands Risk Profile Costa Rica Risk Profile Croatia Risk Profile Cuba Risk Profile Cyprus Risk Profile Czechia Risk Profile Democratic Republic of the Congo Risk Profile Denmark Risk Profile Djibouti Risk Profile Dominica Risk Profile Dominican Republic Risk Profile East Asia Risk Profile Ecuador Risk Profile Egypt Risk Profile El Salvador Risk Profile Equatorial Guinea Risk Profile Eritrea Risk Profile Estonia Risk Profile Eswatini Risk Profile Ethiopia Risk Profile Europe Risk Profile Fiji Risk Profile Finland Risk Profile France Risk Profile French Guiana Risk Profile Gabon Risk Profile Gambia Risk Profile Georgia Risk Profile Germany Risk Profile Ghana Risk Profile Gibraltar Risk Profile Greece Risk Profile Grenada Risk Profile Guadeloupe Risk Profile Guam Risk Profile Guatemala Risk Profile Guinea Risk Profile Guinea Bissau Risk Profile Guyana Risk Profile Haiti Risk Profile Hawaii Risk Profile Honduras Risk Profile Hong Kong Risk Profile Hungary Risk Profile Iceland Risk Profile India Risk Profile Indonesia Risk Profile Iran Risk Profile Iraq Risk Profile Ireland Risk Profile Isle of Man Risk Profile Israel Risk Profile Italy Risk Profile Ivory Coast Risk Profile Jamaica Risk Profile Japan Risk Profile Jordan Risk Profile Kazakhstan Risk Profile Kenya Risk Profile Kiribati Risk Profile Kosovo Risk Profile Kuwait Risk Profile Kyrgyzstan Risk Profile Laos Risk Profile Latvia Risk Profile Lebanon Risk Profile Lesotho Risk Profile Liberia Risk Profile Libya Risk Profile Liechtenstein Risk Profile Lithuania Risk Profile Luxembourg Risk Profile Macao Risk Profile Madagascar Risk Profile Malawi Risk Profile Malaysia Risk Profile Mali Risk Profile Malta Risk Profile Marshall Islands Risk Profile Martinique Risk Profile Mauritania Risk Profile Mauritius Risk Profile Mexico Risk Profile Micronesia Risk Profile Middle East Risk Profile Moldova Risk Profile Monaco Risk Profile Mongolia Risk Profile Montenegro Risk Profile Montserrat Risk Profile Morocco Risk Profile Mozambique Risk Profile Myanmar Risk Profile Namibia Risk Profile Nauru Risk Profile Nepal Risk Profile Netherlands Risk Profile New Caledonia Risk Profile New Zealand Risk Profile Nicaragua Risk Profile Niger Risk Profile Nigeria Risk Profile Niue Risk Profile North Africa Risk Profile North America Risk Profile North Asia Risk Profile North Korea Risk Profile North Macedonia Risk Profile North and South Korea Risk Profile Northeast Asia Risk Profile Northern Mariana Islands Risk Profile Northwest Asia Risk Profile Norway Risk Profile Oceania Risk Profile Oman Risk Profile Pacific Islands Risk Profile Pakistan Risk Profile Palau Risk Profile Palestine Risk Profile Panama Risk Profile Papua New Guinea Risk Profile Paraguay Risk Profile Peru Risk Profile Philippines Risk Profile Poland Risk Profile Portugal Risk Profile Puerto Rico Risk Profile Qatar Risk Profile Romania Risk Profile Russia Risk Profile Rwanda Risk Profile Saint Kitts and Nevis Risk Profile Saint Lucia Risk Profile Saint Vincent and the Grenadines Risk Profile Samoa Risk Profile Sao Tome and Principe Risk Profile Saudi Arabia Risk Profile Senegal Risk Profile Serbia Risk Profile Seychelles Risk Profile Sierra Leone Risk Profile Singapore Risk Profile Slovakia Risk Profile Slovenia Risk Profile Solomon Islands Risk Profile Somalia Risk Profile South Africa Risk Profile South America Risk Profile South Asia Risk Profile South Korea Risk Profile Preview Preview is not available. 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Post Event List PURPOSE The purpose of this page is to provide GEM website visitors, researchers, loss modellers, and emergency and disaster risk reduction professionals with specific downloadable information related to red alert events based on USGS PAGER alerts. GEM promotes the sharing of seismic hazard and risk information with a wide range of stakeholders to enhance understanding of damaging earthquake events. This initiative aims not only to give an overview of the models, data and publications available in areas recently impacted by earthquakes, but also hopes to serve as a resource that can inform future risk reduction strategies. The information provided is intended solely for situational awareness purposes and is not aimed towards driving an official emergency response. Please contact your local authorities for further assistance related to official emergency response services and support. 