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Vital Signs: Time in Congestion - Corridor (Updated October 2018)
data.bayareametro.gov | Last Updated 2018-10-24T00:31:33.000ZVITAL SIGNS INDICATOR Time Spent in Congestion (T7) FULL MEASURE NAME Time Spent in Congestion LAST UPDATED October 2018 DATA SOURCE MTC/Iteris Congestion Analysis No link available CA Department of Finance Forms E-8 and E-5 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/ http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/ CA Employment Division Department: Labor Market Information http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Time spent in congestion measures the hours drivers are in congestion on freeway facilities based on traffic data. In recent years, data for the Bay Area comes from INRIX, a company that collects real-time traffic information from a variety of sources including mobile phone data and other GPS locator devices. The data provides traffic speed on the region’s highways. Using historical INRIX data (and similar internal datasets for some of the earlier years), MTC calculates an annual time series for vehicle hours spent in congestion in the Bay Area. Time spent in congestion is defined as the average daily hours spent in congestion on Tuesdays, Wednesdays and Thursdays during peak traffic months on freeway facilities. This indicator focuses on weekdays given that traffic congestion is generally greater on these days; this indicator does not capture traffic congestion on local streets due to data unavailability. This congestion indicator emphasizes recurring delay (as opposed to also including non-recurring delay), capturing the extent of delay caused by routine traffic volumes (rather than congestion caused by unusual circumstances). Recurring delay is identified by setting a threshold of consistent delay greater than 15 minutes on a specific freeway segment from vehicle speeds less than 35 mph. This definition is consistent with longstanding practices by MTC, Caltrans and the U.S. Department of Transportation as speeds less than 35 mph result in significantly less efficient traffic operations. 35 mph is the threshold at which vehicle throughput is greatest; speeds that are either greater than or less than 35 mph result in reduced vehicle throughput. This methodology focuses on the extra travel time experienced based on a differential between the congested speed and 35 mph, rather than the posted speed limit. To provide a mathematical example of how the indicator is calculated on a segment basis, when it comes to time spent in congestion, 1,000 vehicles traveling on a congested segment for a 1/4 hour (15 minutes) each, [1,000 vehicles x ¼ hour congestion per vehicle= 250 hours congestion], is equivalent to 100 vehicles traveling on a congested segment for 2.5 hours each, [100 vehicles x 2.5 hour congestion per vehicle = 250 hours congestion]. In this way, the measure captures the impacts of both slow speeds and heavy traffic volumes. MTC calculates two measures of delay – congested delay, or delay that occurs when speeds are below 35 miles per hour, and total delay, or delay that occurs when speeds are below the posted speed limit. To illustrate, if 1,000 vehicles are traveling at 30 miles per hour on a one mile long segment, this would represent 4.76 vehicle hours of congested delay [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 35 miles per hour) = 33.33 vehicle hours – 28.57 vehicle hours = 4.76 vehicle hours]. Considering that the posted speed limit on the segment is 60 miles per hour, total delay would be calculated as 16.67 vehicle hours [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 60 miles per hour) = 33.33 vehicle hours – 16.67 vehicle hours = 16.67 vehicle hours]. Data sources listed above were used to calculate per-capita and per-worker statistics. Top congested corridors are ranked by total vehicle hours of delay, meaning that the highlighted corridors reflect a combination of slow speeds and heavy t
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Vital Signs: Street Pavement Condition - by County (Updated August 2018)
data.bayareametro.gov | Last Updated 2018-08-21T00:38:43.000ZVITAL SIGNS INDICATOR Street Pavement Condition (T16) FULL MEASURE NAME Pavement condition index (PCI) LAST UPDATED August 2018 DESCRIPTION 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. DATA SOURCE Metropolitan Transportation Commission: StreetSaver CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Pavement condition index (PCI) relies upon a three-year moving average for regional, county, and city PCI to improve the reliability of the PCI data on an annual basis. The index ranges from 0 to 100, with 0 representing a failed road and 100 representing a brand-new facility. Segment PCI data is collected on a rolling basis but is imputed for interim years based on facility age and treatments using the MTC StreetSaver system. Due to the lack of reported PCI data in 2007, the city of Palo Alto is not included in the Regional Distribution chart.
