Jamie L. Jones
Laurie A. Johnson
Anne M. Wein
Jeff Peters
20200616
Estimated geospatial and tabular damages and vulnerable population distributions resulting from exposure to multiple hazards by the M7.0 HayWired scenario on April 18, 2018, for 17 counties in the San Francisco Bay region, California
tabular and vector digital data
USGS Scientific Investigations Report
2017-5013
Accompanies HayWired vol. 3--Societal consequences
https://doi.org/10.5066/P94Z8BOZ
Laurie A. Johnson
Jamie L. Jones
Anne M. Wein
Jeff Peters
2020
Communities at risk analysis of the HayWired scenario
publication
USGS Scientific Investigations Report
2017-5013
Reston, VA
U.S. Geological Survey
Accompanies HayWired vol. 3--Societal consequences; encompasses five chapters: U1--Overview of the communities at risk analysis of the HayWired scenario with policy implications, U2--Integrated building damage and areas of concentrated damage, U3--Population movements and vulnerabilities, U4--Long-term community recovery challenges, and U5--Research needs resulting from the communities at risk analysis of the HayWired scenario.
https://doi.org/10.3133/sir20175013
This data release is comprised of geospatial and tabular data developed for the HayWired communities at risk analysis. The HayWired earthquake scenario is a magnitude 7.0 earthquake hypothesized to occur on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA.
The following 17 counties are included in this analysis unless otherwise specified: Alameda, Contra Costa, Marin, Merced, Monterey, Napa, Sacramento, San Benito, San Francisco, San Joaquin, San Mateo, Santa Clara, Santa Cruz, Solano, Sonoma, Stanislaus, and Yolo.
The vector data are a geospatial representation of building damage based on square footage damage estimates by Hazus occupancy class for developed areas covering all census tracts in 17 counties in and around the San Francisco Bay region in California, for (1) earthquake hazards (ground shaking, landslide, and liquefaction) and (2) all hazards (ground shaking, landslide, liquefaction, and fire) resulting from the HayWired earthquake scenario mainshock.
The tabular data cover: (1) damage estimates, by Hazus occupancy class, of square footage, building counts, and households affected by the HayWired earthquake scenario mainshock for all census tracts in 17 counties in and around the San Francisco Bay region in California; (2) potential total population residing in block groups in nine counties in the San Francisco Bay region in California (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma); (3) a subset of select tables for 17 counties in and around the San Francisco Bay region in California from the U.S. Census Bureau American Community Survey 5-year (2012-2016) estimates at the block group level selected to represent potentially vulnerable populations that may, in the event of a major disaster, leave an area rather than stay; and (4) building and contents damage estimates (in thousands of dollars, 2005 vintage), by Hazus occupancy class, for the HayWired earthquake scenario mainshock for 17 counties in and around the San Francisco Bay region in California.
The vector .SHP datasets were developed and intended for use in GIS applications such as ESRI's ArcGIS software suite. The tab-delimited .TXT datasets were developed and intended for use in standalone spreadsheet or database applications (such as Microsoft Excel or Access). Please note that some of these data are not optimized for use in GIS applications (such as ESRI's ArcGIS software suite) as-is--census tracts or counties are repeated (the data are not "one-to-one"), so not all information belonging to a tract or county would necessarily be associated with a single record. Separate preparation is needed in a standalone spreadsheet or database application like Microsoft Excel or Microsoft Access before using these data in a GIS.
These data support the following publications: Johnson, L.A., Jones, J.L., Wein, A.M., and Peters, J., 2020, Communities at risk analysis of the HayWired scenario, chaps. U1-U5 of Detweiler, S.T., and Wein, A.M., eds., The HayWired earthquake scenario--Societal consequences: U.S. Geological Survey Scientific Investigations Report 2017-5013, https://doi.org/10.3133/sir20175013.
These data were collected in support of the Science Application for Risk Reduction (SAFRR) project's HayWired earthquake scenario.
Appropriate use may include future work related to research using the HayWired earthquake scenario as its earthquake source.
Please note that this dataset is based on scenario earthquake shaking data and does not represent any known future earthquake activity. These data are for educational and training purposes only.
While the geospatial vector data are based on 2010 vintage Census tracts, areas not classified as "developed" land in the 2011 National Land Cover Database (NLCD) are omitted from the data.
20100301
20180418
observed
None planned
-123.5334
-120.0988
38.9259
35.7911
None
Hazus-MH 2.1
Building damage
Square footage
HayWired
Census tract
Building occupancy class
Block group
American Community Survey
Vulnerable populations
Young and mobile
County
Fire following earthquake
USGS Thesaurus
earthquakes
hazards
landslides
liquefaction
USGS Metadata Identifier
USGS:5d3b7be7e4b01d82ce8d7b6c
None
San Francisco Bay area
Common geographic areas
California
None. Please see 'Distribution Info' for details.
None. Users are advised to read the data set's metadata thoroughly to understand appropriate use and data limitations.
Jamie L Jones
U.S. Geological Survey, SOUTHWEST REGION
Geographer
mailing address
350 North Akron Road
Moffett Field
CA
94035
US
650-439-2425
jamiejones@usgs.gov
Ann-Margaret Esnard and Mary Comerio of the University of California, Berkeley provided valuable expert advice on the damage concentration analysis methodology developed as part of this study. Laura Dinitz, formerly with the U.S. Geological Survey, was instrumental in helping with the initial damage concentration analyses, mapping, and other analytical data products. Aksel Olsen and Cynthia Kroll of the Association of Bay Area Governments (ABAG), Dana Brechwald of the Bay Conservation and Development Commission (BCDC) and formerly with ABAG, and Dena Belzer and Carline Au of Strategic Economics conducted analyses of the Hazus, U.S. Census, and ABAG Community Vulnerability Indicators data. Kent David, Maiclaire Bolton, and Tom Larsen of CoreLogic performed the insurance loss analysis these data are contrasted with and Janiele Maffei, Shawna Ackerman, and D'Anne Orsay of the California Earthquake Authority (CEA) provided data and mapping of the state residential earthquake insurance and housing mitigation programs.
For the vector geospatial datasets, formal attribute accuracy tests were conducted by the author. All data fall within a range of 0 (no building stock damage classified extensive or complete) to 1 (all building stock damage classified extensive or complete).
For the tabular datasets, no formal attribute accuracy tests were conducted.
The vector geospatial data are presented as discrete vector .SHP files with values ranging from 0 to 1. All values fall within the expected range. No overlapping data were found following the final analysis (any overlaps were consolidated or removed as the situation required). Topology tests were conducted to ensure the integrity of the geospatial data.
For any tabular data based on square footage, in cases where damaged square footage was reported as negative (this may infrequently occur when computing damages in small occupancy classes in small census tracts), the negative values were replaced with zeros.
For any remaining tabular data, formal logical consistency tests were conducted by the dataset author. All values fall within expected ranges.
Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
A formal accuracy assessment of the horizontal positional information in the data set has not been conducted.
A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2011
California 2010 Census tract boundaries
vector digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20100301
20101201
observed
Census tract boundaries, 2010
Boundaries used in the creation of many of the final datasets.
U.S. Geological Survey
20141010
NLCD 2011 Land Cover (2011 Edition, amended 2014)
raster digital data
Sioux Falls, SD
U.S. Geological Survey
http://www.mrlc.gov/nlcd2011.php
Digital and/or Hardcopy
20070409
20111111
publication date
NLCD developed land
Developed land portion used in constraining census tract boundaries to developed areas.
Hope A. Seligson
Jamie L. Jones
2019
Estimated square footage damaged, by damage state, resulting from the M7.0 HayWired scenario on April 18, 2018, for 17 counties in the San Francisco Bay region, California
tabular digital data
USGS Scientific Investigations Report
2017-5013-I-Q
Accompanies HayWired vol. 2--Engineering implications
https://doi.org/10.5066/P9UWWM0W
Digital and/or Hardcopy
20180418
publication date
Square footage damaged by Hazus occupancy class and damage state, earthquake hazards
Square footage damage (from earthquake hazards--ground shaking, landslide, and liquefaction) by damage state and occupancy class, used in the creation of any final datasets based on earthquake hazards damage.
Jamie L. Jones
Anne M. Wein
Laurie A. Johnson
Jeff Peters
2020
Estimated square footage, building count, and households affected, by damage state, by the M7.0 HayWired scenario on April 18, 2018, for 17 counties in the San Francisco Bay region, California
tabular digital data
USGS Scientific Investigations Report
2017-5013
Accompanies HayWired vol. 3--Societal consequences
https://doi.org/10.5066/P94Z8BOZ
Digital and/or Hardcopy
20180418
publication date
Square footage damaged by Hazus occupancy class and damage state, all hazards
Square footage damage (from all hazards--ground shaking, landslide, liquefaction, and fire following earthquake) by damage state and occupancy class, used in the creation of any final dataset based on all hazards damage.
