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Integrating people and place: A density-based measure for assessing accessibility to opportunities

Author

Listed:
  • Horner, Mark

    (Florida Stae University)

  • Downs, Joni

    (University of South Florida)

Abstract

Mobile object analysis is a well-studied area of transportation and geographic information science (GIScience). Mobile objects may include people, animals, or vehicles. Time geography remains a key theoretical framework for understanding mobile objects' movement possibilities. Recent efforts have sought to develop probabilistic methods of time geography by exploring questions of data uncertainty, spatial representation, and other limitations of classical approaches. Along these lines, work has blended time geography and kernel density estimation in order to delineate the probable locations of mobile objects in both continuous and discrete network space. This suite of techniques is known as time geographic density estimation (TGDE). The present paper explores a new direction for TGDE, namely the creation of a density-based accessibility measure for assessing mobile objects' potential for interacting with opportunity locations. As accessibility measures have also garnered widespread attention in the literature, the goal here is to understand the magnitude and nature of the opportunities a mobile object had access to, given known location points and a time budget for its movement. New accessibility measures are formulated and demonstrated with synthetic trip diary data. The implications of the new measures are discussed in the context of people-based vs. placed-based accessibility analyses.

Suggested Citation

  • Horner, Mark & Downs, Joni, 2014. "Integrating people and place: A density-based measure for assessing accessibility to opportunities," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 1-18.
    • Handle: RePEc:ris:jtralu:0135
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    References listed on IDEAS

    as
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    Cited by:

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    2. Lingqian Hu, 2017. "Job accessibility and employment outcomes: which income groups benefit the most?," Transportation, Springer, vol. 44(6), pages 1421-1443, November.
    3. Liu, Chang & Bardaka, Eleni, 2021. "The suburbanization of poverty and changes in access to public transportation in the Triangle Region, NC," Journal of Transport Geography, Elsevier, vol. 90(C).
    4. Scott, Darren & H. Y. Lee, Brian & Miller, Eric, 2014. "Special section: Innovations in location choice modeling underlying activity-travel behavior," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 1-2.
    5. Wang, Yafei & Chen, Bi Yu & Yuan, Hui & Wang, Donggen & Lam, William H.K. & Li, Qingquan, 2018. "Measuring temporal variation of location-based accessibility using space-time utility perspective," Journal of Transport Geography, Elsevier, vol. 73(C), pages 13-24.
    6. Barboza, Matheus H.C. & Carneiro, Mariana S. & Falavigna, Claudio & Luz, Gregório & Orrico, Romulo, 2021. "Balancing time: Using a new accessibility measure in Rio de Janeiro," Journal of Transport Geography, Elsevier, vol. 90(C).
    7. Kelobonye, Keone & Zhou, Heng & McCarney, Gary & Xia, Jianhong (Cecilia), 2020. "Measuring the accessibility and spatial equity of urban services under competition using the cumulative opportunities measure," Journal of Transport Geography, Elsevier, vol. 85(C).

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    More about this item

    Keywords

    Transportation; Accessibility; Mobile Objects; GIS;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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