Bridge condition is measured by the share of bridges and overpasses flagged as structurally deficient, weighted by bridge deck area to capture the relative size of the bridge. In short, this measure reflects the integrity of regional bridges and overpasses. Structural deficiency is identified based on the condition of the structure as assessed by engineering professionals (as opposed to just the roadway surface). The dataset includes metropolitan area, regional, county, and individual bridge tables and comes from the Federal Highway Administration’s National Bridge Inventory (1992-2012).
Data Center
Data Center
Explore a wide variety of public datasets related to transportation, land use, the economy, and the environment. Select one or all of the datasets aggregated and refined for the Vital Signs initiative—then download them and start your own analyses of Bay Area trends!
Transportation
Commute mode choice, also known as commute mode share, refers to the mode of transportation that a commuter uses to travel to work, such as driving alone, biking, carpooling or taking transit. The dataset includes metropolitan area, regional, county, city and census tract tables by place of residence and by place of employment. The dataset comes from Bay Area Census (1960 to 2000) and the U.S. Census Bureau’s American Community Survey (2006 to 2014).
Commute patterns, more commonly referred to as county-to-county commute flows, reflect the number of individuals traveling within and between various counties for commuting purposes. The dataset includes county tables and comes from the U.S. Census Bureau’s Census Transportation Planning Package (2010).
Commute time refers to the number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city and census tract tables by place of residence and by place of employment. The dataset comes from Bay Area Census (1980 to 2000) and the U.S. Census Bureau’s American Community Survey (2006 to 2014).
Daily miles traveled, commonly referred to as vehicle miles traveled (VMT), reflects the total and per-person number of miles traveled in personal vehicles on a typical weekday. The dataset includes metropolitan area, regional and county tables. The data comes from the Highway Performance Monitoring System (HPMS) developed by the Federal Highway Administration and Caltrans, as summarized in the California Public Road Data (2001-2013) and the Highway Statistics Series (2013).
Highway pavement condition, measured by the share of highway lane-miles flagged as “distressed” by Caltrans, reflects the regional pavement quality on the highway system. The dataset includes regional and road segment tables and comes from Caltrans’ State of the Pavement reporting (2000-2013) and from Caltrans’ Highway Pavement Condition Inventory (2013).
Miles traveled in congestion reflects the share of miles traveled on regional freeways in congestion for a typical weekday; it is often referred to as the congested share of freeway miles driven (also referred to as vehicle miles traveled, or VMT). Congestion is defined as speeds less than 35 mph, approximately the speed at which freeway throughput is maximized. The dataset includes regional and county data tables and comes from a MTC/Iteris analysis of Caltrans Performance Monitoring System (PeMS) freeway data (2004-2015).
Street pavement condition, more commonly referred to as the pavement condition index (PCI), reflects the quality of pavement on local streets and roads in the region. Calculated using a three-year moving average, PCI ranges from zero (failed) to 100 (brand-new) and has been used as a regional indicator of pavement preservation for over a decade. The dataset includes regional, county, city and road segment tables. The pavement condition data comes from MTC’s StreetSaver system (2003-2015).
Time spent in traffic congestion – also known as congested delay – refers to the number of minutes weekday travelers spend in congested conditions in which freeway speeds drop below 35 mph. Total delay, a companion measure, includes both congested delay and all other delay in which speeds are below the posted speed limit. The dataset includes metropolitan area, regional and freeway corridor tables. It comes from MTC/Iteris analysis of INRIX traffic congestion data (2015), the Texas Transportation Institute Urban Mobility Scorecard (2014) and Texas Transportation Institute unpublished analysis of severe congestion delay (2011), and population/employment data from the California Department of Finance (1998-2015), California Employment Development Department (1998-2015), U.S. Census Bureau (2015) and U.S. Bureau of Labor Statistics (2015).
Traffic volumes at regional gateways refers to the number of vehicles crossing county boundaries on a typical day to enter or exit the nine-county San Francisco Bay Area. The dataset includes county and facility flow tables and comes from Caltrans Annual Traffic Volume Reports (1992-2014).
Transit asset condition reflects the relative age of the region’s transit infrastructure. It is measured in terms of the percentage of transit assets beyond their expected useful life, as gauged by federal standards. In order to incorporate assets of vastly different monetary values (i.e. a bus stop versus a subway station), this percentage is weighted based on the cost to replace each asset. The dataset includes operator tables both for overall conditions and asset category conditions. The data comes from MTC's Regional Transit Capital Inventory (2015).