Federal Emergency Management Agency
2013
Hazus-MH 2.1 earthquake user manual
publication
Washington, D.C.
Federal Emergency Management Agency
https://www.fema.gov/media-library-data/20130726-1820-25045-1179/hzmhs2_1_eq_um.pdf
Digital and/or Hardcopy
2013
publication date
Hazus-MH 2.1 earthquake user manual
Information about the use and underlying structure of the databases created by Hazus-MH 2.1.
Federal Emergency Management Agency
2012
Hazus-MH 2.1 earthquake technical manual
publication
Washington, D.C.
Federal Emergency Management Agency
http://www.fema.gov/media-library-data/20130726-1820-25045-6286/hzmh2_1_eq_tm.pdf
Digital and/or Hardcopy
2012
publication date
Hazus-MH 2.1 earthquake technical manual
Information about the use and underlying structure of Hazus-MH 2.1.
Charles Scawthorn
2019
Fire following the Mw 7.0 HayWired earthquake scenario
vector digital data
USGS Scientific Investigations Report
2017-5013-I-Q
Accompanies HayWired vol. 2--Engineering implications
https://doi.org/10.5066/P9LMGHRV
Digital and/or Hardcopy
20180418
publication date
Scawthorn, 2019
Fire following earthquake data used in the production of any final datasets using all hazards (ground shaking, landslide, liquefaction, fire) inputs.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2001
Census tract boundaries, 2000
vector digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20000301
20001201
publication date
Census tract boundaries, 2000
Boundaries used in combination with the fire Voronoi polygons to distribute burned square footage to census tracts.
Hope A. Seligson
Anne M. Wein
Jamie L. Jones
20180418
HayWired scenario--Hazus analyses of the mainshock and aftershocks
publication
USGS Scientific Investigations Report
2017-5013-I-Q
Reston, VA
U.S. Geological Survey
Chapter in HayWired vol. 2--Engineering implications
https://doi.org/10.3133/sir20175013
Digital and/or Hardcopy
20180418
20181001
publication date
Seligson and others, 2018
Methodology used for developing original estimates of square footage damaged by earthquake hazards caused by the HayWired mainshock.
Charles Scawthorn
Andrew D. Cowell
Frank Borden
1996
Fire-related aspects of the Northridge earthquake
publication
https://nehrpsearch.nist.gov/static/files/NIST/PB99102642.pdf
Digital and/or Hardcopy
1996
publication date
Scawthorn and others, 1996
Background information used in distributing square footage burned between occupancy groupings.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2011
Census 2000 to 2010 Census tract relationship file for California
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov/geographies/reference-files/2010/geo/relationship-files.html
Digital and/or Hardcopy
20000301
20101201
publication date
Census tract relationship file
Relationship file used to redistribute data in 2000 Census tracts to 2010 Census tracts.
Dana Brechwald
Cynthia Kroll
Lindy Lowe
Wendy Goodfriend
2015
Housing and community risk multiple hazard risk assessment
publication
San Francisco, CA
Association of Bay Area Governments, Resilience Program
http://resilience.abag.ca.gov/wp-content/documents/housing/Final%20Report/StrongerHousingSaferCommunities_TechnicalReport.pdf
Digital and/or Hardcopy
2015
publication date
Stronger housing, safer communities technical report
Methodology used by the Association of Bay Area Governments to determine thresholds of community vulnerability for selected community indicators, which informs the methodology used in this analysis.
Association of Bay Area Governments
San Francisco Bay Conservation and Development Commission
2016
Community Vulnerability Indicators by block group shapefile for San Francisco Bay area, 2016 update
vector digital data
San Francisco, CA
Association of Bay Area Governments
Alternative link to data: http://www.adaptingtorisingtides.org/maps-and-data-products/
http://resilience.abag.ca.gov/open-data/
Digital and/or Hardcopy
20100301
20141201
observed
Community Vulnerability Indicators dataset, 2016
Base data used in the development of the final CVI population distribution dataset.
San Francisco Bay Conservation and Development Commission
2016
Community indicators for flood risk
publication
San Francisco, CA
San Francisco Bay Conservation and Development Commission
http://www.adaptingtorisingtides.org/wp-content/uploads/2015/09/BCDC-Community-Indicators-for-Flood-Risk-User-Guide-2016.pdf
Digital and/or Hardcopy
2016
publication date
Community indicators for flood risk
Describes how Community Vulnerability Indicators (CVI) data were updated from the original analysis.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2011
California 2010 Census block group boundaries
vector digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20100301
20101201
observed
Census block group boundaries, 2010
Used to replace block groups excluded from the original Community Vulnerability Indicators (CVI) dataset. These are generally block groups where the percentage of all ten CVI classes are below the thresholds defined for each class.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2015
American Community Survey 2010-2014 5-year estimates, table B01001--Sex by age
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20100301
20141201
observed
Total population
Used to obtain total population estimates for block groups excluded from the original Community Vulnerability Indicators (CVI) dataset. These are generally block groups where the percentage of all ten CVI classes are below the thresholds defined for each class.
Jamie L. Jones
Jeff Peters
Laurie A. Johnson
Anne M. Wein
2020
Building stock damage (as percentages) by generalized occupancy class for developed areas of census tracts (2010 vintage) affected by earthquake hazards (ground shaking, landslide, and liquefaction) of the HayWired earthquake scenario mainshock for counties in the San Francisco Bay area, California
tabular digital data
USGS Scientific Investigations Report
2017-5013
Accompanies HayWired vol. 3--Societal consequences
https://doi.org/10.5066/P94Z8BOZ
Digital and/or Hardcopy
20180418
observed
Areas of concentrated damage, earthquake hazards
Used to identify block groups located in tracts with 20 percent or greater building stock damage classified as extensive or complete as a result of HayWired earthquake scenario earthquake hazards: ground shaking, landslide, and liquefaction.
Jamie L. Jones
Jeff Peters
Laurie A. Johnson
Anne M. Wein
2020
Building stock damage (as percentages) by generalized occupancy class for developed areas of census tracts (2010 vintage) affected by all hazards (ground shaking, landslide, liquefaction, and fire following earthquake) of the HayWired earthquake scenario mainshock for counties in the San Francisco Bay area, California
vector digital data
USGS Scientific Investigations Report
2017-5013
Accompanies HayWired vol. 3--Societal consequences
https://doi.org/10.5066/P94Z8BOZ
Digital and/or Hardcopy
20180418
observed
Areas of concentrated damage, all hazards
Used to identify block groups located in tracts with 20 percent or greater building stock damage classified as extensive or complete as a result of all HayWired earthquake scenario hazards: ground shaking, landslide, liquefaction, and fire.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B14007--School enrollment by detailed level of school for the population 3 years and over
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Population of school age
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for block groups.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B22010--Receipt of food stamps/SNAP in the past 12 months by disability status for households
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Households by disability status
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for block groups.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B25007--Tenure by age of householder
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Households by age group for householder
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for block groups.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B11005--Households by presence of people under 18 years by household type
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Households by household type and presence of children
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for block groups.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B19037--Age of householder by household income in the past 12 months (in 2016 inflation-adjusted dollars)
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Households by age of householder and annual income
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for block groups.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B25063--Gross rent
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Renter-occupied households by rent amount
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for block groups.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B19013--Median household income in the past 12 months (in 2016 inflation-adjusted dollars)
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Median household income
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for counties.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2017
American Community Survey 2012-2016 5-year estimates, table B25064--Median gross rent (dollars)
tabular digital data
Washington, D.C.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
https://www.census.gov
Digital and/or Hardcopy
20120301
20161201
observed
Median gross rent
Source table used in the creation of the final additional vulnerable/mobile populations dataset. Data obtained for counties.
Hope A. Seligson
Jamie L. Jones
2019
Estimated value of building damage resulting from the M7.0 HayWired scenario on April 18, 2018, for 17 counties in the San Francisco Bay region, California
tabular digital data
USGS Scientific Investigations Report
2017-5013-I-Q
Accompanies HayWired vol. 2--Engineering implications
https://doi.org/10.5066/P9UWWM0W
Digital and/or Hardcopy
20180418
observed
Building damage by census tract by occupancy class
Building damage data used in the creation of the final integrated building and contents economic losses dataset.
Jamie L. Jones
Carline Au
2020
Economic subareas of interest for areas containing concentrated damage resulting from the April 18, 2018, HayWired earthquake scenario in the San Francisco Bay region, California
vector digital data
USGS Scientific Investigations Report
2017-5013
Accompanies HayWired vol. 3--Societal consequences
https://doi.org/10.5066/P9CLW518
Digital and/or Hardcopy
20180418
observed
Economic subareas
Shapefile used to assign census units to economic subareas when applicable.
