Global Exposure Model

✨ Overview

The v2023.1.1 release for the GEM's global exposure model is available! 🥳 🚀

This repository hosts the exposure information for the world. It includes figures, summaries and data for each country or territory, for the region (see Region, country and territory list), and for the world.

Global Exposure Model

Global Exposure Model macro-taxonomy

Available information

At country and territory level:

Summary of exposure model at the national level
Exposure model at the first administrative level
Summary of the exposure model aggregated per building class (taxonomy)
Figures for building counts, total replacement cost, and built-up area disaggregated per occupancy type, macrotaxonomy at the national level and at the first administrative level
In the _Metadata regional folder, files are available for the mapping schemes used to associate building counts to different building classes

At regional level:

Metadata for each country in the region
Summary of regional counts and summaries per macrotaxonomy
Figures for building counts, total replacement cost, and built-up area disaggregated per occupancy type and macrotaxonomy

At global level: In the World folder you can find

Maps for building counts, total replacement cost, and built-up area
Maps for main construction material
World summaries and charts for different exposure metrics
Charts for the top 20 countries and territories with a larger concentration of exposure

🚀 Model versions

Each version of the model that is released can be accessed by changing from the main branch to the tag of a given version. The main branch could contain the work-in-progress of the next version of the model.

Version	Release Notes
v2018.0.0	Original version within the larger 2018 Global Risk Model release.
v2022.0.0	Improvements of the global exposure model, compared with the v2018.0.0, include: Building counts and replacement costs updated to 2021 values (include updates in dwelling and establishment counts, mapping schemes, average area, number of stories, replacement cost, code and expected ductility level). Reviewed non-residential models to improve spatial distribution
v2023.0.0	Minor revision relative to `v2022.0.0`: Population distributed across day, night, and transit time periods. Few country-specific updates.
v2023.1.0	Exposure models corresponding to the official June 2023 GEM release of the Global Risk Model. Specific modifications include: Canada updated the replacement costs to end-2022 values using the building construction price indexes (BCPI) from StatCan and updated the population and dwelling counts to 2023 Q1 estimates. Ecuador and Argentina updated mapping for adobe building, now are assigned only when adobe material is specifically reported in census information. Ecuador also incorporates the urban model for metropolitan Quito. Italy changed the masonry unit types used in residential construction Switzerland updated floor areas and costs considering the ERM-CH23 model. Turkey updated after M7.8_Kahramanmaras-Gaziantep earthquake (destroyed buildings removed and changes in mapping schemes). USA major model update considering USACE NSI 2022, HAZUS 6.0, and FEMA P-366 / April 2023. Specific countries and territories updated building taxonomies for consistency. Minor adjustment to ensure consistency in boundary names. Minor adjustments in taxonomy strings for additional GEM vulnerability functions.
v2023.1.1	Add exposure files at Adm1 level for all countries and territories (based on models v2023.1.0)

🌍 Region, country and territory list

The following regions, countries and territories are covered in this repository.