Transit ridership refers to the number of passenger boardings on public transportation, which includes buses, rail systems and ferries. The dataset includes metropolitan area, regional, mode and operator tables for both weekday total and annual per-capita boardings. The data comes from the Federal Transit Administration's National Transit Database (1991-2014), the California Department of Finance (1991-2014) and the U.S. Census Bureau (1991-2014).
Transit system efficiency refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. The data comes from the Federal Transit Administration's National Transit Database (2003-2014) and the Bureau of Labor Statistics (2003-2014).
Transportation planners quantify the travel time reliability of a given route by means of a buffer time index (BTI). BTI is a measure of the amount of time, over and above the average travel time, that a driver would need to budget to ensure on-time arrival at the desired destination, with a 95 percent confidence rate. BTI is expressed as a fraction of the average travel time – the lower the BTI, the more reliable the trip. This measure focuses solely on the regional freeway system, as no comparable data is available on the local street network or transit network. The dataset includes regional and freeway corridor tables and comes from MTC analysis of INRIX traffic congestion data (2010, 2014-2015) and the California Department of Transportation (2010, 2014-2015).
Land and People
Greenfield development is the change in the extent of urban and built-up lands of a given geographical area. Developed lands have a building density of at least 1 unit to 1.5 acres. The dataset includes greenfield development estimates for Bay Area counties, cities, and unincorporated areas and comes from the California Department of Conservation (1990 to 2012). The dataset also includes greenfield development estimates by metropolitan area developed by MTC using data from the U.S. Census Bureau (2000 to 2010).
Housing growth is measured in terms of number of units for which cities issue permits throughout a given year. The dataset includes housing permit numbers, separated into single-family and multi-family units, for Bay Area counties, cities, and unincorporated areas and comes from the California Housing Foundation and the Construction Industry Research Board (1967 to 2015). The dataset also includes housing permit numbers by metropolitan area, which come from the U.S. Census Bureau’s Building Permit Survey (1988 to 2015).
Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. The dataset includes employment estimates for Bay Area counties and sub-county areas and comes from the California Employment Development Department (1990 to 2015) and the U.S. Census Bureau’s Longitudinal Employer-Household Dynamics Program (2005-2014). The dataset also includes employment estimates by metropolitan area from the U.S. Bureau of Labor Statistics (1990 to 2015).
Population is a measurement of the number of residents that live in a given geographical area. The dataset includes population estimates for Bay Area counties, cities, census tracts, and priority development areas. The dataset comes from the California Department of Finance (1960-2015), Brown University’s Longitudinal Tract Database (1970-2010), and the U.S. Census Bureau’s American Community Survey (2014). The dataset also includes population estimates by metropolitan area from the U.S. Census Bureau’s Decennial Census and Intercensal Estimates (1960-2015).
Environment
Bay restoration refers to the acreage of San Francisco Bay. This measure reflects either the Bay’s expansion from restoration projects (such as wetland restorations) or contraction from projects that fill the Bay to create new land for development. This measure is a key indicator of Bay conservation efforts, as well as nearby development activities. The dataset includes acreage of Bay restoration or fill on a regional level and comes from the San Francisco Bay Conservation and Development Commission (1969-2014).
Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. Fatalities are measured as an aggregate number (total fatalities) and as a rate (fatalities per 100,000 residents and fatalities per 100 million vehicle miles traveled). The dataset includes fatality totals and rates for the region and counties, as well as individual collision data; the data comes from the California Highway Patrol and the University of California, Berkeley (2001-2012). It also includes metropolitan area data from the National Highway Safety Administration (2012).
Greenhouse gas emissions refer to carbon dioxide and other chemical compounds that contribute to global climate change. Vital Signs tracks greenhouse gas emissions linked to on-road motor vehicle transportation, using fuel sales to retail customers as a source of monitoring data. This measure helps track progress towards achieving our region’s per-capita greenhouse gas target under Senate Bill 375, which is focused on emissions from cars and light-duty trucks. This dataset includes emissions estimates on the county level and comes from the California Energy Commission (2012).
Injuries from crashes refers to serious but not fatal injuries sustained in a collision. The California Highway Patrol classifies a serious injury as any combination of the following: broken bones; dislocated or distorted limbs; severe lacerations; skull, spinal, chest or abdominal injuries that go beyond visible injuries; unconsciousness at or when taken from the scene; or severe burns. Injuries are measured as an aggregate number (total injuries) and as a rate (injuries per 100,000 residents and injuries per 100 million vehicle miles traveled). The dataset includes injury totals and rates for the region and counties, as well as individual collision data; the data comes from the California Highway Patrol and the University of California, Berkeley (2001-2012).