29th July 2025 M8.8 Petropavlovsk-Kamchatsky Peninsula, Russia On 30 July 2025, at 11:24:52 PETT (23:24:52 UTC, 29 July), a Mw 8.8 megathrust earthquake struck off the eastern coast of the Kamchatka Peninsula in the Russian Far East, 119 km (74 mi) east-southeast of the coastal city of Petropavlovsk-Kamchatsky. Source: https://en.wikipedia.org/wiki/2025_Kamchatka_Peninsula_earthquake USGS PAGER Alert https://earthquake.usgs.gov/earthquakes/eventpage/us6000qw60/pager Related GEM Products Name Description North Asia Exposure Repository with the inventory of residential, commercial and industrial buildings in North Asia Northeast Asia Hazard OpenQuake engine input model to perform hazard calculations for Northeast Asia Active Faults Database A repository with global homogenised characteristics of active faults Global Seismic Risk Map A milestone in global earthquake risk assessment Global Vulnerability Model Sets of functions to assess the consequences of earthquakes on the built environment of the world Global Seismic Hazard Map Openly accessible global datasets and plots for peak ground acceleration with a return period of 475 years on rock No content. Related GEM Publications Development of a Fragility Model for the Residential Building Stock in South America Calibrating collapse and fatality rates for the assessment of fatalities due to earthquakes A Database and Empirical Model for Earthquake Post Loss Amplification User guide Android mobile tool for field data collection Variable resolution probabilistic modeling of residential exposure and vulnerability for risk applications Earthquake-induced liquefaction and landslides in Cali, Colombia Development of the Earthquake Risk Model for Myanmar Seismic Risk Model for the Beijing–Tianjin–Hebei Region, China-Considering Epistemic Uncertainty from the Seismic Hazard Models Strain partitioning in the Southeastern Tibetan Plateau from kinematic modeling of high-resolution Sentinel-1 InSAR and GNSS A township-level exposure model of residential buildings for mainland China Seismic Risk Model for the Beijing–Tianjin–Hebei Region, China-Considering Epistemic Uncertainty from the Seismic Hazard Models A township-level exposure model of residential buildings for mainland China Appraising the PSHA earthquake source models of Japan, New Zealand, and Taiwan Significant Seismic Risk Potential From Buried Faults Beneath Almaty City, Kazakhstan, Revealed From High-Resolution Satellite DEMs Material didáctico para sensibilizar a la comunidad sobre el riesgo sísmico. Aplicación para el Área Metropolitana del Valle de Aburrá (AMVA) Ranking and developing ground-motion models for Southeastern Africa No content. Other Related Products GEM's country risk profile for Afghanistan GEM vulnerability model for Afghanistan GEM exposure model for Afghanistan (admin 1) GEM vulnerability model for Russia test GEM's country risk profile for Myanmar GEM vulnerability model for Myanmar GEM exposure model for China (admin 1) GEM vulnerability model for China GEM's country risk profile for China GEM exposure model for China (admin 1) GEM vulnerability model for China GEM's country risk profile for China GEM vulnerability model for Japan GEM exposure model for Japan (admin 1) GEM's country risk profile for Japan Japan Seismic Hazard Information Station GEM Earthquake Scenario Database (Japan events) Other Related Publications GEM's PSHA input model documentation for Middle East 1234 Yang et al. (2023) Probabilistic seismic hazard assessments for Myanmar and its metropolitan areas. Geoscience Letters, 10(1), 48 Tun et al. (2017) The Sagaing Fault, Myanmar. In A. J. Barber, K. Zaw, & M. J. Crow (Eds.), Myanmar: Geology, Resources and Tectonics (Vol. 48, p. 0). The Geological Society of London GEM's PSHA input model documentation for SouthEast Asia GEM's PSHA input model documentation for China GEM's PSHA input model documentation for China GEM's PSHA input model documentation for Japan DISCLAIMER The information and data provided on this page are for informational purposes only. The Global Earthquake Model (GEM) Foundation makes no warranties, expressed or implied, regarding the accuracy, completeness, or reliability of the data. Users are responsible for their own interpretation and use of the information. GEM shall not be liable for any loss, damage, or injury arising from the use of, or reliance on, the information provided on this page. 