Hope A. Seligson
Jamie L. Jones
2019
Estimated building and contents replacement values for 17 counties in the San Francisco Bay region, California
tabular digital data
USGS Scientific Investigations Report
2017-5013-I-Q
Accompanies HayWired vol. 2--Engineering implications
https://doi.org/10.5066/P9UWWM0W
Digital and/or Hardcopy
2005
2018
publication date
Building and contents replacement values by census tract by occupancy class
Base building and contents value data used in the creation of the final dataset.
Building damage shapefiles methodology, step 1:
Hazus occupancy class data for square footage damaged by (1) all HayWired earthquake scenario mainshock hazards (ground shaking, landslide, liquefaction, and fire) and (2) HayWired earthquake hazards (ground shaking, landslide, and liquefaction) were aggregated into eight generalized occupancy groups for use in various summary analyses. Five of these generalized occupancy groups (industrial and warehouse; offices; retail and commercial; household-serving; and agricultural uses) were classified as non-residential, with the remaining three groups (single family/duplex; multi-family; and group living) classified as residential. A total across all building occupancy classes was also tabulated for use as an all-occupancies group. Using the square footage damage distributed by damage state and Hazus occupancy class, the percentage of extensive (approximate to "yellow-tag" result from building safety inspections) or complete (approximate to "red-tag" result from building safety inspections) damage to building stock for each generalized occupancy group was calculated for each tract.
Square footage damaged by Hazus occupancy class and damage state, all hazards
2017
Building damage shapefiles methodology, step 2:
The percentages calculated for the eight generalized occupancy groups and the all-occupancies group were developed for use in identifying potential areas of concentrated damage. Tracts with 20 percent or greater building square footage damage are considered an area of concentrated damage for a generalized occupancy group. The percentages, originally calculated in Microsoft Excel, were added to the attribute table of a 2010 vintage census tract shapefile using a table join in ArcMap 10.4 and then saved as a new shapefile to combine the shapefile attribute table and the join table.
Census tract boundaries, 2010
2017
Building damage shapefiles methodology, step 3:
Since we assume that building stock damages will occur in built-up areas, the census tract boundary dataset was clipped to remove non-developed land. We distinguished between developed and non-developed areas using the 2011 National Land Cover Dataset (NLCD), a 30-meter resolution raster dataset. The low-, moderate-, and high-intensity developed land classes were used to define developed land, with all other land cover classes treated as non-developed land. A new attribute was added to the raster attribute table in ArcMap 10.4, where each land cover class was reclassified to either developed or non-developed. The new attribute field was used to convert the land cover raster to a polygon dataset. Finally, the developed land portion of the new shapefile was used to clip the census tract boundaries and omit areas where the 2011 NLCD was classified as non-developed.
Census tract boundaries, 2010
NLCD developed land
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 1:
The Hazus-MH v 2.1 methodology makes assumptions about building types, codes, and fragilities, and the timeframes for the repair and return to function for buildings. Hazus used estimates of the square footage of building types/codes in 33 occupancy classes within each 2000 vintage census tract. For ground shaking, liquefaction, and landslide hazards, Hazus estimates building damages in terms of five damage states: none, slight, moderate, extensive, and complete. The slight and moderate damage states can be associated with a "green tag" from a post-earthquake building safety inspection which, in most cases, would allow residents to stay in their homes while repairs are completed. The extensive damage state can be associated with a "yellow tag" from a post-earthquake building safety inspection limiting its use until repairs are completed. The complete damage state can be associated with a "red tag" from a post-earthquake safety inspection which restricts all use of the building because it is unsafe to occupy until repairs are completed.
The 33 original Hazus occupancy classes were aggregated to align with available fire following earthquake data and to represent coarser categories of economic activities. In order to estimate burned area by occupancy class by census tract, the Hazus occupancy classes had to be assigned to one of seven burned building classifications used by Scawthorn and others (1996) after the 1994 Northridge earthquake: one- or two-family residential (RES1, RES2, RES3A), multi-family residential (RES3B, RES3C, RES3D, RES3E, RES3F), public roadways (not applicable), offices and power production/distribution (COM4), primary/secondary schools (EDU1, EDU2), commercial/restaurants (COM1, COM2, COM3, COM5, COM6, COM7, COM8, COM10), and other/unknown (RES4, RES5, RES6, COM9, IND1, IND2, IND3, IND4, IND5, IND6, AGR1, REL1, GOV1, GOV2).
Scawthorn and others, 1996
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 2:
The additional square footage damage from fire following earthquake was integrated with the square footage damages from the other earthquake hazards. To do this, first the burned square footage in Voronoi areas was converted to a burned square footage in census tracts by mapping the 2011 National Land Cover Database (NLCD) developed area within each Voronoi area of the Scawthorn analysis (Scawthorn, 2019). This was done in ESRI's ArcMap 10.4 software by:
(1) Overlaying 2000 vintage census tracts and calculating the proportion of each Voronoi developed area that intersects with each census tract; and
(2) Assuming the burned buildings are uniformly distributed in the developed area, burned building square footage for a census tract is the sum of the Voronoi developed area proportions in the tract multiplied by Voronoi burned building square footage.
The burned building square footage within census tracts was distributed to occupancy classes by creating a distribution of burned buildings across occupancy classes in the San Francisco Bay region using the occupancy distribution of burned buildings for fires following the 1994 Northridge earthquake published in Scawthorn and others (1996) as a reference. Most of the fires after the Northridge earthquake were confined to the buildings with ignitions. In contrast, the HayWired fire following earthquake analysis of ignitions, fire-fighting capacity, and water availability results in fire spread. In the absence of results for burned square footage of building occupancy classes, we used the Northridge earthquake proportion of burned buildings in each occupancy as the proportion of square footage burned in each occupancy. This assumption means that fires disproportionately spread into residential neighborhoods of single-family homes.
Scawthorn, 2019
NLCD developed land
Census tract boundaries, 2000
Scawthorn and others, 1996
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 3:
The allocation of burned square footage to census tracts and occupancy classes was conducted in two steps. First, the regional burned occupancy square footage of each occupancy classes is allocated across census tracts weighted by burned square footage and occupancy square footage in the census tract. This is done by calculating the following items:
(1) The regional burned occupancy square footage, which was calculated as the percent of burned square footage in an occupancy class multiplied by the total burned square footage for each census tract.
(2) The weight for burned square footage in a census tract, which was calculated as the proportion of burned square footage in the census tract.
(3) The weight for occupancy class square footage in a census tract, which was calculated as the proportion of the regional occupancy in the census tract.
The final allocation of the regional occupancy class burned area to a census tract was calculated as the product of the regional burned building square footage in an occupancy class and the weight for occupancy class square footage in the census tract.
Thus, the occupancy burned building area allocations to census tracts were weighted by burned building area and occupancy class building area in census tracts.
Scawthorn, 2019
NLCD developed land
Census tract boundaries, 2000
Scawthorn and others, 1996
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 4:
The second step adjusted these allocations back to the burned area assigned to the census tract by rescaling as follows:
(1) Divide the burned building square footage in a specific occupancy class allocated to the census tract by the sum of the burned building square footage in each occupancy class allocated to the census tract, and
(2) Multiply the result by the burned building square footage in the census tract.
Therefore, the uncertain burned occupancy distribution influenced, rather than determined, the allocations of burned area in a census tract to building occupancy classes.
Scawthorn, 2019
NLCD developed land
Census tract boundaries, 2000
Scawthorn and others, 1996
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 5:
Next, the burned building estimates were adjusted to reduce double-counting of structures destroyed by other earthquake hazards. To do so, it was assumed that there is independency between complete damage from earthquake hazards and complete damage from fire due to fire spread. Thus, the proportion of "burned rubble" in each occupancy class represents the proportion of buildings that are completely damaged by earthquake hazards multiplied by the proportion of burned buildings in each occupancy class.
In Microsoft Excel, this amount is subtracted from the amount of previously calculated burned occupancy square footage to yield additional square footage of complete damage from fire following earthquake. The additional complete damage from fire was transferred from other damage states (none, slight, moderate, and extensive) in proportion to the amount of square footage in each earthquake damage state in the census tract, meaning that exposed square footage in damage states not completely damaged is reduced to accommodate the increase in completely damaged square footage.
This procedure estimated that about 5 million square feet of 79 million square feet burned was already completely damaged by the earthquake hazards.
Square footage damaged by Hazus occupancy class and damage state, all hazards
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 6:
The integrated damage results needed to be aligned with 2010 population and economic census data. To align these results, as well as the original square footage damage resulting from earthquake hazards (ground shaking, landslide, and liquefaction), with 2010 vintage census data, the 2000 vintage tract-based damage results were converted into 2010 tract geographies. The conversion relied on official census relationship files to parse the relations. Housing units were used as weights when disaggregating the Hazus data. For example, where a 2000 tract was split into two smaller 2010 tracts, the building damages were distributed to the new tracts in proportion to their housing count rather than their share of the original tract area. This method has benefits and drawbacks. It is more accurate for housing but less representative of the commercial distribution because housing may be scarcer in commercial areas.
