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The metrics of street network connectivity: their inconsistencies

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  • Paul L. Knight
  • Wesley E. Marshall

Abstract

The concept of street connectivity has been gaining increasing appeal among researchers, planners, and planning authorities. In response, many connectivity metrics have been developed in an effort to understand better street network connectivity. This paper will study the effectiveness and consistency of three mainstream metrics - the Connectivity Index, Intersection Density, and Street Density - with respect to differences in study area and geometry. While these metrics are intended to be applied incrementally, this paper reveals that the metrics often fail to do this successfully. By controlling for many variables - including block size, block geometry, right-of-way size, network size, and network geometry - actual behaviors of these metrics deviate substantially from their intended behaviors. The metrics are non-linear functions of both study area and geometry and are ultimately inconsistent and unpredictable. In other words, each metric will yield inconsistent readings based upon the amount of area studied or the arrangement of the study boundary drawn. This has two major consequences: (1) the metrics will not produce the results desired as they are applied to incremental development; and (2) the metrics can be easily gamed by a developer privy to the information found within this paper. Neither of these outcomes is desirable in helping to better understand and potentially regulate street connectivity.

Suggested Citation

  • Paul L. Knight & Wesley E. Marshall, 2015. "The metrics of street network connectivity: their inconsistencies," Journal of Urbanism: International Research on Placemaking and Urban Sustainability, Taylor & Francis Journals, vol. 8(3), pages 241-259, September.
  • Handle: RePEc:taf:rjouxx:v:8:y:2015:i:3:p:241-259
    DOI: 10.1080/17549175.2014.909515
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Geoff Boeing, 2020. "Planarity and street network representation in urban form analysis," Environment and Planning B, , vol. 47(5), pages 855-869, June.
    2. 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.
    3. Benita, Francisco & Piliouras, Georgios, 2020. "Location, location, usage: How different notions of centrality can predict land usage in Singapore," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    4. Scoppa, Martin & Bawazir, Khawla & Alawadi, Khaled, 2019. "Straddling boundaries in superblock cities. Assessing local and global network connectivity using cases from Abu Dhabi, UAE," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 770-782.
    5. Ayse Ozbil & Tugce Gurleyen & Demet Yesiltepe & Ezgi Zunbuloglu, 2019. "Comparative Associations of Street Network Design, Streetscape Attributes and Land-Use Characteristics on Pedestrian Flows in Peripheral Neighbourhoods," IJERPH, MDPI, vol. 16(10), pages 1-23, May.
    6. Boeing, Geoff, 2020. "Off the Grid... and Back Again? The Recent Evolution of American Street Network Planning and Design," SocArXiv t9um6, Center for Open Science.
    7. Kian Wee Chen & Leslie Norford, 2017. "Evaluating Urban Forms for Comparison Studies in the Massing Design Stage," Sustainability, MDPI, vol. 9(6), pages 1-17, June.
    8. Choi, Dong-ah & Ewing, Reid, 2021. "Effect of street network design on traffic congestion and traffic safety," Journal of Transport Geography, Elsevier, vol. 96(C).
    9. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82, Center for Open Science.

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