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Vital Signs: Street Pavement Condition - Bay Area (Updated October 2019)
data.bayareametro.gov | Last Updated 2019-10-15T03:16:14.000ZVITAL SIGNS INDICATOR Street Pavement Condition (T16) FULL MEASURE NAME Pavement condition index (PCI) LAST UPDATED October 2019 DESCRIPTION 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. DATA SOURCE Metropolitan Transportation Commission: StreetSaver CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Pavement condition index (PCI) relies upon a three-year moving average for regional, county and city PCI to improve the reliability of the PCI data on an annual basis. The index ranges from 0 to 100, with 0 representing a failed road and 100 representing a brand-new facility. Segment PCI data is collected on a rolling basis but is imputed for interim years based on facility age and treatments using the MTC StreetSaver system. Pavement condition data was not collected in 2008. As such, 2007 and 2009 PCI scores were averaged to compute a 2008 estimate for the region, county and city datasets. Due to a lack of reported PCI data for the city of Palo Alto in 2007, an average could not be calculated, so Palo Alto is not included in the Regional Distribution chart.
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Vital Signs: Street Pavement Condition - by City (Updated August 2018)
data.bayareametro.gov | Last Updated 2018-08-21T00:42:13.000ZVITAL SIGNS INDICATOR Street Pavement Condition (T16) FULL MEASURE NAME Pavement condition index (PCI) LAST UPDATED August 2018 DESCRIPTION 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. DATA SOURCE Metropolitan Transportation Commission: StreetSaver CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Pavement condition index (PCI) relies upon a three-year moving average for regional, county, and city PCI to improve the reliability of the PCI data on an annual basis. The index ranges from 0 to 100, with 0 representing a failed road and 100 representing a brand-new facility. Segment PCI data is collected on a rolling basis but is imputed for interim years based on facility age and treatments using the MTC StreetSaver system. Due to the lack of reported PCI data in 2007, the city of Palo Alto is not included in the Regional Distribution chart.
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Vital Signs: Street Pavement Condition - by decade (Updated August 2018)
data.bayareametro.gov | Last Updated 2018-08-21T00:44:35.000ZVITAL SIGNS INDICATOR Street Pavement Condition (T16) FULL MEASURE NAME Pavement condition index (PCI) LAST UPDATED August 2018 DESCRIPTION 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. DATA SOURCE Metropolitan Transportation Commission: StreetSaver CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Pavement condition index (PCI) relies upon a three-year moving average for regional, county, and city PCI to improve the reliability of the PCI data on an annual basis. The index ranges from 0 to 100, with 0 representing a failed road and 100 representing a brand-new facility. Segment PCI data is collected on a rolling basis but is imputed for interim years based on facility age and treatments using the MTC StreetSaver system. Due to the lack of reported PCI data in 2007, the city of Palo Alto is not included in the Regional Distribution chart.
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Vital Signs: Jobs By Industry – Bay Area
data.bayareametro.gov | Last Updated 2019-08-13T16:19:32.000ZVITAL SIGNS INDICATOR Jobs by Industry (EC1) FULL MEASURE NAME Employment by place of work by industry sector LAST UPDATED July 2019 DESCRIPTION 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. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment by place of work and by industry. Industries are classified by their North American Industry Classification System (NAICS) code. Vital Signs aggregates employment into 11 industry sectors: Farm, Mining, Logging and Construction, Manufacturing, Trade, Transportation and Utilities, Information, Financial Activities, Professional and Business Services, Educational and Health Services, Leisure and Hospitality, Government, and Other. EDD counts all public-sector jobs under Government, including public transportation, public schools, and public hospitals. The Other category includes service jobs such as auto repair and hair salons and organizations such as churches and social advocacy groups. Employment in the technology sector are classified under three categories: Professional and Business Services, Information, and Manufacturing. The latter category includes electronic and computer manufacturing. For further details of typical firms found in each sector, refer to the 2012 NAICS Manual (http://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2012). The Bureau of Labor Statistics (BLS) provides industry estimates for non-Bay Area metro areas. Their main industry employment estimates, the Current Employment Survey and Quarterly Census of Employment and Wages, do not provide annual estimates of farm employment. To be consistent, the metro comparison evaluates nonfarm employment for all metro areas, including the Bay Area. Industry shares are thus slightly different for the Bay Area between the historical trend and metro comparison sections. The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of the nation’s employment in that same sector. Because BLS does not provide national farm estimates, note that there is no LQ for regional farm employment. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.
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Vital Signs: Life Expectancy Ten Year Change – by city
data.bayareametro.gov | Last Updated 2018-07-06T18:04:50.000ZVITAL SIGNS INDICATOR Street Pavement Condition (T16) FULL MEASURE NAME Pavement condition index (PCI) LAST UPDATED May 2017 DESCRIPTION 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. DATA SOURCE Metropolitan Transportation Commission: StreetSaver CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Pavement condition index (PCI) relies upon a three-year moving average for regional, county, and city PCI to improve the reliability of the PCI data on an annual basis. The index ranges from 0 to 100, with 0 representing a failed road and 100 representing a brand-new facility. Segment PCI data is collected on a rolling basis but is imputed for interim years based on facility age and treatments using the MTC StreetSaver system. Due to the lack of reported PCI data in 2006, the city of Palo Alto is not included in the Regional Distribution chart.