Ozone concentrations refer to the quantity of ozone (O3) molecules in the air we breathe. In the Bay Area, ozone is measured by over a dozen monitoring stations that record hourly concentrations used to determine compliance with national standards. These hourly data are used to calculate eight-hour peak ozone levels for the fourth-worst day of the year, the most common indicator of ozone performance. This dataset includes regional and sensor-specific concentrations and comes from the Bay Area Air Quality Management District (1970-2015). It also includes metropolitan area data from the Environmental Protection Agency (2015).
Particulate matter concentrations refer to the amount of fine particulate matter (PM2.5) in the air we breathe. Fine particulate matter particles are very small, measuring less than 2.5 microns (μg) or 1/25 the width of a human hair – yet they pose a significant health risk. Air quality standards for particulate matter are expressed in two ways: the annual average (reflecting average concentrations during the course of a given year) and the 24-hour average (reflecting worst-case conditions in a given year). This dataset includes regional and sensor-specific concentrations and comes from the Bay Area Air Quality Management District (1999-2015). It also includes metropolitan area data from the Environmental Protection Agency (2015).
Vulnerability to sea level rise refers to the share of the historical and current Bay Area population located in areas at risk from forecasted sea level rise over the coming decades. Given that there are varying forecasts for the heightened high tides (i.e., mean highest high water mark), projected sea level impacts are presented for six scenarios ranging from a one foot rise to six feet. A neighborhood is considered vulnerable to sea level rise when at least 10 percent of its land area is forecasted to be inundated by peak high tides in the coming years. The dataset includes at-risk population and population share data for the region, counties, and neighborhoods from the San Francisco Bay Conservation and Development Commission (2015) and the U.S. Census Bureau (1990-2012).
Economy
Airport activity refers to the number of passenger boardings at Bay Area commercial airports and to the quantity of goods – measured in tons – that arrive in the region as air cargo. This dataset includes passenger and freight data for Bay Area airports, as well as passenger data for metropolitan areas, from the Federal Aviation Administration (2001-2013).
Economic output is measured by the total and per-capita gross regional product and refers to the value of goods and services generated by workers and companies in a region. This dataset includes metropolitan area data (both aggregate and disaggregate) and comes from the Bureau of Economic Analysis (2001-2013).
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city. The dataset includes home price data for the region, counties, cities, and tracts from Redfin (1990-2014), as well as metropolitan area data from Zillow (1998-2014).
Housing affordability refers to the share of household income expended on housing and can be broken down by income level and tenure (renter versus owner). It captures the burden of housing costs on a household budget, with those households expending more than 35 percent of income on housing considered to be excessively burdened. The dataset includes affordability data for the region and for counties from the U.S. Census Bureau (1980-2013); for year 2013, the data is broken down by income bracket. It also includes metropolitan area data from the U.S. Census Bureau (1980-2013).
Income reflects the median earnings of individuals and households from employment. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis. The dataset includes income data by place of residence and by place of employment from the U.S. Census Bureau for the region, counties, cities, and tracts (1970-2013 for region, counties, and cities; 2013 only for tracts). It also includes data by metropolitan area from the U.S. Census Bureau (1970-2013).
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers. The dataset includes job and job growth data for the Bay Area and its counties from the California Employment Development Department (1990-2013). The dataset also includes job data by metropolitan area from the Bureau of Labor Statistics (2013).
Labor force participation refers to the share of the adult population that is either employed or seeking employment, regardless of whether the employment is full-time or part-time. The dataset includes regional, county, city, and tract data from the U.S. Census Bureau (1980-2013 for region and county; 2013 only for city and tract). It also includes metropolitan area data from the U.S. Census Bureau’s American Community Survey (2013).
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels. This dataset includes poverty data for metropolitan areas, counties, cities, and tracts and comes from the U.S. Census Bureau (1980-2013).
Rent refers to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. The dataset includes rent payment data for the region, counties, cities, and tracts from the U.S. Census Bureau (1970-2013 for region, counties, and cities; 2010-2013 for tracts). It also includes metropolitan area rent payment data from the U.S. Census Bureau (1970-2013).
Seaport activity refers to the quantity of goods moved into or out of the region through seaports. Seaport activity is measured at major ports by the number of shipping containers moved; these are known as twenty-foot equivalent units (TEUs). This dataset includes freight data for the Bay Area’s primary seaport from the Port of Oakland (1990-2014). It also includes freight data for other ports in major metropolitan areas from the American Association of Port Authorities (1990-2013).
Unemployment refers to the share of the labor force that is not currently employed full-time or part-time and reflects the strength of the regional employment market. The dataset includes unemployment rate data for the Bay Area, as well as counties and cities, from the California Employment Development Department (1990-2013). The dataset also includes job data by metropolitan area from the Bureau of Labor Statistics (1990-2014).