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Retrofitting the Suburbs to Increase Walking: Evidence from a Land-use-Travel Study

Author

Listed:
  • Marlon G. Boarnet

    (Departments of Planning, Policy, and Design and Economics and the Institute of Transportation Studies, University of California - Irvine, Irvine, California, 92697-7075, USA, mgboarne@uci.edu)

  • Kenneth Joh

    (Department of Landscape Architecture & Urban Planning, Texas A&M University, 3137 TAMU, College Station, Texas, 78743-3137, USA, kjoh@tamu.edu)

  • Walter Siembab

    (Siembab Planning Associates, 5944 Chariton Avenue, Los Angeles, California, 90056, USA, ws@siembab.com)

  • William Fulton

    (School of Policy, Planning & Development, University of Southern California, Los Angeles, California, 90089, USA; bfulton@cp-dr.com)

  • Mai Thi Nguyen

    (Department of City and Regional Planning, University of North Carolina at Chapel Hill, CB # 3140, Chapel Hill, North Carolina, 27599, USA, mai@unc.edu)

Abstract

This paper reports results from a detailed travel diary survey of 2125 residents in the South Bay area of Los Angeles County—a mature, auto-oriented suburban region. Study areas were divided into four centres, typical of compact development or smart growth, and four linear, auto-oriented corridors. Results show substantial variation in the amount of walking across study areas. Trips are shorter and more likely to be via walking in centres. A key to the centres’ increased walking travel is the concentration of local shopping and service destinations in a commercial core. Yet the amount of business concentration that is associated with highly pedestrian-oriented neighbourhoods is from three to four times as large as what can be supported by the local resident base, suggesting that pedestrian-oriented neighbourhoods necessarily import shopping trips, and hence driving trips, from larger surrounding catchment areas. The results suggest both land use and mobility strategies that can be appropriate for suburban regions.

Suggested Citation

  • Marlon G. Boarnet & Kenneth Joh & Walter Siembab & William Fulton & Mai Thi Nguyen, 2011. "Retrofitting the Suburbs to Increase Walking: Evidence from a Land-use-Travel Study," Urban Studies, Urban Studies Journal Limited, vol. 48(1), pages 129-159, January.
    • Handle: RePEc:sae:urbstu:v:48:y:2011:i:1:p:129-159
    DOI: 10.1177/0042098010364859
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    References listed on IDEAS

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    Cited by:

    1. Ahlfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2019. "The economic effects of density: A synthesis," Journal of Urban Economics, Elsevier, vol. 111(C), pages 93-107.
    2. Clark, Thomas A., 2013. "Metropolitan density, energy efficiency and carbon emissions: Multi-attribute tradeoffs and their policy implications," Energy Policy, Elsevier, vol. 53(C), pages 413-428.
    3. Boarnet, Marlon G. & Hsu, Hsin-Ping, 2015. "The gender gap in non-work travel: The relative roles of income earning potential and land use," Journal of Urban Economics, Elsevier, vol. 86(C), pages 111-127.
    4. Lee, Yongsung & Guhathakurta, Subhrajit, 2018. "An analysis of the effects of suburban densification on vehicle use for shopping: Do existing residents respond to land-use changes in the same way as recent movers?," Journal of Transport Geography, Elsevier, vol. 68(C), pages 193-204.
    5. Simon Choi & Changkeun Park & JiYoung Park, 2014. "A spatio-temporal analysis of population and employment growth for Southern California," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(1), pages 19-40, January.
    6. Neatt, Kevin & Millward, Hugh & Spinney, Jamie, 2017. "Neighborhood walking densities: A multivariate analysis in Halifax, Canada," Journal of Transport Geography, Elsevier, vol. 61(C), pages 9-16.
    7. Kenneth Joh & Sandip Chakrabarti & Marlon G. Boarnet & Ayoung Woo, 2015. "The Walking Renaissance: A Longitudinal Analysis of Walking Travel in the Greater Los Angeles Area, USA," Sustainability, MDPI, vol. 7(7), pages 1-27, July.
    8. Silva, Mafalda C. & Horta, Isabel M. & Leal, Vítor & Oliveira, Vítor, 2017. "A spatially-explicit methodological framework based on neural networks to assess the effect of urban form on energy demand," Applied Energy, Elsevier, vol. 202(C), pages 386-398.

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