IDEAS home Printed from https://ideas.repec.org/a/sae/inrsre/v43y2020i3p229-253.html
   My bibliography  Save this article

Size Distribution of Building Lots and Density of Buildings and Road Networks: Theoretical Derivation Based on Gibrat’s Law and Empirical Study of Downtown Districts in Tokyo

Author

Listed:
  • Hiroyuki Usui
  • Yasushi Asami

Abstract

The concept of density lacks the ability to explain the diversity of physical elements of urban form such as building lot sizes. Thus, urban planners tend to discuss the validity of density values without taking into consideration the variation of building lot sizes due to the limited data available on building lot shapes. Our objective is to discuss the potential of building density and road network density in order to estimate the size distribution of building lots at the district scale in downtown Tokyo. The study finds that (1) building lot sizes approximately follow the lognormal distribution whose parameters, mean, and variance are formulated by gross building density, the coefficient of variation of building lots, road network density, and average road width by removing large building lots and (2) the value of the coefficient of variation is approximately equal to one. As a practical problem, we discuss how to determine the maximum building density by considering the variation of building lot sizes. It was found that the maximum building density can be determined based on a stochastic approach. These findings are expected to provide urban planners with a theoretical basis for discussing the validity of density values.

Suggested Citation

  • Hiroyuki Usui & Yasushi Asami, 2020. "Size Distribution of Building Lots and Density of Buildings and Road Networks: Theoretical Derivation Based on Gibrat’s Law and Empirical Study of Downtown Districts in Tokyo," International Regional Science Review, , vol. 43(3), pages 229-253, May.
    • Handle: RePEc:sae:inrsre:v:43:y:2020:i:3:p:229-253
    DOI: 10.1177/0160017619826270
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0160017619826270
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0160017619826270?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. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    2. Xiaolu Gao & Yasushi Asami, 2005. "Estimating the Boundary Lines of Land Lots with a Multiobjective Optimization Approach," Environment and Planning B, , vol. 32(4), pages 581-596, August.
    3. Hiroyuki Usui, 2018. "Statistical distribution of building lot frontage: application for Tokyo downtown districts," Journal of Geographical Systems, Springer, vol. 20(3), pages 295-316, July.
    4. Legras, Sophie & Cavailhès, Jean, 2016. "Environmental performance of the urban form," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 1-11.
    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. Hiroyuki Usui, 2019. "Statistical distribution of building lot depth: Theoretical and empirical investigation of downtown districts in Tokyo," Environment and Planning B, , vol. 46(8), pages 1499-1516, October.
    2. Hiroyuki Usui, 2021. "Optimisation of building and road network densities in terms of variation in plot sizes and shapes," Environment and Planning B, , vol. 48(5), pages 1263-1278, June.
    3. Francesca Dal Cin & Martin Fleischmann & Ombretta Romice & João Pedro Costa, 2020. "Climate Adaptation Plans in the Context of Coastal Settlements: The Case of Portugal," Sustainability, MDPI, vol. 12(20), pages 1-19, October.

    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. Hiroyuki Usui, 2019. "Statistical distribution of building lot depth: Theoretical and empirical investigation of downtown districts in Tokyo," Environment and Planning B, , vol. 46(8), pages 1499-1516, October.
    2. Hiroyuki Usui & Joan Perez, 2022. "Are patterns of vacant lots random? Evidence from empirical spatiotemporal analysis in Chiba prefecture, east of Tokyo," Environment and Planning B, , vol. 49(3), pages 777-793, March.
    3. Hiroyuki Usui, 2021. "Optimisation of building and road network densities in terms of variation in plot sizes and shapes," Environment and Planning B, , vol. 48(5), pages 1263-1278, June.
    4. Hiroyuki Usui, 2018. "Statistical distribution of building lot frontage: application for Tokyo downtown districts," Journal of Geographical Systems, Springer, vol. 20(3), pages 295-316, July.
    5. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    6. He, Xiaoping, 2022. "Energy effect of urban diversity: An empirical study from a land-use perspective," Energy Economics, Elsevier, vol. 108(C).
    7. Denant-Boemont, Laurent & Gaigné, Carl & Gaté, Romain, 2018. "Urban spatial structure, transport-related emissions and welfare," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 29-45.
    8. Wagner, Roy, 2008. "On the metric, topological and functional structures of urban networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2120-2132.
    9. Ermal Shpuza, 2017. "Relative size measures of urban form based on allometric subtraction," Environment and Planning B, , vol. 44(1), pages 141-159, January.
    10. Lin, Jingyi, 2012. "Network analysis of China’s aviation system, statistical and spatial structure," Journal of Transport Geography, Elsevier, vol. 22(C), pages 109-117.
    11. Asya Natapov & Daniel Czamanski & Dafna Fisher-Gewirtzman, 2018. "A Network Approach to Link Visibility and Urban Activity Location," Networks and Spatial Economics, Springer, vol. 18(3), pages 555-575, September.
    12. David Levinson, 2012. "Network Structure and City Size," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-11, January.
    13. Blaudin de Thé, Camille & Carantino, Benjamin & Lafourcade, Miren, 2021. "The carbon ‘carprint’ of urbanization: New evidence from French cities," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    14. Basnak, Paul & Giesen, Ricardo & Muñoz, Juan Carlos, 2020. "Technology choices in public transport planning: A classification framework," Research in Transportation Economics, Elsevier, vol. 83(C).
    15. Zhao, Pengxiang & Jia, Tao & Qin, Kun & Shan, Jie & Jiao, Chenjing, 2015. "Statistical analysis on the evolution of OpenStreetMap road networks in Beijing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 59-72.
    16. Chunzhu Wei & Pablo Cabrera-Barona & Thomas Blaschke, 2016. "Local Geographic Variation of Public Services Inequality: Does the Neighborhood Scale Matter?," IJERPH, MDPI, vol. 13(10), pages 1-20, October.
    17. Jong In Baek & Yong Un Ban, 2020. "The Impacts of Urban Air Pollution Emission Density on Air Pollutant Concentration Based on a Panel Model," Sustainability, MDPI, vol. 12(20), pages 1-26, October.
    18. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82, Center for Open Science.
    19. David J Giacomin & David M Levinson, 2015. "Road network circuity in metropolitan areas," Environment and Planning B, , vol. 42(6), pages 1040-1053, November.
    20. Pavithra Parthasarathi & David Levinson & Hartwig Hochmair, 2013. "Network Structure and Travel Time Perception," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-13, 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:inrsre:v:43:y:2020:i:3:p:229-253. 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.