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Street network analysis “edge effects†: Examining the sensitivity of centrality measures to boundary conditions

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  • Jorge Gil

Abstract

With increased interest in the use of network analysis to study the urban and regional environment, it is important to understand the sensitivity of centrality analysis results to the so-called “edge effect†. Most street network models have artificial boundaries, and there are principles that can be applied to minimise or eliminate the effect of the boundary condition. However, the extent of this impact has not been systematically studied and remains little understood. In this article we present an empirical study on the impact of different network model boundaries on the results of closeness and betweenness centrality analysis of street networks. The results demonstrate that the centrality measures are affected differently by the edge effect, and that the same centrality measure is affected differently depending on the type of network distance used. These results highlight the importance, in any study of street networks, of defining the network's boundary in a way that is relevant to the research question, and of selecting appropriate analysis parameters and statistics.

Suggested Citation

  • Jorge Gil, 2017. "Street network analysis “edge effects†: Examining the sensitivity of centrality measures to boundary conditions," Environment and Planning B, , vol. 44(5), pages 819-836, September.
  • Handle: RePEc:sae:envirb:v:44:y:2017:i:5:p:819-836
    DOI: 10.1177/0265813516650678
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    1. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
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    Cited by:

    1. 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.

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