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Publications Site Effects in Parametric Ground Motion Models for the GEM-PEER Global GMPEs Project Share Facebook LinkedIn Download 2012 | Peer-reviewed We review site parameters used in ground motion prediction equations (GMPEs) for various tectonic regimes and describe procedures for estimation of site parameters in the absence of site-specific data. Most modern GMPEs take as the principal site parameter the average shear wave velocity in the upper 30 m of the site (Vs30) either directly or as the basis for site classification into categories. Three GMPEs developed for active regions also use basin depth parameters. We review estimation procedures for Vs30 that utilize surface geology, terrain-based site categories, ground slope, or combinations of these. We analyze the relative efficacy of those procedures using a profile data set from California assembled in a recent NGA project. The results indicate that no single procedure is most effective and that prediction dispersion is lower for young sediments than for stiff soils or rock.

License Request Form You have chosen to get more information about: Europe Hazard Hazard Please check the link below to see if this product already meets your your requirements before submitting your request for a license. Thank you. DOWNLOAD THE OPEN VERSION Summary of steps to obtain a license for the requested product. Fill in the application form below. Click Submit. Please check your email Inbox or Spam folder for the summary of your request. You will then be contacted by the GEM Product Manager with either a request for more information, or a request to sign the license. If you do not hear from us within 2 weeks, please send an email to product@globalquakemodel.org . REQUEST DETAILS A. Requesting party information First Name Last Name Role/Job Email Business type Business type Other business Sector Sector Other sector B. License agreement signatory information The signatory must be someone who is authorised to sign license agreements on your behalf such as your immediate supervisor, manager or legal officer. If you’re a PhD student, the signatory must be your adviser or a university officer in charge of license agreements or similar legal documents. Full Name of Signatory Position Company Email of Signatory Organisation name Complete Address C. Purpose of request GEM is able to offer products for free because of the support of our project partners, national collaborators and institutional sponsors. All of GEM’s products are freely available for public good, non-commercial use, but with different license restrictions. In most cases we release products under an open license (e.g., CC BY-SA or CC BY-NC-SA), which permits (re)distribution. In this case, we are granting access under a more restricted license that forbids distribution or disclosure and requires signing by GEM and the licensee in order to better assure accountability for the confidentiality of the information. In order for GEM to properly assess your request, please answer the following questions below. 1. Explain briefly how will the GEM product be used e.g. project, research including the expected results and the foreseen public benefit. 2. Will you be able to share the results of your work with GEM? YES NO 3. Will you be able to provide feedback to GEM on the quality and usefulness of this product via a survey? YES NO C. Privacy Policy By submitting this form, you consent to the processing of your personal data in accordance with our Privacy Policy and the EU General Data Protection Regulation (GDPR). We are committed to safeguarding your information and ensuring it is only used for the purpose outlined in this form. You have the right to access, rectify, or delete your data at any time. For more information, please refer to our Privacy Policy. I agree Words: 0 Email us at product@globalquakemodel.org if you're experiencing problems submitting your application. Thank you. Submit Thanks for submitting! You will be contacted as soon as possible Incomplete data. Please fill in all required fields. Thank you.

