National Neighborhood Data Archive (NaNDA): Traffic Volume by Census Tract and ZIP Code Tabulation Area, United States, 1963-2019 (ICPSR 38584)

Version Date: Nov 10, 2022 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Jessica M. Finlay, University of Michigan. Institute for Social Research; Robert Melendez, University of Michigan. Institute for Social Research; Michael Esposito, Washington University in St. Louis; Anam Khan, University of Michigan. Institute for Social Research; Mao Li, University of Michigan. Institute for Social Research; Iris Gomez-Lopez, University of Michigan. Institute for Social Research; Philippa Clarke, University of Michigan. Institute for Social Research; Megan Chenoweth, University of Michigan. Institute for Social Research

Series:

https://doi.org/10.3886/ICPSR38584.v2

Version V2 ()

  • V2 [2022-11-10]
  • V1 [2022-11-07] unpublished
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This dataset contains measures of traffic volume per census tract and ZIP code tabulation area (ZCTA) in the United States from 1963 to 2019 (primarily 1997 to 2019). High traffic volume may be used as a proxy for heavy traffic, high traffic speeds, and impediments to walking or biking. The dataset contains measures of the average, maximum, and minimum traffic volume per year or per ZCTA per year. These figures are available for all streets, highways, and non-highways. In the ZCTA dataset, data is collected intermittently across locations over time, therefore traffic volume has been interpolated for years in which no measures are available. Data Source: Traffic volume measurements are derived from Kalibrate's TrafficMetrix database accessed via Esri Demographics. Census tract boundaries come from the 2010 TIGER/Line shapefiles. ZCTA boundaries come from the 2019 TIGER/Line shapefiles.

Finlay, Jessica M., Melendez, Robert, Esposito, Michael, Khan, Anam, Li, Mao, Gomez-Lopez, Iris, … Chenoweth, Megan. National Neighborhood Data Archive (NaNDA): Traffic Volume by Census Tract and ZIP Code Tabulation Area, United States, 1963-2019 . Inter-university Consortium for Political and Social Research [distributor], 2022-11-10. https://doi.org/10.3886/ICPSR38584.v2

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United States Department of Health and Human Services. Administration for Community Living. National Institute on Disability, Independent Living, and Rehabilitation Research (90RTHF0001), United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging (RF1-AG-057540), United States Department of Health and Human Services. National Institutes of Health. National Institute of Nursing Research (U01NR020556), United States Department of Health and Human Services. National Institutes of Health. National Center on Minority Health and Health Disparities (U01NR020556)

census tract and ZIP code tabulation area (ZCTA)

Inter-university Consortium for Political and Social Research
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1963 -- 2019
2020 -- 2021
  1. The data and documentation for National Neighborhood Data Archive (NaNDA): Traffic Volume by Census Tract, United States, 1963-2019 and National Neighborhood Data Archive (NaNDA): Traffic Volume by ZIP Code Tabulation Area, United States, 1963-2019 were originally deposited in openICPSR.
  2. A ZIP code to ZCTA crosswalk must be used to combine this dataset with ZIP code geocoded data. A crosswalk and sample code for merging the crosswalk with National Neighborhood Data Archive (NaNDA) datasets are available in the ICPSR Linkage Library.
  3. Data users interested in walkability and neighborhood disamenities (such as pollution and traffic) might find useful data in these other NaNDA datasets:

  4. Data users interested in other resources that contribute to walkability, such as parks, public transit, and retail and other destinations, may find the following additional NaNDA datasets to be of use:

  5. For additional information see the National Neighborhood Data Archive (NaNDA).
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The purpose of this study is to characterize the average volume of traffic passing through a census tract and a ZIP code tabulation area in a given year.

The research team used three different types of traffic counts within TrafficMetrix: average annual daily traffic, average annual weekday traffic, and average daily traffic. For each corresponding location, the team obtained its latitude and longitude and whether the location is on a highway, then assigned latitudes and longitudes to census tracts and zip code tabulation areas (ZCTA). The team then determined the average, maximum, minimum, and number of traffic volume measurements across all locations in a tract and ZCTA in a given year. Separate measurements were created for highway traffic vs. non-highway traffic.

Traffic measurements are not available in every year. For the ZCTA data, the team interpolated values for certain years between observations due to the lack of measurements taken during that year. Missing values were created using a linear interpolation of the two nearest non-missing years. In the census tract data, measures were not interpolated for missing years.

Cross-sectional

Census tracts or ZIP code tabulation areas in the United States, excluding U.S. island territories.

ZIP code tabulation area, census tract

Data and documentation for the ZCTA-level data were originally deposited in openICPSR project 160261.

Data and documentation for the census tract-level data were originally deposited in openICPSR project 160262.

ZIP code tabulation area boundaries come from the 2019 TIGER/Line shapefiles (U.S. Census Bureau, 2019).

Kalibrate. "TrafficMetrix (2019 Version)." Esri Demographics, 2019.

United States Census Bureau. "TIGER/Line Shapefiles, 2010 Census Tracts (2010 Version)," 2010.

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2022-11-07

2022-11-10 The study website link was updated in the ICPSR codebooks.

2022-11-07 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Notes

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.