Census tract boundaries, 2010
Census tract relationship file
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 7:
Once square footage was redistributed to 2010 vintage census boundaries, the building counts and households affected could be estimated in Excel. These estimates were computed twice, once using the square footage damaged by earthquake hazards and once using the square footage damaged by all hazards.
The building counts were calculated by dividing the square footage for each tract's unique Hazus occupancy class and damage state by the average square footage for a structure in the occupancy class. For example, RES1 has an average square footage of 1,600. If a tract had 320,000 square feet classified as being extensively damaged, the companion extensively damaged building count would be 320,000 divided by 1,600, or 200 RES1 buildings. Please note that building counts, since they are estimated based on an occupancy group's average building size, will not be integer values.
Finally, the number of households was estimated based on the number of units in each residential Hazus occupancy class multiplied by the building count. For RES1 and RES2, this count was the same (these are single-family units and mobile homes). RES3A was multiplied by two (these are duplexes). RES3F was multiplied by 50 due to lack of additional information about the possible maximum number of units in a structure in this class. For the remaining RES3 occupancy classes, the building count was multiplied by the low and high unit count associated with each occupancy class (see below). The resulting household counts are provided as low and high estimates.
RES3B--3-4 units
RES3C--5-9 units
RES3D--10-19 units
RES3E--20-49 units
Please note that the numbers of households, since they are estimated based on the building count estimates, will not be integer values.
2017
Square footage damage, building count, and households affected by tract, occupancy class, and damage state methodology, step 8:
Finally, the 33 Hazus occupancy classes were each assigned to one of eight generalized occupancy groupings, three residential and five non-residential. The three residential building occupancy groupings are: single family/duplex dwellings (RES1, RES2, RES3A), multi-family dwellings (RES3B, RES3C, RES3D, RES3E, RES3F), and group living uses (RES5, RES6). Single family/duplex dwellings include single family, mobile home, and duplex housing that are either owner- or renter-occupied. Multi-family dwellings include structures with three or more housing units and also can be owner- or renter-occupied, such as apartment complexes and condominiums. The five non-residential building occupancy groupings are: retail and commercial (RES4, COM1, COM3, COM5, COM8, COM9, COM10), offices (COM4), industrial and warehouse (COM2, IND1, IND2, IND3, IND4, IND5, IND6), household-serving (COM6, COM7, REL1, GOV1, GOV2, EDU1, EDU2), and agricultural uses (AGR1). These classifications were used for summarizing results.
2017
CVI population distribution methodology, step 1:
The Association of Bay Area Governments (ABAG) Community Vulnerability Indicators (CVI) dataset was downloaded from http://resilience.abag.ca.gov/open-data/; block groups excluded from the CVI dataset (along with the total population in these block groups) were restored using 2010 block group data from https://www.census.gov. The attributes from the CVI dataset were saved into a separate Excel workbook for further analysis. The block group identifier, the total population, the county name, the presence/absence fields for each CVI class, and the count of CVI classes present in each block group (the CVI score) were retained; any other fields from the original CVI dataset were deleted from the Excel workbook. For block groups added back in to the dataset, all CVI classes and the CVI score were assigned zero.
The ten CVI classes used by ABAG are the following (CVI class abbreviation, followed by description and definition):
HCB: Housing cost burden--household monthly housing cost greater than 50 percent of gross monthly household income
TrnSpd: Transportation cost burden--households with high transportation cost
Renter: Home ownership--rental households
VLowIn: Household income--households with less than 50 percent of the region's Area Median Income (AMI)
NoHS: Education--people 25 years of age and older without a high school diploma
POC: Racial/cultural composition--non-white residents
NoVeh: Transit dependence--households without a vehicle
LimEng: Non-English speakers--households where no one 15 years of age or older speak English well
Under5: Age-Young children--people under 5 years of age
75Up: Age-Elderly--people 75 years of age and older
Higher percentages of populations or households meeting the above requirements lead a block group to qualify as vulnerable for a CVI class.
Community Vulnerability Indicators dataset, 2016
Stronger housing, safer communities technical report
Community indicators for flood risk
Census block group boundaries, 2010
Total population
2019
CVI population distribution methodology, step 2:
Each block group in the nine-county region was assigned to a class naming the economic subarea the block group is located in using ArcMap 10.5. For block groups outside the seven economic subareas, the class was defined as "Not in AOI". Block groups within the seven economic subareas were assigned to one of the following: Northern Alameda County, Central Alameda County, Southern Alameda County, Dublin-Pleasanton, Western Contra Costa County, Novato, or Vallejo. This process was repeated to identify block groups found within tracts classified as areas of concentrated damage, using damage due to (1) all earthquake hazards (ground shaking, landslide, liquefaction, fire) or (2) only earthquake hazards (ground shaking, landslide, liquefaction) in the seven economic subareas. The results were exported to an Excel-compatible worksheet and transferred to the data table resulting from step 1 using a lookup formula.
Economic subareas
Areas of concentrated damage, all hazards
Areas of concentrated damage, earthquake hazards
2019
CVI population distribution methodology, step 3:
The nature of the available data used prohibit isolating subgroups within a population and counting the number of people with different combinations of CVI indicators within a block group. It is only possible to consider how common different indicators are within a particular CVI score. To address this, a new adjusted population field was added in Excel for each of the ten CVI classes. For any CVI class where the block group was identified as meeting the criteria for inclusion, the adjusted population for the CVI class was assigned a value of the total population of the block group divided by the number of CVI classes present in the block group (the CVI score). The contribution of each indicator adds up to the total population in the specific subregion in the areas of concentrated damage with the CVI score.
For example, if three CVI classes (elderly population, renters, and very low income) were present in a block group with a population of 2100, a population of 700 would be assigned to the elderly population field, the renters field, and the very low income field. All other CVI classes would receive a population of zero. Summing across all ten CVI class fields for a specific block group would sum up to the total population for the block group.
2019
Additional vulnerable/mobile populations distribution methodology, step 1:
The American Community Survey (ACS) provides 1-year, 3-year, and 5-year estimates of populations and households across a wide range of categories and expands on the decennial Census population and household counts in between census years. Data for individual, unique demographic groups that could be considered vulnerable or otherwise not tied to an area were obtained from the U.S. Census Bureau American Factfinder web page (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml, to be replaced with https://data.census.gov/cedsci/?intcmp=aff_cedsci_banner). The 2012-2016 5-year ACS estimates were selected for this analysis since the 5-year estimate allowed for the finest spatial resolution (in this case, 2010 vintage block groups).
Six tables were downloaded from the American Factfinder web page:
B14007--School enrollment by detailed level of school for the population 3 years and over
B22010--Receipt of food stamps/SNAP in the past 12 months by disability status for households
B25007--Tenure by age of householder
B11005--Households by presence of people under 18 years by household type
B19037--Age of householder by household income in the past 12 months (in 2016 inflation-adjusted dollars)
B25063--Gross rent
Population of school age
Households by disability status
Households by age group for householder
Households by household type and presence of children
Households by age of householder and annual income
Renter-occupied households by rent amount
Median household income
Median gross rent
2018
Additional vulnerable/mobile populations distribution methodology, step 2:
Data from the six tables downloaded from the American Factfinder were opened in Microsoft Excel in order to extract the specific population and household subsets needed. All data were reported by 2010 Census block group, the smallest Census spatial unit with 5-year ACS data estimates available. Details for how each specific population or household subset were obtained are provided below:
(1) School-age children, extracted from table B14007, were estimated by summing all columns with counts of people in primary or secondary school (kindergarten through 12th grade).
(2) Households with a disabled member, extracted from table B22010, were estimated by summing the count of households with 1 or more persons with a disability either receiving food stamps or not receiving food stamps.
(3) Renter-occupied households with householders between 25 and 34, extracted from table B25007, were estimated by extracting the column for renter-occupied households with the householder aged between 25 and 34.
(4) Households with no children and do not identify as families, extracted from table B11005, were estimated by summing the columns for male-headed and female-headed non-family households with no people under 18 years present.
(5) Households with householders under 45 who earn an income higher than the median for the county they reside in, extracted from table B19037, were estimated by first getting the median household income for each county in the study region (found in table B19013). Once the median county income was added to the data in table B19037, household counts for all columns including or above the median county income for each block group were summed.
(6) Renter-occupied households with rent costs higher than the median for the county they reside in, extracted from table B19037, were estimated by first getting the median gross rent for each county in the study region (found in table B25064). Once the median county gross rent was added to the data in table B25063, household counts for all columns including or above the median county gross rent for each block group were summed.
