IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v48y2021i2d10.1007_s11116-019-10072-0.html
   My bibliography  Save this article

Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows

Author

Listed:
  • Crispin H. V. Cooper

    (Cardiff University)

  • Ian Harvey

    (Cardiff University
    Cardiff University)

  • Scott Orford

    (Cardiff University)

  • Alain J. F. Chiaradia

    (University of Hong Kong
    Belt and Road Urban Observatory (OBORobs))

Abstract

Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for environmental, social and economic sustainability. We present longitudinal evaluation of a model of the effect of urban environmental layout change in a city centre (Cardiff 2007–2010), on pedestrian flows. Our model can be classed as regression based direct demand using Multiple Hybrid Spatial Design Network Analysis (MH-sDNA) assignment, which bridges the gap between direct demand models, facility-based activity estimation and spatial network analysis (which can also be conceived as a pedestrian route assignment based direct demand model). Multiple theoretical flows are computed based on retail floor area: everywhere to shops, shop to shop, railway stations to shops and parking to shops. Route assignment, in contrast to the usual approach of shortest path only, is based on a hybrid of shortest path and least directional change (most direct) with a degree of randomization. The calibration process determines a suitable balance of theoretical flows to best match observed pedestrian flows, using generalized cross-validation to prevent overfit. Validation shows that the model successfully predicts the effect of layout change on flows of up to approx. 8000 pedestrians per hour based on counts spanning a 1 km2 city centre, calibrated on 2007 data and validated to 2010 and 2011. This is the first time, to our knowledge, that a pedestrian flow model with assignment has been evaluated for its ability to forecast the effect of urban layout changes over time.