REGION	COUNTRIES AND TERRITORIES
Africa	Algeria, Angola, Benin, Botswana, Burkina_Faso, Burundi, Cameroon, Cape_Verde, Central_African_Republic, Chad, Comoros, Congo, Democratic_Republic_of_the_Congo, Djibouti, Egypt, Equatorial_Guinea, Eritrea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea_Bissau, Ivory_Coast, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao_Tome_and_Principe, Senegal, Seychelles, Sierra_Leone, Somalia, South_Africa, South_Sudan, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia, Zimbabwe
Caribbean_Central_America	Anguilla, Antigua_and_Barbuda, Aruba, Bahamas, Barbados, Belize, British_Virgin_Islands, Cayman_Islands, Costa_Rica, Cuba, Dominica, Dominican_Republic, El_Salvador, Grenada, Guadeloupe, Guatemala, Haiti, Honduras, Jamaica, Martinique, Montserrat, Nicaragua, Panama, Puerto_Rico, Saint_Kitts_and_Nevis, Saint_Lucia, Saint_Vincent_and_the_Grenadines, Trinidad_and_Tobago, Turks_and_Caicos_Islands, US_Virgin_Islands
Central_Asia	Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan
East_Asia	China, Hong_Kong, Japan, Macao, North_Korea, South_Korea, Taiwan
Europe	Albania, Andorra, Austria, Belarus, Belgium, Bosnia_and_Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Gibraltar, Greece, Hungary, Iceland, Ireland, Isle_of_Man, Italy, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, North_Macedonia, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United_Kingdom
Middle_East	Afghanistan, Armenia, Azerbaijan, Bahrain, Georgia, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Pakistan, Palestine, Qatar, Saudi_Arabia, Syria, United_Arab_Emirates, Yemen
North_America	Canada, Mexico, United_States_of_America
North_Asia	Mongolia, Russia
Oceania	American_Samoa, Australia, Cook_Islands, Fiji, Guam, Kiribati, Marshall_Islands, Micronesia, Nauru, New_Caledonia, New_Zealand, Niue, Northern_Mariana_Islands, Palau, Papua_New_Guinea, Samoa, Solomon_Islands, Tonga, Tuvalu, Vanuatu
South_America	Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, French_Guiana, Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela
South_Asia	Afghanistan, Bangladesh, Bhutan, India, Nepal, Pakistan, Sri_Lanka
Southeast_Asia	Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor_Leste, Vietnam

Explanation of exposure model content

Definition of column headers

Each exposure csv contains the following column headers, as briefly defined below

ASSET_ID: Unique identifier for an asset, which comprises a group of buildings sharing similar attributes and location
BUILDINGS: The total number of buildings comprising the asset. A building unit is defined as a permanent, separate, and independent structure designed to serve any activity. For constructions comprising blocks, terraced buildings, or buildings enclosed by common fencing, a building unit refers to the superstructure that is structurally designed to respond independently under seismic loads
COST_CONTENTS_USD: The cost of contents in each asset
COST_NONSTRUCTURAL_USD: The cost of nonstructural components in each asset
COST_PER_AREA_USD: The average replacement cost per unit area (in 2021 US$/sq.m., including the structural and nonstructural components, but not the building contents)
COST_STRUCTURAL_USD: The cost of structural components in each asset
DWELLING: A self-contained residential space within a building designed for habitation by one or more individuals or families. For example, a multi-story residential building is comprised of numerous dwelling units, such as multiple apartments within the same structure. Conversely, in a single-family detached unit, the number of dwelling units and buildings is the same
ESTABLISHMENT: A single physical location where economic activities occur (e.g., services or industrial operations). An establishment is often characterized by having a specific address, management, and operational control, distinct from other units of the same company or organization.
ID_1: ID for the first administrative level, matches either the ID used in the national census, the administrative division boundary vector files, or both
ID_i: ID for the administrative level i
NAME_1: Name of the first administrative level
NAME_i: Name of the administrative level i
LONGITUDE, LATITUDE: Geographical coordinates assigned to the asset for risk calculations. In general, these locations do not represent building-specific geolocations, but are either aggregated at a representative point for the lowest administrative level or are the result of the spatial disaggregation algorithm (and thus still represent aggregated assets, but at a finer resolution)
OCCUPANCY: The primary occupancy class: Res for residential, Com for commercial, and Ind for industrial
OCCUPANTS_PER_ASSET: The number of residents in each residential asset
OCCUPANTS_PER_ASSET_AVERAGE: The time-averaged number of occupants in each asset (residential, commercial, industrial)
OCCUPANTS_PER_ASSET_DAY: The average number of occupants in each asset (residential, commercial, industrial) during the daytime period
OCCUPANTS_PER_ASSET_NIGHT: The average number of occupants in each asset (residential, commercial, industrial) during the nighttime period
OCCUPANTS_PER_ASSET_TRANSIT: The average number of occupants in each asset (residential, commercial, industrial) during the transit time period
TAXONOMY: Building taxonomy string that is used for mapping vulnerability functions for the asset
TOTAL_AREA_SQM: The total floor area comprising the asset (sq.m.)
TOTAL_REPL_COST_USD: The total replacement cost for the asset (in 2021 US$, including the structural, nonstructural components, and building contents)

Where can I find additional information on the defined building classes?

