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Development of a temporal and spatial linkage between transit demand and land-use patterns

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Abstract

We are exploring ways to capture the temporal and spatial dimensions of the use of public transit. Specifically, we are investigating how different land uses affect the spatial and temporal demand for public transit services. Spatially, the availability of new data collection technology in public transit allows us to examine transit demand at the individual stop level. Our hypothesis, however, is that transit users' activity may not be originated from or destined to an individual stop per se; rather, the activity is associated with a specific location in the vicinity of the stop, and this location may be "covered" by several adjacent transit stops. More importantly, understanding the transit demand at this aggregate level (an aggregate "catchment" area) can enhance the ability to define a specific land-use type and the temporal characteristics related to passengers' activities. Temporally, we seek to understand the relationship between the demand for public transit service at specific times of the day and the associated land uses that may strongly influence the timing of that demand. To explore these dimensions, this study: 1) proposes a method of stop aggregation; 2) generates transit service areas based on these aggregated stops; 3) develops a set of metrics to better represent land-use types within these service areas; and 4) examines the spatial and temporal characteristics of transit demand for these service areas. These methods are applied to a case study using land-use and transit demand data from the Minneapolis–St. Paul metropolitan area.

Suggested Citation

  • Lee, Sanggu & Hickman, Mark & Tong, Daoqin, 2013. "Development of a temporal and spatial linkage between transit demand and land-use patterns," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 6(2), pages 33-46.
  • Handle: RePEc:ris:jtralu:0107
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    Cited by:

    1. Neema Nassir & Mark Hickman & Zhen-Liang Ma, 2015. "Activity detection and transfer identification for public transit fare card data," Transportation, Springer, vol. 42(4), pages 683-705, July.
    2. Jianming Le & Kunhui Ye, 2022. "Measuring City-Level Transit Accessibility Based on the Weight of Residential Land Area: A Case of Nanning City, China," Land, MDPI, vol. 11(9), pages 1-17, September.
    3. Zijia Wang & Hao Tang & Wenjuan Wang & Yang Xi, 2020. "The Pattern of Non-Roundtrip Travel on Urban Rail and Its Application in Transit Improvement," Sustainability, MDPI, vol. 12(9), pages 1-16, April.
    4. Merkebe Getachew Demissie & Lina Kattan, 2022. "Understanding the temporal and spatial interactions between transit ridership and urban land-use patterns: an exploratory study," Public Transport, Springer, vol. 14(2), pages 385-417, June.
    5. You-Jin Jung & Jeffrey M. Casello, 2020. "Assessment of the transit ridership prediction errors using AVL/APC data," Transportation, Springer, vol. 47(6), pages 2731-2755, December.

    More about this item

    Keywords

    public transit; land use;

    JEL classification:

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

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