Suggested Citation

  • Crispin H. V. Cooper & Ian Harvey & Scott Orford & Alain J. F. Chiaradia, 2021. "Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows," Transportation, Springer, vol. 48(2), pages 643-672, April.
    • Handle: RePEc:kap:transp:v:48:y:2021:i:2:d:10.1007_s11116-019-10072-0
    DOI: 10.1007/s11116-019-10072-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-019-10072-0
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-019-10072-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Raford, Noah & Ragland, David, 2006. "Pedestrian Volume Modeling for Traffic Safety and Exposure Analysis: The Case of Boston, Massachusetts," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt61n3s4zr, Institute of Transportation Studies, UC Berkeley.
    3. Dionysia Lambiri & Alessandra Faggian & Neil Wrigley, 2017. "Linked-trip effects of ‘town-centre-first' era foodstore development: An assessment using difference-in-differences," Environment and Planning B, , vol. 44(1), pages 160-179, January.
    4. Paul Stangl, 2019. "Overcoming flaws in permeability measures: modified route directness," Journal of Urbanism: International Research on Placemaking and Urban Sustainability, Taylor & Francis Journals, vol. 12(1), pages 1-14, January.
    5. Shatu, Farjana & Yigitcanlar, Tan & Bunker, Jonathan, 2019. "Shortest path distance vs. least directional change: Empirical testing of space syntax and geographic theories concerning pedestrian route choice behaviour," Journal of Transport Geography, Elsevier, vol. 74(C), pages 37-52.
    6. Cooper, Crispin H.V., 2017. "Using spatial network analysis to model pedal cycle flows, risk and mode choice," Journal of Transport Geography, Elsevier, vol. 58(C), pages 157-165.
    7. Borgers, A. & Timmermans, H. J. P., 1986. "City centre entry points, store location patterns and pedestrian route choice behaviour: A microlevel simulation model," Socio-Economic Planning Sciences, Elsevier, vol. 20(1), pages 25-31.
    8. Lowry, Michael, 2014. "Spatial interpolation of traffic counts based on origin–destination centrality," Journal of Transport Geography, Elsevier, vol. 36(C), pages 98-105.
    9. Boeing, Geoff, 2019. "The Morphology and Circuity of Walkable and Drivable Street Networks," SocArXiv edj2s, Center for Open Science.
    10. Raford, Noah & Chiaradia, Alain & Gil, Jorge, 2007. "Space Syntax: The Role of Urban Form in Cyclist Route Choice in Central London," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8qz8m4fz, Institute of Transportation Studies, UC Berkeley.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fernando Fonseca & Escolástica Fernandes & Rui Ramos, 2022. "Walkable Cities: Using the Smart Pedestrian Net Method for Evaluating a Pedestrian Network in Guimarães, Portugal," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    2. Sevtsuk, Andres & Basu, Rounaq, 2022. "The role of turns in pedestrian route choice: A clarification," Journal of Transport Geography, Elsevier, vol. 102(C).
    3. Zaouche, Mounia & Bode, Nikolai W.F., 2023. "Bayesian spatio-temporal models for mapping urban pedestrian traffic," Journal of Transport Geography, Elsevier, vol. 111(C).
    4. An, Zihao & Xie, Bo & Liu, Qiyang, 2023. "No street is an Island: Street network morphologies and traffic safety," Transport Policy, Elsevier, vol. 141(C), pages 167-181.
    5. Tianyang Ge & Wenjun Hou & Yang Xiao, 2023. "Study on the Regeneration of City Centre Spatial Structure Pedestrianisation Based on Space Syntax: Case Study on 21 City Centres in the UK," Land, MDPI, vol. 12(6), pages 1-26, June.
    6. Pei Yin & Miaojuan Peng, 2023. "Station Layout Optimization and Route Selection of Urban Rail Transit Planning: A Case Study of Shanghai Pudong International Airport," Mathematics, MDPI, vol. 11(6), pages 1-29, March.
    7. Zhou, You & Zhang, Lingzhu & JF Chiaradia, Alain, 2022. "Estimating wider economic impacts of transport infrastructure Investment: Evidence from accessibility disparity in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 220-235.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Singleton, Patrick A. & Park, Keunhyun & Lee, Doo Hong, 2021. "Varying influences of the built environment on daily and hourly pedestrian crossing volumes at signalized intersections estimated from traffic signal controller event data," Journal of Transport Geography, Elsevier, vol. 93(C).
    2. Zhou, You & Zhang, Lingzhu & JF Chiaradia, Alain, 2022. "Estimating wider economic impacts of transport infrastructure Investment: Evidence from accessibility disparity in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 220-235.
    3. Geoff Boeing, 2020. "A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood," Environment and Planning B, , vol. 47(4), pages 590-608, May.
    4. Lingzhu Zhang & Alain JF Chiaradia, 2022. "Walking in the cities without ground, how 3d complex network volumetrics improve analysis," Environment and Planning B, , vol. 49(7), pages 1857-1874, September.
    5. Yang, Wenyue & Chen, Huiling & Wang, Wulin, 2020. "The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 88(C).
    6. Yat Yen & Pengjun Zhao & Muhammad T Sohail, 2021. "The morphology and circuity of walkable, bikeable, and drivable street networks in Phnom Penh, Cambodia," Environment and Planning B, , vol. 48(1), pages 169-185, January.
    7. Mona Jabbari & Fernando Fonseca & Rui Ramos, 2021. "Accessibility and Connectivity Criteria for Assessing Walkability: An Application in Qazvin, Iran," Sustainability, MDPI, vol. 13(7), pages 1-18, March.
    8. Cooper, Crispin H.V., 2017. "Using spatial network analysis to model pedal cycle flows, risk and mode choice," Journal of Transport Geography, Elsevier, vol. 58(C), pages 157-165.
    9. Boeing, Geoff, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz, Center for Open Science.
    10. Ali Soltani & Andrew Allan & Masoud Javadpoor & Jaswanth Lella, 2022. "Space Syntax in Analysing Bicycle Commuting Routes in Inner Metropolitan Adelaide," Sustainability, MDPI, vol. 14(6), pages 1-13, March.
    11. Burcu H. Ozuduru & Chris J. Webster & Alain J. F. Chiaradia & Eda Yucesoy, 2021. "Associating street-network centrality with spontaneous and planned subcentres," Urban Studies, Urban Studies Journal Limited, vol. 58(10), pages 2059-2078, August.
    12. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    13. John Stanley & Janet Stanley, 2023. "Improving Appraisal Methodology for Land Use Transport Measures to Reduce Risk of Social Exclusion," Sustainability, MDPI, vol. 15(15), pages 1-18, August.
    14. Marie Geraldine Herrmann-Lunecke & Cristhian Figueroa-Martínez & Francisca Parra Huerta & Rodrigo Mora, 2022. "The Disabling City: Older Persons Walking in Central Neighbourhoods of Santiago de Chile," Sustainability, MDPI, vol. 14(17), pages 1-19, September.
    15. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.
    16. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    17. Van Acker, Veronique & Ho, Loan & Stevens, Larissa & Mulley, Corinne, 2020. "Quantifying the effects of childhood and previous residential experiences on the use of public transport," Journal of Transport Geography, Elsevier, vol. 86(C).
    18. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    19. Toşa, Cristian & Sato, Hitomi & Morikawa, Takayuki & Miwa, Tomio, 2018. "Commuting behavior in emerging urban areas: Findings of a revealed-preferences and stated-intentions survey in Cluj-Napoca, Romania," Journal of Transport Geography, Elsevier, vol. 68(C), pages 78-93.
    20. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:48:y:2021:i:2:d:10.1007_s11116-019-10072-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.