The building classes defined within this exposure model follow the GEM Taxonomy v3.2 convention. Please refer to the GEM Taxonomy Glossary for additional details on taxonomy substrings and the Taxonomy_tables_v3.2.xlsx available here.

👨‍👩‍👧‍👦 Related datasets and resources

Users interested in the global exposure model might find the following GEM Foundation products useful:

📚 Publications

Please cite the work as follows: Yepes-Estrada, C., Calderon, A., Costa, C., Crowley, H., Dabbeek, J., Hoyos, M., Martins, L., Paul, N., Rao, A., Silva, V. (2023). Global Building Exposure Model for Earthquake Risk Assessment. Earthquake Spectra. doi:10.1177/87552930231194048

Repository

Regional and national model references

Africa: Paul et al. (2022)¹
Australia: Dunford and Power (2014)²
Canada: Journeay et al. (2022)³
Central America: Calderon et al. (2022)⁴
Central Asia: Pittore et al. (2020)⁵
China: Ma et al. (2021)⁶
Costa Rica: Calderon et al. (2019)⁷
Europe: Crowley et al. (2020)⁸
GED4GEM: Gamba et al. (2012)⁹
India: Rao et al. (2020)¹⁰
Iran: Motamed at al. (2019)¹¹
Middle East: Dabbeek and Silva (2020)¹²
New Zealand: Abbott et al. (2020)¹³
Pacific Island Countries: PCRAFI initiative¹⁴
South America: Yepes-Estrada et al. (2017)¹⁵
Turkey: Rao et al. (2021)¹⁶
United States: FEMA (2017)¹⁷

🌟 Contributors

The authors are grateful for the input from dozens of local and international experts. A list of contributors can be found at https://www.globalquakemodel.org/risk-model-contributors.

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which requires:

Attribution (you must give appropriate credit, provide a link to the license, and indicate if changes were made)
Non-commercial (you may not use the material for commercial purposes)
ShareAlike (derivatives created must be made available under the same license as the original)

If your use case deviates from the requirements of the offered license, but still want to explore the use of the data, please contact us at license@globalquakemodel.org

Any deviation from these terms incurs license infringement. For commercial use of the data contained within this work, a specific license agreement must be made tailored to your use case, in such instance please contact GEM at product@globalquakemodel.org.

🤔 Frequently asked questions

Which version am I seeing? How to change the version?

By default, you will see the files in the repository in the main branch. Each version of the model that is released is marked with a tag. By changing the tag version at the top of the repository, you can see the files for a given version.

Note that the main branch could contain the work-in-progress of the next version of the model.

How do I download the data for a given version?

For each version, a related zip file is available in the release section.

Administrative regions

The exposure models typically use the names of the administrative regions available in each country's census information, when available. However, depending on the available source data and base year for which the models are derived, the number of first-level administrative divisions and their names may differ from the current divisions and names for each country. GEM does not provide associated boundary files.

Where can I find the models at the highest available resolution?

Please contact us at product@globalquakemodel.org

References:

