Walkability at Street Level: An Indicator-Based Assessment Model

Petra Stutz (), Dana Kaziyeva, Christoph Traun, Christian Werner and Martin Loidl
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Petra Stutz: Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria
Dana Kaziyeva: Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria
Christoph Traun: Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria
Christian Werner: Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria
Martin Loidl: Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria

Sustainability, 2025, vol. 17, issue 8, 1-19

Abstract: Walking is recognised as a healthy and sustainable mode of transport. Providing adequate infrastructure is pivotal for the promotion of walking and, subsequently, for achieving the benefits derived from its numerous positive effects. However, efficiently measuring the walkability at the street level remains challenging. In this paper, we present an indicator-based assessment model that can be used with open spatial data to evaluate segment-based walkability. The model incorporates eleven indicators describing the street segments and their close surroundings that are relevant for pedestrians, such as the presence and type of pedestrian infrastructure, road category, noise levels, and exposure to green and blue space. A weighted average calculation results in walkability index values for each street segment within a road network graph. The model’s generic approach and the ability to be used with open data ensure its reproducibility, adaptability, and scalability. The feasibility of the walkability model was shown using a case study for Salzburg, Austria. The model’s validity was evaluated through a large-scale study involving 660 full responses to an online survey. Participants provided ratings on the walkability of randomly selected street segments in Salzburg, which were compared with the calculated index, revealing a strong correlation (Spearman’s rank correlation = 0.82).

Keywords: walkability; GIS; segment-based; open data; built environment; indicator-based (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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