2018
Additional vulnerable/mobile populations distribution methodology, step 3:
Once the specific population or household subsets were extracted by block group for the study region, a new field was added for each population or household subset and the percentage of each subset relative to the block group total was calculated in the new fields.
Percentages were based on the following universes (Census term for total base population or housing count relative to the table):
(1) Total population is the selected universe for school-age children
(2) Total occupied housing units is the selected universe for households with a disabled member
(3) Total occupied housing units is the selected universe for renter-occupied households with householders between 25 and 34
(4) Total occupied housing units is the selected universe for households with no children and do not identify as families
(5) Total occupied housing units is the selected universe for households with householders under 45 who earn an income higher than the median for the county they reside in
(6) Total renter-occupied housing units is the selected universe for renter-occupied households with rent costs higher than the median for the county they reside in
2018
Additional vulnerable/mobile populations distribution methodology, step 4:
Means and standard deviations were calculated in Microsoft Excel based on the block group data for each population or household subset's estimated percentages. One-half of the standard deviation added to the mean was used as the threshold value for determining whether a specific population or household subset in a block group was more highly concentrated than the average for the region; this was added as a new field for each population or household subset. This is consistent with the updated methodology used to assign thresholds to community vulnerability indicators by the San Francisco Bay Conservation and Development Commission (BCDC) Adapting to Rising Tides project (available at http://www.adaptingtorisingtides.org/maps-and-data-products/); the community vulnerability indicators methodology was originally implemented by the Association of Bay Area Governments (ABAG) Stronger Housing, Safer Communities project (available at http://resilience.abag.ca.gov/projects/stronger_housing_safer_communities_2015/).
The selected threshold values are listed below:
(1) 0.1835 is the threshold for school-age children
(2) 0.2614 is the threshold for households with a disabled member
(3) 0.1647 is the threshold for renter-occupied households with householders between 25 and 34
(4) 0.4101 is the threshold for households with no children and do not identify as families
(5) 0.2643 is the threshold for households with householders under 45 who earn an income higher than the median for the county they reside in
(6) 0.7591 is the threshold for renter-occupied households with rent costs higher than the median for the county they reside in
Please note that while the methodology from the BCDC Adapting to Rising Tides project was used for defining threshold values for the demographic data listed above, the data for that project use a different 5-year ACS dataset and, as such, are not directly comparable. In order to develop new demographic indicators compatible with the ABAG project (http://resilience.abag.ca.gov/projects/stronger_housing_safer_communities_2015/) or BCDC project (http://www.adaptingtorisingtides.org/maps-and-data-products), first check the available indicator dataset to determine the appropriate 5-year ACS dataset to query.
Stronger housing, safer communities technical report
Community indicators for flood risk
2019
Additional vulnerable/mobile populations distribution methodology, step 5:
Finally, each block group in the nine-county region was assigned to a class naming the economic subarea the block group is located in using a lookup formula in Microsoft Excel. For block groups outside the seven economic subareas, the class was defined as "Not in AOI". Block groups within the seven economic subareas were assigned to one of the following: Northern Alameda County, Central Alameda County, Southern Alameda County, Dublin-Pleasanton, Western Contra Costa County, Novato, or Vallejo. This process was repeated to identify block groups found within tracts classified as areas of concentrated damage, using damage due to (1) all earthquake hazards (ground shaking, landslide, liquefaction, fire) or (2) only earthquake hazards (ground shaking, landslide, liquefaction) in the seven economic subareas.
Areas of concentrated damage, all hazards
Areas of concentrated damage, earthquake hazards
Economic subareas
2019
Integrated building and contents economic losses methodology, step 1:
Using earthquake hazards (ground shaking, landslide, and liquefaction) and all hazards (ground shaking, landslide, liquefaction, and fire) estimates of square footage damaged by the HayWired scenario mainshock by census tract, Hazus building occupancy class, and Hazus damage state, the proportion of square footage in each damage state and occupancy class was calculated by county. The tract-level square footage damages were first aggregated to the county level in Microsoft Excel for each Hazus occupancy class. Fire damages were separated from earthquake hazards by subtracting the earthquake hazard complete damage square footage damaged from the all hazards complete damage square footage damaged for each building occupancy in each county.
Square footage damaged by Hazus occupancy class and damage state, all hazards
2017
Integrated building and contents economic losses methodology, step 2:
Each county's burned square footage in each Hazus occupancy class was divided by the total square footage for the same occupancy class in each county to get the proportion of the area burned at that scale. This proportion is used to estimate the economic impacts from building and contents losses resulting from fire. Fire is assumed to be complete damage, which is 100 percent of the building and content values. The building and content values of the building stock for each occupancy class in each county was multiplied by the proportion of the area burned in order to get the final value of building and contents damage caused by fire.
Square footage damaged by Hazus occupancy class and damage state, all hazards
Building and contents replacement values by census tract by occupancy class
2017
Integrated building and contents economic losses methodology, step 3:
The final total building and contents damage as a result of ground shaking, landslide, liquefaction, and fire was then established by adding together the building and contents damages estimated using Hazus and the additional fire damage estimates calculated in Excel.
Building damage by census tract by occupancy class
2017
HayWired_bldg_dmg_pcts.zip
ZIP archive containing two vector .SHP files and their accompanying metadata: HayWired_bldg_dmg_pcts_allHaz.shp and HayWired_bldg_dmg_pcts_eqHaz.shp.
Producer Defined
FID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
ESRI
Coordinates defining the features.
GEOID
U.S. Census Bureau census tract (2010 vintage) associated with each record.
Producer Defined
Lists U.S. Census Bureau census tract (2010 vintage) for each record.
The first two digits of the census tract identifier comprise the state's FIPS (Federal Information Processing Standard) code. The next three digits make up the county's FIPS code. The remaining six digits of the census tract designation are unique to each tract.
pAll
Percentage of all building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.636803
pIndWare
Percentage of industrial/warehouse non-residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.857143
pOff
Percentage of office non-residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.746079
pRetCom
Percentage of retail/commercial non-residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.758443
pHouseServ
Percentage of household-serving non-residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.748609
pAgUse
Percentage of agricultural use non-residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
1.000000
pSRes
Percentage of single family/duplex residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.568317
pMRes
Percentage of multi-family residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.933660
pComRes
Percentage of group living residential building stock classified as extensively or completely damaged.
Producer Defined
0.000000
0.700700
ACD_SRes
Defines whether the record is classified as an area of concentrated damage as a result of more than 20 percent of single family/duplex dwellings experiencing extensive or complete damage.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
ACD_MRes
Defines whether the record is classified as an area of concentrated damage as a result of more than 20 percent of multi-family dwellings experiencing extensive or complete damage.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
ACD_All
Defines whether the record is classified as an area of concentrated damage as a result of more than 20 percent of all building stock experiencing extensive or complete damage.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
HayWired_sqft_dmg_bldg_dmg_allHaz.txt
Tab-delimited text file.
Producer Defined
GEOID
U.S. Census Bureau census tract (2010 vintage) associated with each record.
Producer Defined
Lists U.S. Census Bureau census tract (2010 vintage) for each record.
The first two digits of the census tract identifier comprise the state's FIPS (Federal Information Processing Standard) code. The next three digits make up the county's FIPS code. The remaining six digits of the census tract designation are unique to each tract.
If using these data in conjunction with U.S. Census Bureau tract (2010 vintage) TIGER shapefiles, please ensure that the census tract identifiers are eleven characters in length (specifically that the leading 0 is maintained in the code). The field type must be text in order to associate the data in this field with the tract TIGER shapefile.
The values for each record represent the damaged building square footage, building count, or households affected by damage state for an individual occupancy in a given tract, meaning that each census tract is repeated 165 times (five times for each of 33 Hazus occupancy classes).
County
California county name associated with the record.
Producer Defined
California county name associated with the record. Will be one of 17 counties: Alameda, Contra Costa, Marin, Merced, Monterey, Napa, Sacramento, San Benito, San Francisco, San Joaquin, San Mateo, Santa Clara, Santa Cruz, Solano, Sonoma, Stanislaus, or Yolo. No part of any of these counties have been omitted from this dataset.
Occupancy
Hazus occupancy class associated with the record.