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Vital Signs: Greenfield Development – by metro area
data.bayareametro.gov | Last Updated 2020-07-03T16:36:42.000ZVITAL SIGNS INDICATOR Greenfield Development (LU5) FULL MEASURE NAME The acres of construction on previously undeveloped land LAST UPDATED November 2019 DESCRIPTION Greenfield development refers to construction on previously undeveloped land and the corresponding expansion of our region’s developed footprint, which includes the extent of urban and built-up lands. The footprint is defined as land occupied by structures, with a building density of at least 1 unit to 1.5 acres. DATA SOURCE Department of Conservation: Farmland Mapping and Monitoring Program GIS Data Tables/Layers (1990-2016) https://www.conservation.ca.gov/dlrp/fmmp U.S. Census Bureau: Decennial Census Population by Census Block Group (2000-2010) http://factfinder.census.gov U.S. Census Bureau: American Community Survey (5-year) Population by Census Block Group (2000-2017) http://factfinder.census.gov METHODOLOGY NOTES (across all datasets for this indicator) For regional and local data, FMMP maps the extent of “urban and built-up” lands, which generally reflect the developed urban footprint of the region. The footprint is defined as land occupied by structures with building density of at least 1 unit to 1.5 acres. Uses include residential, industrial, commercial, construction, institutional, public administration, railroad and other transportation yards, cemeteries, airports, golf courses, sanitary landfills, sewage treatment, water control structures, and other developed purposes. To determine the amount of greenfield development (in acres) occurring in a given two-year period, the differences in urban footprint are computed on a county-level. FMMP makes slight refinements to urban boundaries over time, so changes in urban footprint +/- 100 acres are not regionally significant. The GIS shapefile represents the 2016 urban footprint and thus does not show previously urbanized land outside of the footprint (i.e. Hamilton Air Force Base). For metro comparisons, a different methodology had to be used to avoid the geospatial limitations associated with FMMP. U.S. Census population by census block group was gathered for each metro area for 2000, 2010, and 2017. Population data for years 2000 and 2010 come from the Decennial Census while data for 2018 comes from the 2017 5-year American Community Survey. The block group was considered urbanized if its average/gross density was greater than 1 housing unit per acre (a slightly higher threshold than FMMP uses for its definition). Because a block group cannot be flagged as partially urbanized, and non-residential uses are not fully captured, the urban footprint of the region calculated with this methodology is smaller than in FMMP. The metro data should be primarily used for looking at comparative growth rate in greenfield development rather than the acreage totals themselves.
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Vital Signs: Highway Pavement Condition – Bay Area
data.bayareametro.gov | Last Updated 2018-07-06T18:05:10.000ZVITAL SIGNS INDICATOR Highway Pavement Condition (T17) FULL MEASURE NAME Distressed share of highway lane-miles LAST UPDATED February 2017 DESCRIPTION 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. DATA SOURCE California Department of Transportation: State of the Pavement Report http://www.dot.ca.gov/hq/maint/Pavement/Pavement_Program/PDF/2015_SOP-7-9_12-22-15-FINAL_revised_1-4-15.pdf CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Caltrans datasets only include regional performance on a historical basis and rely on "distressed" lane-mileage as an indicator for poor pavement condition. The geospatial data for 2015 provides the condition on each lane-mile for each segment of roadway; data on a corridor basis reflects a sum of all lane-mileage for that corridor.
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Vital Signs: Street Pavement Condition - by county (Updated October 2019)
data.bayareametro.gov | Last Updated 2019-10-15T03:15:32.000ZVITAL SIGNS INDICATOR Street Pavement Condition (T16) FULL MEASURE NAME Pavement condition index (PCI) LAST UPDATED October 2019 DESCRIPTION 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. DATA SOURCE Metropolitan Transportation Commission: StreetSaver CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Pavement condition index (PCI) relies upon a three-year moving average for regional, county and city PCI to improve the reliability of the PCI data on an annual basis. The index ranges from 0 to 100, with 0 representing a failed road and 100 representing a brand-new facility. Segment PCI data is collected on a rolling basis but is imputed for interim years based on facility age and treatments using the MTC StreetSaver system. Pavement condition data was not collected in 2008. As such, 2007 and 2009 PCI scores were averaged to compute a 2008 estimate for the region, county and city datasets. Due to a lack of reported PCI data for the city of Palo Alto in 2007, an average could not be calculated, so Palo Alto is not included in the Regional Distribution chart.