Networks and Spatial Economics

, Volume 18, Issue 3, pp 657–676 | Cite as

Measuring the Impact of Street Network Configuration on the Accessibility to People and Walking Attractors

  • M. BielikEmail author
  • R. König
  • S. Schneider
  • T. Varoudis


A common approach to evaluating the quality of urban environments in terms of walkability is to measure the accessibility of walking attractors. For this purpose, the information on street network configuration and distribution of walking attractors is required. However, in the early planning stages when not all the necessary data on land use allocation is available, or if the knowledge about the walkability impact of the pure street network configuration is required, this approach is of little use. By addressing this deficiency, we developed method for predicting the accessibility of walking attractors only by using the information on the street network configuration. This method is based on the hypothesis that street network configuration influences how people move through space, and this in turn affects the allocation and accessibility of walking attractors. We empirically test this hypothesis in a case study of Weimar, Germany and found that street network configuration alone was significant and the strongest predictor of AWA. We show how street network influences the distribution of people in terms of pedestrian movement flows and that the access to these movement flows is highly correlated to the neighbourhood walkability. This highlights the importance of urban structure as an interface for social interaction and suggests the positive effect of social proximity on the quality of environment.


Street network Centrality Accessibility Walkability Walk Score 



This study was carried out as part of the research project ESUM - Analysing trade-offs between the energy and social performance of urban morphologies funded by the German Research Foundation (DFG) and Swiss National Science Foundation (SNSF).


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Bauhaus Universät WeimarWeimarGermany
  2. 2.ETH ZürichZürichSwitzerland
  3. 3.University College LondonLondonUK

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