Producer Defined
RES1
Single family dwellings
Producer defined
RES2
Mobile homes/manufactured housing
Producer defined
RES3A
Multi-family dwellings, duplexes
Producer defined
RES3B
Multi-family dwellings, 3-4 units
Producer defined
RES3C
Multi-family dwellings, 5-9 units
Producer defined
RES3D
Multi-family dwellings, 10-19 units
Producer defined
RES3E
Multi-family dwellings, 20-49 units
Producer defined
RES3F
Multi-family dwellings, 50 or more units
Producer defined
RES4
Temporary lodging
Producer defined
RES5
Institutional dormitories
Producer defined
RES6
Nursing homes
Producer defined
COM1
Retail trade buildings (stores)
Producer defined
COM2
Wholesale trade buildings (warehouses)
Producer defined
COM3
Personal and repair services buildings (service stations/shops)
Producer defined
COM4
Professional and technical services buildings (offices)
Producer defined
COM5
Banks
Producer defined
COM6
Hospitals
Producer defined
COM7
Medical offices and clinics
Producer defined
COM8
Entertainment and recreation buildings (restaurants/bars)
Producer defined
COM9
Theaters
Producer defined
COM10
Parking structures (garages)
Producer defined
IND1
Heavy industrial facilities
Producer defined
IND2
Light industrial facilities
Producer defined
IND3
Food/drug/chemical processing facilities
Producer defined
IND4
Metal/mineral processing facilities
Producer defined
IND5
High technology facilities
Producer defined
IND6
Construction facilities
Producer defined
AGR1
Agricultural facilities
Producer defined
REL1
Churches and non-profit facilities
Producer defined
GOV1
General government services facilities (offices)
Producer defined
GOV2
Emergency response facilities (police/fire stations)
Producer defined
EDU1
Grade (K-12) schools
Producer defined
EDU2
Colleges and universities
Producer defined
ResNonRes
High-level occupancy group associated with the record.
Producer Defined
Residential
Residential building use, including single family/duplex, multi-family, and group living uses.
Producer defined
Non-residential
Non-residential building use, including industrial/warehouse, retail/commercial, offices, household-serving, and agricultural uses.
Producer defined
OccupancyGen
Generalized occupancy class associated with the record.
Producer Defined
Single family/duplex
Residential occupancy class comprised of single-family and duplex residences. Includes RES1, RES2, and RES3A Hazus occupancy classes.
Producer defined
Multi-family
Residential occupancy class comprised of multi-family residences. Includes RES3B, RES3C, RES3D, RES3E, and RES3F Hazus occupancy classes.
Producer defined
Group living
Residential occupancy class comprised of communal (group) residences. Includes RES5 and RES6 Hazus occupancy classes.
Producer defined
Industrial/warehouse
Non-residential occupancy class comprised of industrial and warehousing building uses. Includes COM2, IND1, IND2, IND3, IND4, IND5, and IND6 Hazus occupancy classes.
Producer defined
Retail/commercial
Non-residential occupancy class comprised of retail and other commercial building uses. Includes COM1, COM3, COM5, COM8, COM9, COM10, and RES4 Hazus occupancy classes.
Producer defined
Offices
Non-residential occupancy class comprised of office building uses. Includes COM4 Hazus occupancy classes.
Producer defined
Household-serving
Non-residential occupancy class comprised of household-serving (community-needs) building uses. Includes COM6, COM7, REL1, GOV1, GOV2, EDU1, and EDU2 Hazus occupancy classes.
Producer defined
Agricultural uses
Non-residential occupancy class comprised of agricultural building uses. Includes AGR1 Hazus occupancy classes.
Producer defined
DmgState
Hazus damage state associated with the record. Descriptions of damage states vary depending on the building type, and multiple building types combine to describe different occupancy classes. For more information, please refer to the Hazus-MH 2.1 technical manual (available at https://www.fema.gov/media-library-data/20130726-1820-25045-6286/hzmh2_1_eq_tm.pdf).
Producer Defined
None
No damage according to Hazus modeling results.
Producer defined
Slight
Slight damage according to Hazus modeling results.
Producer defined
Moderate
Moderate damage according to Hazus modeling results.
Producer defined
Extensive
Extensive damage according to Hazus modeling results.
Producer defined
Complete
Complete damage according to Hazus modeling results.
Producer defined
avgBldgSqft
Average building square footage used in Hazus for estimating the number of buildings assigned to a specific occupancy class.
Producer Defined
1,080
145,000
Square feet
sqft_eqHaz
Estimated building square footage impacted as a result of earthquake hazards (ground shaking, landslide, liquefaction) caused by the HayWired mainshock.
Producer defined
0
14,196,064
Square feet
bldgCnt_eqHaz
Estimated building count impacted as a result of earthquake hazards (ground shaking, landslide, liquefaction) caused by the HayWired mainshock. Estimates are based on average square footage for a specific occupancy type.
Producer defined
0.000
3,512.181
Number of buildings
hhLow_eqHaz
Estimated number of households (low-range value) impacted as a result of earthquake hazards (ground shaking, landslide, liquefaction) caused by the HayWired mainshock. Estimates are based on minimum number of units for a specific multi-unit residential occupancy type.
Producer defined
0.000
3,512.181
Number of households
hhHigh_eqHaz
Estimated number of households (high-range value) impacted as a result of earthquake hazards (ground shaking, landslide, liquefaction) caused by the HayWired mainshock. Estimates are based on maximum number of units for a specific multi-unit residential occupancy type.
Producer defined
0.000
3,512.181
Number of households
sqft_allHaz
Estimated building square footage impacted as a result of all hazards (ground shaking, landslide, liquefaction, fire) caused by the HayWired mainshock.
Producer defined
0
14,196,064
Square feet
bldgCnt_allHaz
Estimated building count impacted as a result of all hazards (ground shaking, landslide, liquefaction, fire) caused by the HayWired mainshock. Estimates are based on average square footage for a specific occupancy type.
Producer defined
0.000
3,512.181
Number of buildings
hhLow_allHaz
Estimated number of households (low-range value) impacted as a result of all hazards (ground shaking, landslide, liquefaction, fire) caused by the HayWired mainshock. Estimates are based on maximum number of units for a specific multi-unit residential occupancy type.
Producer defined
0.000
3,512.181
Number of households
hhHigh_allHaz
Estimated number of households (high-range value) impacted as a result of all hazards (ground shaking, landslide, liquefaction, fire) caused by the HayWired mainshock. Estimates are based on maximum number of units for a specific multi-unit residential occupancy type.
Producer defined
0.000
3,512.181
Number of households
HayWired_cvi_popExposure_allHaz.txt
Tab-delimited text file.
Producer Defined
GEOID
U.S. Census Bureau block group (2010 vintage) associated with each record.
Producer Defined
Lists U.S. Census Bureau block group (2010 vintage) for each record.
The first two digits of the block group identifier comprise the state's FIPS (Federal Information Processing Standard) code. The next three digits make up the county's FIPS code. The next six digits comprise the census tract identifier. The final digit is the block group identifier.
If using these data in conjunction with U.S. Census Bureau block group (2010 vintage) TIGER shapefiles, please ensure that the block group identifiers are twelve characters in length (specifically that the leading 0 is maintained in the code). The field type must be text in order to associate the data in this field with the block group TIGER shapefile.
Subarea
The economic subarea assigned to the record. Used to provide general geographic context for the most significant concentrations of census tracts with 20 percent or more extensive or complete building damage.
Producer Defined
Northern Alameda County
Block group is in the Northern Alameda County economic subarea, located in Alameda County.
Producer defined
Central Alameda County
Block group is in the Central Alameda County economic subarea, located in Alameda County.
Producer defined
Southern Alameda County
Block group is in the Southern Alameda County economic subarea, located in Alameda County.
Producer defined
Dublin-Pleasanton
Block group is in the Dublin-Pleasanton economic subarea, located in Alameda County.
Producer defined
Western Contra Costa County
Block group is in the Western Contra Costa County economic subarea, located in Contra Costa County.
Producer defined
Novato
Block group is in the Novato economic subarea, located in Marin County.
Producer defined
Vallejo
Block group is in the Vallejo economic subarea, located in Solano County.
Producer defined
Not in AOI
Block group is not in any defined economic subarea.
Producer defined
ACD_allHaz
Defines whether the record is classified as an area of concentrated damage as a result of damage caused by all HayWired earthquake hazards: ground shaking, landslides, liquefaction, and fire following earthquake.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
ACD_eqHaz
Defines whether the record is classified as an area of concentrated damage as a result of damage caused by HayWired earthquake hazards: ground shaking, landslides, and liquefaction.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
CountyName
California county name associated with the record.
Producer Defined
California county name associated with the record. Will be one of nine counties: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, or Sonoma.
Total_Pop
Total population associated with the record.
Producer Defined
0
9,811
People
NoHS_ind
Identifier showing whether the record is classified as having a high concentration of population age 25 or older without a high school diploma. Threshold value (estimated using the regional mean plus one-half standard deviation) is 19 percent.
Producer Defined
0
Low concentration of population age 25 or older without a high school diploma.
Producer defined
1
High concentration of population age 25 or older without a high school diploma.
Producer defined
POC_ind
Identifier showing whether the record is classified as having a high concentration of population identifying as non-white. Threshold value (estimated using the regional mean plus one-half standard deviation) is 68 percent.