News Will measuring losses to natural disasters really tell us about changes in risk? By: Jul 2, 2018 Share Facebook LinkedIn Two years ago, in March 2015, representatives of 187 countries met in Sendai, Japan to agree to the Sendai Framework for Disaster Risk Reduction for the period 2015 to 2030. Last month, on February 2nd, the UN General Assembly approved seven global targets to reduce risk from natural disasters, and agreed to a set of indicators for measuring global progress toward these targets. The indicators for Targets A, B, and C aim to reduce by 2030 mortality, affected people, and economic loss, respectively. The targets will be to reduce impacts in a relative sense, so that mortality and affected people will be measured per 100,000 population; and economic loss will be measured in relation to gross domestic product. Global Target D aims to reduce risk to critical infrastructure, including health and educational facilities. In the article “How can the world reduce losses for the poor?” Robert Glasser, UNISDR, states that the measurement of the indicators introduces a “major degree of accountability” for the seven global targets, but will the proposed measurement of disaster losses actually be useful for monitoring changes in risk? The answer is yes and no. Why the Sendai indicators are not enoughWhile measuring these indicators will be quite useful, it is highly unlikely that this monitoring process alone will allow the world to accurately measure the actual reduction in risk, particularly for rare, high impact events, such as major earthquakes, cyclones and volcanic eruptions. For instance, Munich Re estimates that worldwide the average annual deaths for the past ten years from all natural disasters was about 60,000 people, while last year accounted for only 8,600 deaths. Yet, in the 2004 Indian Ocean Earthquake and Tsunami, more than 230,000 people died in a single event. With such a high variation in annual losses at the global scale, there is little chance that monitoring such variation alone will give us an accurate picture of risk at a global scale, and certainly not at a national or urban scale. An alternative way of more accurately measuring riskBy the end of 2018, GEM will have produced a global earthquake risk model, which will provide a baseline at national level for earthquake hazard and risk globally. Moreover, the model and all of the tools and data underlying the model will be available openly, freely and transparently for the public good. This information can and should be used to monitor risk. Since risk is a function of hazard, vulnerability and exposure, the trends in these variables measured over time will allow us to determine the extent to which we are meeting the global targets for risk reduction. Moreover, this will be possible not only at the global level, but also at the national and even urban/local levels. Changes in exposure will be necessary to determine how the distribution of population, assets and investments are evolving spatially and temporally. Similarly, measuring vulnerability will be critical to understand how social, physical and economic factors are evolving and contributing to changing risk. Changes in the physical risk to schools, hospitals and other vulnerable building types can be estimated at local to global levels by collecting exposure and vulnerability information and tracking retrofits and new construction over time. One approach would be to collect information on the ratios of numbers of buildings constructed above and below building code standards, such as for unreinforced masonry, the building class most vulnerable to earthquake damage and casualties. Trends could be tracked to estimate changes in risk in terms of potential physical and economic loss. Finally, disaster mitigation could be incentivized by providing tools to demonstrate the cost-benefits of retrofitting or replacing these and other vulnerable buildings in high-risk areas. Thus, the information in risk models can be used to both track changes in risk as well as to identify cost-effective opportunities for risk mitigation and reduction activities. GEM’s contribution to disaster risk reductionGEM is very well placed to assist in the process of informing the recently agreed Sendai targets by working with countries to develop national earthquake hazard models, by assisting in collecting and analyzing vulnerability and exposure data, and by combining this information into a risk modeling and monitoring framework at national and urban levels. This would be accomplished by further developing partnerships in developing countries to increase their capacity to assess and manage earthquake risks. GEM is also developing tools that can be used in both developing and developed countries to assess the costs and benefits of mitigating and/or reducing these risks. With continued investment over time, these and other risk models, tools and data can be further developed to provide much needed support to achieving the goals of the Sendai Framework. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News Canada joins GEM as Public Sponsor By: Jul 2, 2018 Share Facebook LinkedIn Canada’s ‘coalition of the willing’ led by Natural Resources Canada - with members Public Safety Canada, Insurance Bureau of Canada, Defence Research and Development Canada, Institute for Catastrophic Loss Reduction, Canadian Institute of Planners and indigenous community - joins GEM as Public Sponsor. GEM Governing Board officially welcomed Canada as its newest member earlier this month. The partnership is expected to contribute to the assessment of earthquake risk using OpenQuake in support of disaster risk reduction (DRR) planning in Canada. Phil Hill, official representative, expressed excitement and is looking forward to a fruitful collaboration especially in including indigenous population in GEM’s future tools development and risk models for Canada. A National Steering Committee composed of government, academia and private stakeholders with support from an Expert Working Group will implement GEM in Canada. Canada is the 12th member of GEM from the government sector – joining Italy, Australia, UK, Germany, USA, Japan, New Zealand, Switzerland, Norway, Taiwan and Nepal. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

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