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Uses of Census Data and Geographies

Explore how Census data shapes transportation policy. Learn about Commodity Flow Survey areas, CTPP demographics, and LATCH estimates, vital for state and local planning efforts. Dive into Geographic Lessons from LATCH, offering insights on data quality and geographic levels.

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Uses of Census Data and Geographies

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  1. Uses of Census Data and Geographies Theresa Firestine and Clara Reschovsky Bureau of Transportation Statistics, DOT August 2, 2018

  2. BTS Publications and Products • Passenger Travel Facts & Figures • Pocket Guide • Now an app for smart phones • Transportation Statistics Annual Report (TSAR) • State Transportation Statistics • Lives online and can be updated more often • Presentations to outside groups • LATCH

  3. Geographic Boundary Files • BTS data is usually different from Census data, but uses Census boundary files as its base • State delineations • Metropolitan and micropolitan statistical areas • Tracts

  4. Commodity Flow Survey • BTS partners with the Census Bureau to conduct survey • Primary source of national and state-level data on domestic freight shipments by American establishments • Types of commodities being moved • Origins and destinations • Values and weights • Modes of transportation • Distance shipped and ton-miles of commodities shipped • CFS is a component of the Census Bureau’s economic census and is conducted every five years.  • First CFS was conducted in 1993 and data collection for the 2017 CFS is complete (data release anticipated between Dec 2018 and Dec 2019 • 134 CFS Areas– made up of full states, or a combination of MSA/CSAs and balance of state • MSA/CSAs are selected based on a combination of large population & major freight gateways (ex. Laredo, Tx)

  5. Commodity Flow Survey Areas • BTS has designed the CFS areas • Controlled at the state level • Survey samples drawn at the CFS Area level

  6. Census Transportation Planning Package (ctpp.transportation.org) • Largest special tabulation from the Census Bureau; pooled fund from states through AASHTO • Based on 1970-2000 Decennial Census data, 2006-2010 ACS, and 2012-2016 ACS (forthcoming) • Key inputs to a variety of state, regional, and local transportation policy and planning efforts • Demographic characteristics • Tabulations at home and work geographies • Journey-to-work travel flows by characteristics • Support corridor and project studies, environmental analyses, and emergency operations management

  7. CTPP Software Maps Workers arriving at work between 7:30 and 7:45 AM for TAZs in DC and surrounding areas Total Population by State of Residence State of Work for Workers living in Colorado

  8. Other DOT uses (very briefly) • Grant programs require population and characteristics as part of application process • Survey weights often use Census data as base • FHWA uses ACS data to weight the NHTS survey data • FTA requires usage of Census population and characteristics for states, MPOs, fixed-route transit agencies to demonstrate adequate service to disadvantages populations • Race/ethnicity • Low income • Limited English proficiency

  9. LATCH: Local Area Transportation Characteristics by Household • Sub-national estimates for all U.S. Census tracts of average weekday household: • Person-miles traveled • Person trips • Vehicle-miles traveled • Vehicle-trips • Model uses NHTS data and transfers it to Census Tracts using American Community Survey data • Estimates provide potentially beneficial indicators to local governments and other customers who may not have the budget and/or time for conducting their own household local survey • NHTS itself is not a reliable data source for most smaller geographic areas due to sample size limitations

  10. Geographic Lessons from LATCH • Provides template for choosing appropriate geographic level without losing data quality • Estimation by Census Region/Division and by urban/suburban/rural to capture geographic difference in travel behavior • Margin of Error varies by geographic level • Margin of Error > Estimate necessitates combining subgroups for data quality • Spatial outliers • Data outliers, e.g. NYC https://www.bts.gov/statistical-products/surveys/local-area-transportation-characteristics-households-latch-survey

  11. Questions? • Clara Reschovsky, Bureau of Transportation Statistics clara.reschovsky@dot.gov • Theresa Firestine, Bureau of Transportation Statistics theresa.firestine@dot.gov

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