Producer Defined
0
Low concentration of population identifying as non-white.
Producer defined
1
High concentration of population identifying as non-white.
Producer defined
PopUnder5_ind
Identifier showing whether the record is classified as having a high concentration of population under the age of 5. Threshold value (estimated using the regional mean plus one-half standard deviation) is 8 percent.
Producer Defined
0
Low concentration of population under the age of 5.
Producer defined
1
High concentration of population under the age of 5.
Producer defined
Pop75Up_ind
Identifier showing whether the record is classified as having a high concentration of population age 75 and older. Threshold value (estimated using the regional mean plus one-half standard deviation) is 9 percent.
Producer Defined
0
Low concentration of population age 75 and older.
Producer defined
1
High concentration of population age 75 and older.
Producer defined
HCB_ind
Identifier showing whether the record is classified as having a high concentration of households spending more than 50 percent of their income on housing. Threshold value (estimated using the regional mean plus one-half standard deviation) is 35 percent for renters and 19 percent for homeowners.
Producer Defined
0
Low concentration of households spending more than 50 percent of their income on housing.
Producer defined
1
High concentration of households spending more than 50 percent of their income on housing.
Producer defined
TrnSpnd_ind
Identifier showing whether the record is classified as having a high concentration of households with high transportation costs. Threshold value (estimated using the regional mean plus one-half standard deviation) is 18 percent.
Producer Defined
0
Low concentration of households with high transportation costs.
Producer defined
1
High concentration of households with high transportation costs.
Producer defined
Renter_ind
Identifier showing whether the record is classified as having a high concentration of households occupied by renters. Threshold value (estimated using the regional mean plus one-half standard deviation) is 55 percent.
Producer Defined
0
Low concentration of households occupied by renters.
Producer defined
1
High concentration of households occupied by renters.
Producer defined
VLowIn_ind
Identifier showing whether the record is classified as having a high concentration of households with income less than 50 percent of the area's median income. Threshold value (estimated using the regional mean plus one-half standard deviation) is 33 percent.
Producer Defined
0
Low concentration of households with income less than 50 percent of the area's median income.
Producer defined
1
High concentration of households with income less than 50 percent of the area's median income.
Producer defined
LimEng_ind
Identifier showing whether the record is classified as having a high concentration of households without a proficient English speaker over the age of 14. Threshold value (estimated using the regional mean plus one-half standard deviation) is 14 percent.
Producer Defined
0
Low concentration of households without a proficient English speaker over the age of 14.
Producer defined
1
High concentration of households without a proficient English speaker over the age of 14.
Producer defined
NoVeh_ind
Identifier showing whether the record is classified as having a high concentration of households without a vehicle. Threshold value (estimated using the regional mean plus one-half standard deviation) is 15 percent.
Producer Defined
0
Low concentration of households without a vehicle.
Producer defined
1
High concentration of households without a vehicle.
Producer defined
CVI_scr
The Community Vulnerability Indicator (CVI) score associated with the record. The CVI score is the count of CVI classes identified as high concentration.
Producer Defined
0
9
NoHS_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of population age 25 or older without a high school diploma.
Producer Defined
0.000
3,847.000
People
POC_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of population identifying as non-white.
Producer Defined
0.000
4,548.000
People
PopUnder5_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of population under the age of 5.
Producer Defined
0.000
3,270.333
People
Pop75Up_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of population age 75 and older.
Producer Defined
0.000
6,065.000
People
HCB_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of households spending more than 50 percent of their income on housing.
Producer Defined
0.000
4,439.000
People
TrnSpnd_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of households with high transportation costs.
Producer Defined
0.000
5,112.000
People
Renter_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of households occupied by renters.
Producer Defined
0.000
3,270.333
People
VLowIn_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of households with income less than 50 percent of the area's median income.
Producer Defined
0.000
2,753.000
People
LimEng_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of households without a proficient English speaker over the age of 14.
Producer Defined
0.000
2,874.000
People
NoVeh_pop_adj
Total population adjusted using the record's CVI score, assigned to the indicator for high concentration of households without a vehicle.
Producer Defined
0.000
2,155.250
People
HayWired_ACS_16_5YR_YngMob_allHaz.txt
Tab-delimited text file.
Producer Defined
GEOID
U.S. Census Bureau block group (2010 vintage) associated with each record.
Producer Defined
Lists U.S. Census Bureau block group (2010 vintage) for each record.
The first two digits of the block group identifier comprise the state's FIPS (Federal Information Processing Standard) code. The next three digits make up the county's FIPS code. The next six digits comprise the census tract identifier. The final digit is the block group identifier.
If using these data in conjunction with U.S. Census Bureau block group (2010 vintage) TIGER shapefiles, please ensure that the block group identifiers are twelve characters in length (specifically that the leading 0 is maintained in the code). The field type must be text in order to associate the data in this field with the block group TIGER shapefile.
Subarea
The economic subarea assigned to the record. Used to provide general geographic context for the most significant concentrations of census tracts with 20 percent or more extensive or complete building damage.
Producer Defined
Northern Alameda County
Block group is in the Northern Alameda County economic subarea, located in Alameda County.
Producer defined
Central Alameda County
Block group is in the Central Alameda County economic subarea, located in Alameda County.
Producer defined
Southern Alameda County
Block group is in the Southern Alameda County economic subarea, located in Alameda County.
Producer defined
Dublin-Pleasanton
Block group is in the Dublin-Pleasanton economic subarea, located in Alameda County.
Producer defined
Western Contra Costa County
Block group is in the Western Contra Costa County economic subarea, located in Contra Costa County.
Producer defined
Novato
Block group is in the Novato economic subarea, located in Marin County.
Producer defined
Vallejo
Block group is in the Vallejo economic subarea, located in Solano County.
Producer defined
Not in AOI
Block group is not in any defined economic subarea.
Producer defined
ACD_allHaz
Defines whether the record is classified as an area of concentrated damage as a result of damage caused by all HayWired earthquake hazards: ground shaking, landslides, liquefaction, and fire following earthquake.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
ACD_eqHaz
Defines whether the record is classified as an area of concentrated damage as a result of damage caused by HayWired earthquake hazards: ground shaking, landslides, and liquefaction.
Producer Defined
N
Area of less concentrated damage
Producer defined
Y
Area of concentrated damage
Producer defined
County
California county name associated with the record.
Producer Defined
California county name associated with the record. Will be one of 17 counties: Alameda, Contra Costa, Marin, Merced, Monterey, Napa, Sacramento, San Benito, San Francisco, San Joaquin, San Mateo, Santa Clara, Santa Cruz, Solano, Sonoma, Stanislaus, or Yolo.
Total_pop
Total population associated with the record.
Producer Defined
0
16,867
People
Total_OHU
Total number of occupied housing units associated with the record.
Producer Defined
0
5,254
Occupied housing units
Total_RO_OHU
Total number of renter-occupied housing units associated with the record.
Producer Defined
0
3,075
Renter-occupied housing units
SchAge_pop
Total population of school age (kindergarten through 12th grade) associated with the record.
Producer Defined
0
4,281
People
SchAge_pct
Percentage of school-age population associated with the record, calculated by dividing the total population of school age (kindergarten through 12th grade) by the total population for the record.
Producer Defined
0.0000
0.4557
SchAge_ind
Identifier showing whether the record is classified as having a high concentration of population of school age (kindergarten through 12th grade). Threshold value (estimated using the block-group mean plus one-half standard deviation) is 0.1835.
Producer Defined
0
Low concentration of population of school age.
Producer defined
1
High concentration of population of school age.
Producer defined
Disab_OHU
Total number of occupied housing units with at least one resident identifying as disabled associated with the record.
Producer Defined
0
1,255
Occupied housing units
Disab_pct
Percentage of occupied housing units with at least one disabled member associated with the record, calculated by dividing the total number of occupied housing units with at least one resident identifying as disabled by the total number of occupied housing units for the record.
Producer Defined
0.0000
0.8095
Disab_ind
Identifier showing whether the record is classified as having a high concentration of occupied housing units with at least one member identifying as disabled. Threshold value (estimated using the block-group mean plus one-half standard deviation) is 0.2614.
Producer Defined
0
Low concentration of occupied housing units with at least one member identifying as disabled.
Producer defined
1
High concentration of occupied housing units with at least one member identifying as disabled.
Producer defined
YngRnt_OHU
Total number of renter-occupied housing units with householders between age 25 and 34 associated with the record.
Producer Defined
0
1,710
Occupied housing units
YngRnt_pct
Percentage of renter-occupied housing units with householders between 25 and 34 associated with the record, calculated by dividing the total number of renter-occupied housing units with householders between age 25 and 34 by the total number of occupied housing units for the record.
