Open-File Report 2008–1160
Earthquakes have claimed approximately 8 million lives over the last 2,000 years (Dunbar, Lockridge and others, 1992) and fatality rates are likely to continue to rise with increased population and urbanizations of global settlements especially in developing countries. More than 75% of earthquake-related human casualties are caused by the collapse of buildings or structures (Coburn and Spence, 2002). It is disheartening to note that large fractions of the world’s population still reside in informal, poorly-constructed & non-engineered dwellings which have high susceptibility to collapse during earthquakes. Moreover, with increasing urbanization half of world’s population now lives in urban areas (United Nations, 2001), and half of these urban centers are located in earthquake-prone regions (Bilham, 2004). The poor performance of most building stocks during earthquakes remains a primary societal concern. However, despite this dark history and bleaker future trends, there are no comprehensive global building inventories of sufficient quality and coverage to adequately address and characterize future earthquake losses. Such an inventory is vital both for earthquake loss mitigation and for earthquake disaster response purposes. While the latter purpose is the motivation of this work, we hope that the global building inventory database described herein will find widespread use for other mitigation efforts as well.
For a real-time earthquake impact alert system, such as U.S. Geological Survey’s (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER), (Wald, Earle and others, 2006), we seek to rapidly evaluate potential casualties associated with earthquake ground shaking for any region of the world. The casualty estimation is based primarily on (1) rapid estimation of the ground shaking hazard, (2) aggregating the population exposure within different building types, and (3) estimating the casualties from the collapse of vulnerable buildings. Thus, the contribution of building stock, its relative vulnerability, and distribution are vital components for determining the extent of casualties during an earthquake.
It is evident from large deadly historical earthquakes that the distribution of vulnerable structures and their occupancy level during an earthquake control the severity of human losses. For example, though the number of strong earthquakes in California is comparable to that of Iran, the total earthquake-related casualties in California during the last 100 years are dramatically lower than the casualties from several individual Iranian earthquakes. The relatively low casualties count in California is attributed mainly to the fact that more than 90 percent of the building stock in California is made of wood and is designed to withstand moderate to large earthquakes (Kircher, Seligson and others, 2006). In contrast, the 80 percent adobe and or non-engineered masonry building stock with poor lateral load resisting systems in Iran succumbs even for moderate levels of ground shaking. Consequently, the heavy death toll for the 2003 Bam, Iran earthquake, which claimed 31,828 lives (Ghafory-Ashtiany and Mousavi, 2005), is directly attributable to such poorly resistant construction, and future events will produce comparable losses unless practices change. Similarly, multistory, precast-concrete framed buildings caused heavy casualties in the 1988 Spitak, Armenia earthquake (Bertero, 1989); weaker masonry and reinforced-concrete framed construction designed for gravity loads with soft first stories dominated losses in the Bhuj, India earthquake of 2001 (Madabhushi and Haigh, 2005); and adobe and weak masonry dwellings in Peru controlled the death toll in the Peru earthquake of 2007 (Taucer, J. and others, 2007). Spence (2007) after conducting a brief survey of most lethal earthquakes since 1960 found that building collapses remains a major cause of earthquake mortality and unreinforced masonry buildings are one of the most vulnerable building stock throughout the world. Hence, it becomes clear that mapping out the extreme variations of the vulnerabilities in global building inventories is essential for both long-term earthquake loss mitigation and for rapidly identifying disasters. Unfortunately, information about the global building stock and its vulnerability is very limited and most often nonexistent. Building inventory and vulnerability data are publicly available only for handful of countries or regions around the globe.
This report describes the procedure that has been adopted as a first pass at the development of a global building inventory database. The inventory development consists of estimates of the fractions of building types observed in each country, their functional use, and average day and night occupancy. Various data sources exist that provide building-specific information at a local or regional level with varying degrees of confidence; however, few data sources have been found to be relevant, consistent, and useful to our needs on a global scale. The inventory development methodology presented in this report not only compiles data from various sources but also allows us to rate and select the best source based on its vintage and quality. The building-specific inventory distribution developed is necessary for the casualty estimation methodology used for the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) system.
The database developed during this investigation has been made available as an electronic supplement (Appendix VII) of this report. The database contains four tables, each reflecting a combination of urban or rural, residential or non-residential category. The fraction of building types or dwellings and their occupancy characteristics have been collated for each country to represent a country-specific distribution (represented by a row in each of the four table specific to a country and is also representative of population exposure) by PAGER structure types. As more data become available, we expect that the existing online inventory database will get replaced in parts with better quality data. The inventory database developed herein exists in the public domain, subject to peer review, scrutiny, and open enhancement. The database is available in most common accessible and readable format (Microsoft Excel spreadsheet) for the worldwide user community. Having the electronic supplement of this database will not only help users to access it online but will also allow the possibility of enhancing the quality of data through an open review and development process.
Posted October 2008
This is an electronic copy of Appendix VII that contains four spreadsheets. Refer to the sheet named, Release_Notes, included in this database file for more information.
Jaiswal, K.S., and Wald, D.J., 2008, Creating a global building inventory for earthquake loss assessment and risk management: U.S. Geological Survey Open-File Report 2008-1160, 103 p.
Inventory Literature and Data Review
Inventory Data Sources
UN Statistical Database on Global Housing (1993)
UN-HABITAT Database (2007)
Housing Census Database (Country-Specific)
World Housing Encyclopedia Database (Country-Specific)
Data Compiled from Published Literature
PAGER Specific Inventory Needs
Phase I: Database Identification, Preparation, and Confidence Rating
Geographic Location and Resolution
Construction Type Classification
Average Occupancy by Construction Type
Phase II: Data Prioritization, Merging, and Country Assignments
Selection of Attribute Assignments Using Ratings and Vintage of Data Source
Phase III: Data Development for Missing Entries and Synthesis
Missing Entries and Country-Pairing
PAGER Inventory Matrix Compilation
Limitations of the Methodology
Illustration of Inventory Data Compilation for Peru
United Nations Housing Database
UN-HABITAT (2007) DHS Database
Population and Housing Census
World Housing Encyclopedia (WHE) Reports
Published Literature of Housing/Building Stock
Inventory Compilation for Selected Countries
Application to the Continental United States
Web Delivery of Global Inventory
Processing of Raw Data
Construction Type Mapping
Occupancy by Construction Type
Limitations of PAGER Inventory Database
Housing Units and Building/Structure Type Inventory
Wall Material and Structure Type
Vintage of Database
Resolution of Inventory Distribution
Scope of Inventory Updating