IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v42y2015i5p888-903.html
   My bibliography  Save this article

Gradual rasterization: redefining spatial resolution in transport modelling

Author

Listed:
  • Rolf Moeckel
  • Rick Donnelly

Abstract

It is a challenge to find the appropriate level of spatial resolution in transport modelling. While the zone system has substantial influence on model results, the resolution and design of zones is rarely analyzed systematically, and even less commonly adjusted to a specific modelling need. In this paper we present a new methodology to automatically create a new zone system based on the quadtree algorithm specific to transport modelling. Gradual raster cells are generated, where smaller raster cells tend to be used in urban areas and larger raster cells dominate in low-density, rural areas. As changing the zonal resolution affects the number of intrazonal and interzonal trips, an algorithm has been developed that adjusts intrazonal trips in line with the network resolution. Trip tables of a travel demand model for the state of Georgia, USA were disaggregated using this new zone system of gradual raster cells. The traffic assignment results validate significantly better than when using the original zone system.

Suggested Citation

  • Rolf Moeckel & Rick Donnelly, 2015. "Gradual rasterization: redefining spatial resolution in transport modelling," Environment and Planning B, , vol. 42(5), pages 888-903, September.
  • Handle: RePEc:sae:envirb:v:42:y:2015:i:5:p:888-903
    DOI: 10.1068/b130199p
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/b130199p
    Download Restriction: no

    File URL: https://libkey.io/10.1068/b130199p?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
    ---><---

    References listed on IDEAS

    as
    1. Rolf Moeckel, 2013. "Firm Location Choice Versus Job Location Choice in Microscopic Simulation Models," Advances in Spatial Science, in: Francesca Pagliara & Michiel de Bok & David Simmonds & Alan Wilson (ed.), Employment Location in Cities and Regions, edition 127, chapter 0, pages 223-242, Springer.
    2. Lovelace, Robin & Ballas, Dimitris & Watson, Matt, 2014. "A spatial microsimulation approach for the analysis of commuter patterns: from individual to regional levels," Journal of Transport Geography, Elsevier, vol. 34(C), pages 282-296.
    Full references (including those not matched with items on IDEAS)

    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. Dewulf, Bart & Neutens, Tijs & Vanlommel, Mario & Logghe, Steven & De Maeyer, Philippe & Witlox, Frank & De Weerdt, Yves & Van de Weghe, Nico, 2015. "Examining commuting patterns using Floating Car Data and circular statistics: Exploring the use of new methods and visualizations to study travel times," Journal of Transport Geography, Elsevier, vol. 48(C), pages 41-51.
    2. Hainan Huang & Yi Lin & Jiancheng Weng & Jian Rong & Xiaoming Liu, 2018. "Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    3. Sakai, Takanori & Beziat, Adrien & Heitz, Adeline, 2020. "Location factors for logistics facilities: Location choice modeling considering activity categories," Journal of Transport Geography, Elsevier, vol. 85(C).
    4. Izabela Rogalska, 2020. "Perception of Location Factors by Entrepreneurs and Representatives of Business Environment Institutions," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 600-613.
    5. Nicholas Fournier & Eleni Christofa & Arun Prakash Akkinepally & Carlos Lima Azevedo, 2021. "Integrated population synthesis and workplace assignment using an efficient optimization-based person-household matching method," Transportation, Springer, vol. 48(2), pages 1061-1087, April.
    6. Jiri Horak & Jan Tesla & David Fojtik & Vit Vozenilek, 2019. "Modelling Public Transport Accessibility with Monte Carlo Stochastic Simulations: A Case Study of Ostrava," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    7. Ruihong Huang, 2019. "Simulating individual work trips for transit-facilitated accessibility study," Environment and Planning B, , vol. 46(1), pages 84-102, January.
    8. Dianna M. Smith & Alison Heppenstall & Monique Campbell, 2021. "Estimating Health over Space and Time: A Review of Spatial Microsimulation Applied to Public Health," J, MDPI, vol. 4(2), pages 1-11, June.
    9. Kuehnel, Nico & Ziemke, Dominik & Moeckel, Rolf & Nagel, Kai, 2020. "The end of travel time matrices: Individual travel times in integrated land use/transport models," Journal of Transport Geography, Elsevier, vol. 88(C).
    10. Eveline van Leeuwen & Yoshifumi Ishikawa & Peter Nijkamp, 2016. "Microsimulation and interregional input–output modelling as tools for multi-level policy analysis," Environment and Planning C, , vol. 34(1), pages 135-150, February.
    11. Ma, Xiaolei & Liu, Congcong & Wen, Huimin & Wang, Yunpeng & Wu, Yao-Jan, 2017. "Understanding commuting patterns using transit smart card data," Journal of Transport Geography, Elsevier, vol. 58(C), pages 135-145.
    12. Stuart Donovan & Thomas de Graaff & Henri L.F. de Groot, 2023. "An inexact science: Accounting for measurement error and downward bias in mode and location choice models," Tinbergen Institute Discussion Papers 23-010/VIII, Tinbergen Institute.
    13. Jinjing Li & Yogi Vidyattama, 2019. "Projecting spatial population and labour force growth in Australian districts," Journal of Population Research, Springer, vol. 36(3), pages 205-232, September.
    14. Cathal O'Donoghue & Gijs Dekkers, 2018. "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 61-96.
    15. Krug, Jean & Burianne, Arthur & Bécarie, Cécile & Leclercq, Ludovic, 2021. "Refining trip starting and ending locations when estimating travel-demand at large urban scale," Journal of Transport Geography, Elsevier, vol. 93(C).
    16. Hadrien Salat & Dustin Carlino & Fernando Benitez-Paez & Anna Zanchetta & Daniel Arribas-Bel & Mark Birkin, 2023. "Synthetic population Catalyst: A micro-simulated population of England with circadian activities," Environment and Planning B, , vol. 50(8), pages 2309-2316, October.

    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:sae:envirb:v:42:y:2015:i:5:p:888-903. 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: SAGE Publications (email available below). General contact details of provider: .

    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.