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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: Seaport Activity – by metro area
data.bayareametro.gov | Last Updated 2019-10-25T20:09:10.000ZVITAL SIGNS INDICATOR Seaport Activity (EC18) FULL MEASURE NAME Shipping containers moved (TEUs) LAST UPDATED August 2019 DESCRIPTION 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). DATA SOURCE American Association of Port Authorities: Western Hemisphere Port TEU Container Volumes 1990-2017 https://www.aapa-ports.org/unifying/content.aspx?ItemNumber=21048 Port of Oakland 1990-2018 https://www.oaklandseaport.com/performance/facts-figures/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Container volumes include both empty and full containers that move through a given port; they include imports, exports, and domestic freight flows.
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Vital Signs: Seaport Activity – Bay Area
data.bayareametro.gov | Last Updated 2019-10-25T20:09:24.000ZVITAL SIGNS INDICATOR Seaport Activity (EC18) FULL MEASURE NAME Shipping containers moved (TEUs) LAST UPDATED August 2019 DESCRIPTION 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). DATA SOURCE American Association of Port Authorities: Western Hemisphere Port TEU Container Volumes 1990-2017 https://www.aapa-ports.org/unifying/content.aspx?ItemNumber=21048 Port of Oakland 1990-2018 https://www.oaklandseaport.com/performance/facts-figures/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Container volumes include both empty and full containers that move through a given port; they include imports, exports, and domestic freight flows.
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Vital Signs: Greenfield Development – Bay Area
data.bayareametro.gov | Last Updated 2020-07-03T16:37:00.000ZVITAL 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: Greenfield Development – by county
data.bayareametro.gov | Last Updated 2020-07-03T16:36:18.000ZVITAL 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: Greenfield Development – Bay Area shapefile
data.bayareametro.gov | Last Updated 2020-07-03T16:35:24.000ZVITAL 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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ART Bay Area Inundation Scenario - 36" Sea Level Rise
data.bayareametro.gov | Last Updated 2023-06-09T00:07:18.000ZInundation feature set representing areas vulnerable to a 36 inch rise in sea level for the San Francisco Bay Region. This is a derivative feature set, assembled by the Metropolitan Transportation Commission (MTC), created by merging county-specific, land-only inundation feature sets. The source, county-level feature sets were produced for Adapting to Rising Tides (ART), a program led by the San Francisco Bay Conservation and Development Commission (BCDC), in September 2017. The sea level rise (SLR) scenario used to produce this data represents 36 inches (three feet) of water level above the current mean higher high water (MHHW) tidal datum. This is considered the most likely level of sea level rise expected by 2100; or an existing 50-year extreme tide. The polygons contain the extent and depth of land-only inundation (in feet) flooding of the bayside shoreline. Depth of flooding were created by subtracting a land surface Digital Elevation Model (DEM) from the water surface DEM representing the SLR scenario (MHHW + SLR). Extent of flooding were created by employing a two rule assessment to determine if an area is inundated. It must be below the assigned water surface DEM elevation value, and it must be connected to an adjacent area that was either flooded or open water. This method applies an "eight-side rule" for connectedness, where the area is considered "connected" if any of its cardinal or diagonal directions is connected to a flooded area or open water. Hydraulic connectivity assessment removes areas from the inundation zone if they are protected by levees or other topographic features that prevent inland inundation. This assessment also removed areas that are low lying but inland and not directly connected to an adjacent inundated area. The 36 inch SLR scenario can be used to approximate all extreme tide/sea level rise combinations that produce a water level in the range of MHHW + 33 inches to MHHW + 39 inches, including: - 36 inches of SLR; - 1-year extreme tide event coupled with 24 inches of SLR; - 2-year extreme tide event coupled with 18 inches of SLR; - 5-year extreme tide event coupled with 12 inches of SLR; - 25-year extreme tide event coupled with 6 inches of SLR, and - 50-year extreme tide event under existing conditions (no SLR). Publication Date: June 2019 Creation Date: March 2019 Status: Progress: Complete Maintenance and Update Frequency: None planned Contact Information: Contact Organization: Metropolitan Transportation Commission Contact Person: Data & Visualization Contact Address: Address Type: mailing and physical Address: 375 Beale Street, Suite 800 City: San Francisco State or Province: California Postal Code: 94105 Country: United States of America Contact Voice Telephone: (415) 778-6700 Contact Electronic Mail Address: dataviz@bayareametro.gov Hours: 9:00 AM - 5:00 PM (PST) Monday through Friday
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Vital Signs: Life Expectancy – by ZIP Code
data.bayareametro.gov | Last Updated 2018-07-06T18:05:06.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population. Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly im
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Vital Signs: Life Expectancy – Bay Area
data.bayareametro.gov | Last Updated 2018-07-06T18:05:05.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and Zip codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population. Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential Zip code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the Zip code-level life expectancy calculation, it is assumed that postal Zip codes share the same boundaries as Zip Code Census Tabulation Areas (ZCTAs). More information on the relationship between Zip codes and ZCTAs can be found at https://www.census.gov/geo/reference/zctas.html. Zip code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 Zip code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for Zip codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest Zip code with population. Zip code population for 2000 estimates comes from the Decennial Census. Zip code population for 2013 estimates are from the American Community Survey (5-Year Average). The ACS provides Zip code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to Zip codes based on majority land-area. Zip codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, Zip codes with populations of less than 5,000 were aggregated with neighboring Zip codes until the merged areas had a population of more than 5,000. In this way, the original 305 Bay Area Zip codes were reduced to 218 Zip
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Vital Signs: Life Expectancy – by county
data.bayareametro.gov | Last Updated 2018-07-06T18:05:04.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and Zip codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population. Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential Zip code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the Zip code-level life expectancy calculation, it is assumed that postal Zip codes share the same boundaries as Zip Code Census Tabulation Areas (ZCTAs). More information on the relationship between Zip codes and ZCTAs can be found at https://www.census.gov/geo/reference/zctas.html. Zip code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 Zip code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for Zip codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest Zip code with population. Zip code population for 2000 estimates comes from the Decennial Census. Zip code population for 2013 estimates are from the American Community Survey (5-Year Average). The ACS provides Zip code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to Zip codes based on majority land-area. Zip codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, Zip codes with populations of less than 5,000 were aggregated with neighboring Zip codes until the merged areas had a population of more than 5,000. In this way, the original 305 Bay Area Zip codes were reduced to 218 Zip