Producer Defined
0.0000
1.0000
YngRnt_ind
Identifier showing whether the record is classified as having a high concentration of renter-occupied housing units with householders between age 25 and 34. Threshold value (estimated using the block-group mean plus one-half standard deviation) is 0.1647.
Producer Defined
0
Low concentration of renter-occupied housing units with householders between age 25 and 34.
Producer defined
1
High concentration of renter-occupied housing units with householders between age 25 and 34.
Producer defined
NKdNFam_OHU
Total number of occupied housing units not identifying as families and have no children associated with the record.
Producer Defined
0
2,505
Occupied housing units
NKdNFam_pct
Percentage of occupied housing units with no children and are not families associated with the record, calculated by dividing the total number of occupied housing units not identifying as families and have no children by the total number of occupied housing units for the record.
Producer Defined
0.0000
1.0000
NKdNFam_ind
Identifier showing whether the record is classified as having a high concentration of households not identifying as families and have no children. Threshold value (estimated using the block-group mean plus one-half standard deviation) is 0.4101.
Producer Defined
0
Low concentration of households not identifying as families and have no children.
Producer defined
1
High concentration of households not identifying as families and have no children.
Producer defined
YngHiInc_OHU
Total number of occupied housing units with householders under age 45 earning an income greater than the county median associated with the record.
Producer Defined
0
2,474
Occupied housing units
YngHiInc_pct
Percentage of young householders earning above-county-median income associated with the record, calculated by dividing the total number of occupied housing units with householders under age 45 earning an income higher than the county median by the total number of occupied housing units for the record.
Producer Defined
0.0000
1.0000
YngHiInc_ind
Identifier showing whether the record is classified as having a high concentration of occupied housing units with householders under age 45 earning an income higher than the county median. Threshold value (estimated using the block-group mean plus one-half standard deviation) is 0.2643.
Producer Defined
0
Low concentration of occupied housing units with householders under age 45 earning an income higher than the county median.
Producer defined
1
High concentration of occupied housing units with householders under age 45 earning an income higher than the county median.
Producer defined
HiRnt_RO_OHU
Total number of renter-occupied households paying monthly rent higher than the county median associated with the record.
Producer Defined
0
2,530
Renter-occupied housing units
HiRnt_pct
Percentage of households paying rent higher than the county median associated with the record, calculated by dividing the total number of renter-occupied households paying rent higher than the county median by the total number of renter-occupied households for the record.
Producer Defined
0.0000
1.0000
HiRnt_ind
Identifier showing whether the record is classified as having a high concentration of renter-occupied households paying monthly rent higher than the county median. Threshold value (estimated using the block-group mean plus one-half standard deviation) is 0.7591.
Producer Defined
0
Low concentration of renter-occupied households paying rent higher than the county median.
Producer defined
1
High concentration of renter-occupied households paying rent higher than the county median.
Producer defined
YngMob_scr
Sum of the number of indicator demographics associated with young and mobile populations where high concentrations are present for the record. Indicator demographics used in this are: renter-occupied housing units with householders between age 25 and 34, occupied housing units with householders under age 45 earning an income higher than the county median, renter-occupied housing units with monthly rent higher than the county median, and occupied housing units not identifying as families and have no children.
Producer Defined
0
4
HayWired_bldg_content_losses_allHaz.txt
Tab-delimited text file.
Producer Defined
County
California county name associated with the record.
Producer Defined
California county name associated with the record. Will be one of 17 counties: Alameda, Contra Costa, Marin, Merced, Monterey, Napa, Sacramento, San Benito, San Francisco, San Joaquin, San Mateo, Santa Clara, Santa Cruz, Solano, Sonoma, Stanislaus, or Yolo. No part of any of these counties have been omitted from this dataset.
Occupancy
Hazus occupancy class associated with the record.
Producer Defined
RES1
Single family dwellings
Producer defined
RES2
Mobile homes/manufactured housing
Producer defined
RES3A
Multi-family dwellings, duplexes
Producer defined
RES3B
Multi-family dwellings, 3-4 units
Producer defined
RES3C
Multi-family dwellings, 5-9 units
Producer defined
RES3D
Multi-family dwellings, 10-19 units
Producer defined
RES3E
Multi-family dwellings, 20-49 units
Producer defined
RES3F
Multi-family dwellings, 50 or more units
Producer defined
RES4
Temporary lodging
Producer defined
RES5
Institutional dormitories
Producer defined
RES6
Nursing homes
Producer defined
COM1
Retail trade buildings (stores)
Producer defined
COM2
Wholesale trade buildings (warehouses)
Producer defined
COM3
Personal and repair services buildings (service stations/shops)
Producer defined
COM4
Professional and technical services buildings (offices)
Producer defined
COM5
Banks
Producer defined
COM6
Hospitals
Producer defined
COM7
Medical offices and clinics
Producer defined
COM8
Entertainment and recreation buildings (restaurants/bars)
Producer defined
COM9
Theaters
Producer defined
COM10
Parking structures (garages)
Producer defined
IND1
Heavy industrial facilities
Producer defined
IND2
Light industrial facilities
Producer defined
IND3
Food/drug/chemical processing facilities
Producer defined
IND4
Metal/mineral processing facilities
Producer defined
IND5
High technology facilities
Producer defined
IND6
Construction facilities
Producer defined
AGR1
Agricultural facilities
Producer defined
REL1
Churches and non-profit facilities
Producer defined
GOV1
General government services facilities (offices)
Producer defined
GOV2
Emergency response facilities (police/fire stations)
Producer defined
EDU1
Grade (K-12) schools
Producer defined
EDU2
Colleges and universities
Producer defined
OccupancyGen
Generalized occupancy class associated with the record.
Producer Defined
Single family/duplex
Residential occupancy class comprised of single-family and duplex residences. Includes RES1, RES2, and RES3A Hazus occupancy classes.
Producer defined
Multi-family
Residential occupancy class comprised of multi-family residences. Includes RES3B, RES3C, RES3D, RES3E, and RES3F Hazus occupancy classes.
Producer defined
Group living
Residential occupancy class comprised of communal (group) residences. Includes RES5 and RES6 Hazus occupancy classes.
Producer defined
Industrial/warehouse
Non-residential occupancy class comprised of industrial and warehousing building uses. Includes COM2, IND1, IND2, IND3, IND4, IND5, and IND6 Hazus occupancy classes.
Producer defined
Retail/commercial
Non-residential occupancy class comprised of retail and other commercial building uses. Includes COM1, COM3, COM5, COM8, COM9, COM10, and RES4 Hazus occupancy classes.
Producer defined
Offices
Non-residential occupancy class comprised of office building uses. Includes COM4 Hazus occupancy classes.
Producer defined
Household-serving
Non-residential occupancy class comprised of household-serving (community-needs) building uses. Includes COM6, COM7, REL1, GOV1, GOV2, EDU1, and EDU2 Hazus occupancy classes.
Producer defined
Agricultural uses
Non-residential occupancy class comprised of agricultural building uses. Includes AGR1 Hazus occupancy classes.
Producer defined
BldgDmg_comb
Estimated building damage, in thousands of dollars (2005 vintage), as a result of earthquake hazards (ground shaking, landslide, liquefaction) caused by the HayWired mainshock.
Producer Defined
0.0000
6,937,537.3782
Thousands of dollars (2005 vintage)
ContentDmg_comb
Estimated building contents damage, in thousands of dollars (2005 vintage), as a result of earthquake hazards (ground shaking, landslide, liquefaction) caused by the HayWired mainshock.
Producer Defined
0.0000
1,627,057.3215
Thousands of dollars (2005 vintage)
BldgDmg_fire
Estimated building damage, in thousands of dollars (2005 vintage), as a result of fire following the HayWired mainshock.
Producer Defined
0.0000
3,630,245.0533
Thousands of dollars (2005 vintage)
ContentDmg_fire
Estimated building contents damage, in thousands of dollars (2005 vintage), as a result of fire following the HayWired mainshock.
Producer Defined
0.0000
1,466,574.3330
Thousands of dollars (2005 vintage)
BldgContentDmg_all
Estimated building and contents damage, in thousands of dollars (2005 vintage), as a result of all earthquake hazards (ground shaking, landslide, liquefaction, fire) caused by the HayWired mainshock.
Producer Defined
0.0000
13,661,414.0860
Thousands of dollars (2005 vintage)
U.S. Geological Survey
GS ScienceBase
mailing address
Denver Federal Center, Building 810, Mail Stop 302
Denver
CO
80225
United States
1-888-275-8747
sciencebase@usgs.gov
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
Digital Data
https://doi.org/10.5066/P94Z8BOZ
None
20200818
Jamie L Jones
U.S. Geological Survey, SOUTHWEST REGION
Geographer
mailing address
350 North Akron Road
Moffett Field
CA
94035
US
650-439-2425
jamiejones@usgs.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998