Paul, N., Silva, V., Amo-Oduro, D. (2022). Development of a uniform exposure model for the African continent for use in disaster risk assessment. International Journal of Disaster Risk Reduction, Volume 71, ISSN 2212-4209. doi: 10.1016/j.ijdrr.2022.102823. ↩
Dunford, M., Power, L. (2014). National Exposure Information System (NEXIS) Building Exposure - Statistical Area Level 1 (SA1). Geoscience Australia, Canberra, Australia. doi: 10.4225/25/5420C7F537B15. ↩
Journeay, M., LeSueur, P., Chow, W., Wagner, C.L. (2022). Physical exposure to natural hazards in Canada: An overview of methods and findings. GEOLOGICAL SURVEY OF CANADA, OPEN FILE 8892. Available at https://doi.org/10.4095/330012. ↩
Calderón, A., Silva V, Avilés, M., Méndez, R., Castillo, R., Gil, J., López, M. (2022). Toward a uniform earthquake loss model across Central America. Earthquake Spectra, 38(1):178-199. doi:10.1177/87552930211043894. ↩
Pittore, M., Haas, M., Silva, V. (2020). Variable resolution probabilistic modelling of residential exposure and vulnerability for risk applications. Earthquake Spectra, 36(1_suppl), 321-344. doi:10.1177/8755293020951582 ↩
Ma, J., Rao, A., Silva, V., Lui, K., Wang, M. (2021). A township-level exposure model of residential buildings for mainland China. Nat Hazards 108, 389–423. https://doi.org/10.1007/s11069-021-04689-7 ↩
Calderon, A., Silva, V. (2019). Probabilistic seismic vulnerability and loss assessment of the residential building stock in Costa Rica. Bulletin of Earthquake Engineering 17, 1257–1284. Doi: 10.1007/s10518-018-0499-1. ↩
Crowley, H., Despotaki, V., Rodrigues, D., Silva, V., Toma-Danila, D., Riga, E., Karatzetzou, A., Fotopoulou, S., Zugic, Z., Sousa, L., Ozcebe, S., Gamba, P. (2020). Exposure model for European seismic risk assessment. Earthquake Spectra, 36(1_suppl), 252–273. doi: 10.1177/8755293020919429. ↩
Gamba, P., Cavalca, D., Jaiswal, K., Huyck, C., Crowley, H. (2012). The GED4GEM Project: Development of a Global Exposure Database for the Global Earthquake Model Initiative. Proceedings of the 15th World Conference on Earthquake Engineering, Lisbon, Portugal. ↩
Rao, A., Dutta, D., Kalita, P., Ackerley, N., Silva, V., Raghunandan, M., Ghosh, J., Ghosh, S., Brzev, S., Dasgupta, K. (2020). Probabilistic seismic risk assessment of India. Earthquake Spectra, 36(1_suppl), 345–371. doi: 10.1177/8755293020957374. ↩
Motamed, H., Calderon, A., Silva, V., Costa, C. (2019). Development of a probabilistic earthquake loss model for Iran. Bulletin of Earthquake Engineering 17, 1795–1823. doi: 10.1007/s10518-018-0515-5. ↩
Dabbeek, J., Silva, V. (2020). Modelling the residential building stock in the Middle East for multi-hazard risk assessment. Natural Hazards 100, 781–810. doi: 10.1007/s11069-019-03842-7. ↩
Abbott, E., Horspool, N., Gerstenberger, M., Huso, R., Van Houtte, C., McVerry, G., Canessa, S. (2020). Challenges and opportunities in New Zealand seismic hazard and risk modelling using OpenQuake. Earthquake Spectra, 36, 210-225. doi:10.1177/8755293020966338. ↩
Pacific: Catastrophe Risk Assessment and Financing Initiative - PCRAFI ↩
Yepes-Estrada, C., Silva, V., Valcárcel J, Acevedo, A., Tarque, N., Hube, M., Coronel, G., Santamaría, H. (2017). Modelling the Residential Building Inventory in South America for Seismic Risk Assessment. Earthquake Spectra, 33(1), 299-322. doi:10.1193/101915eqs155dp. ↩
Rao, A., Calderón, A., Silva, V., Martins, L., Paul, N. (2021). Earthquake Risk Assessment and Retrofit Scenarios for Turkey. Report for the World Bank. ↩
FEMA, Federal Emergency Management Agency (2017). FEMA P-366: Hazus® Estimated Annualized Earthquake Losses for the United States. ↩

ekh351/global_exposure_model