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The Half-Mile Circle: Does It Best Represent Transit Station Catchments?

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  • Guerra, Erick
  • Cervero, Robert
  • Tischler, Daniel
Abstract
One-half mile has become the accepted distance for gauging a transit station’s catchment area in the U.S. It is the de facto standard for planning TODs (transit oriented developments) in America. Planners and researchers use transit catchment areas not only to make predictions about transit ridership and the land use and socioeconomic impacts of transit, but also to prescribe regulations, such as the relaxation of restrictive zoning, or carve out TOD financial plans. This radius is loosely based on the distance that people are willing to walk to transit, but this same reasoning has been used to justify other transit catchment areas. Using station-level variables from 1,449 high-capacity American transit stations in 21 cities, we aim to identify whether there is clear benchmark between distance and ridership that provides a norm for station-area planning and prediction. For the purposes of predicting station-level transit ridership, we find that different catchment areas have little influence on a model’s predictive power. This suggests that transit agencies should use the easiest and most readily available data when estimating direct demand models. For prescribing land-use policy, by contrast, the evidence is less clear. Nevertheless, we find some support for using a quarter-mile catchment area for jobs around transit and a half-mile catchment for population. While these distances will likely vary from place to place and depending on the study purpose, they are a good starting point for considering transit-oriented policy or collecting labor-intensive data, such as surveys, about transit-adjacent firms or households.

Suggested Citation

  • Guerra, Erick & Cervero, Robert & Tischler, Daniel, 2011. "The Half-Mile Circle: Does It Best Represent Transit Station Catchments?," University of California Transportation Center, Working Papers qt9jd6r1t9, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt9jd6r1t9
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    Cited by:

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    2. Singh, Yamini Jain & Lukman, Azhari & Flacke, Johannes & Zuidgeest, Mark & Van Maarseveen, M.F.A.M., 2017. "Measuring TOD around transit nodes - Towards TOD policy," Transport Policy, Elsevier, vol. 56(C), pages 96-111.
    3. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Teller, David, 2020. "Study design impacts on built environment and transit use research," Journal of Transport Geography, Elsevier, vol. 82(C).
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    6. Jyothi Chava & Peter Newman, 2016. "Stakeholder Deliberation on Developing Affordable Housing Strategies: Towards Inclusive and Sustainable Transit-Oriented Developments," Sustainability, MDPI, vol. 8(10), pages 1-21, October.
    7. Vale, David S. & Viana, Cláudia M. & Pereira, Mauro, 2018. "The extended node-place model at the local scale: Evaluating the integration of land use and transport for Lisbon's subway network," Journal of Transport Geography, Elsevier, vol. 69(C), pages 282-293.
    8. Aston, Laura & Currie, Graham & Pavkova, Katerina, 2016. "Does transit mode influence the transit-orientation of urban development? – An empirical study," Journal of Transport Geography, Elsevier, vol. 55(C), pages 83-91.
    9. Kevin Credit, 2018. "Transit-oriented economic development: The impact of light rail on new business starts in the Phoenix, AZ Region, USA," Urban Studies, Urban Studies Journal Limited, vol. 55(13), pages 2838-2862, October.
    10. Cervero, Robert & Guerra, Erick, 2011. "Urban Densities and Transit: A Multi-dimensional Perspective," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3mb598qr, Institute of Transportation Studies, UC Berkeley.
    11. Arlie Adkins & Andrew Sanderford & Gary Pivo, 2017. "How Location Efficient Is LIHTC? Measuring and Explaining State-Level Achievement," Housing Policy Debate, Taylor & Francis Journals, vol. 27(3), pages 335-355, May.
    12. Jinbao Zhao & Wei Deng & Yan Song & Yueran Zhu, 2014. "Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models," Transportation, Springer, vol. 41(1), pages 133-155, January.
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