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Arslan, M, Cruz, C, Roxin, A and Ginhac, D (2018) Spatio-temporal analysis of trajectories for safer construction sites. Smart and Sustainable Built Environment, 7(01), 80–100.

Bebelaar, N, Braggaar, R C, Kleijwegt, C M, Meulmeester, R W E, Michailidou, G, Salheb, N, van der Spek, S, Vaissier, N and Verbree, E (2018) Monitoring urban environmental phenomena through a wireless distributed sensor network. Smart and Sustainable Built Environment, 7(01), 68–79.

Brynskov, M, Heijnen, A, Balestrini, M and Raetzsch, C (2018) Experimentation at scale: challenges for making urban informatics work. Smart and Sustainable Built Environment, 7(01), 150–63.

Dritsa, D and Biloria, N (2018) Towards a multi-scalar framework for smart healthcare. Smart and Sustainable Built Environment, 7(01), 33–52.

Foth, M (2018) Participatory urban informatics: towards citizen-ability. Smart and Sustainable Built Environment, 7(01), 4–19.

Gholami, M, Mofidi Shemirani, M and Fayaz, R (2018) A modelling methodology for a solar energy-efficient neighbourhood. Smart and Sustainable Built Environment, 7(01), 117–32.

Haeusler, M H, Hespanhol, L and Hoggenmueller, M (2018) ParticipationPlus. Smart and Sustainable Built Environment, 7(01), 133–49.

Hussein, D, Sarkar, S and Armstrong, P (2018) Mapping preferences for the number of built elements. Smart and Sustainable Built Environment, 7(01), 53–67.

Muehlbauer, M (2018) Towards typogenetic tools for generative urban aesthetics. Smart and Sustainable Built Environment, 7(01), 20–32.

Nourian, P, Rezvani, S, Valeckaite, K and Sariyildiz, S (2018) Modelling walking and cycling accessibility and mobility. Smart and Sustainable Built Environment, 7(01), 101–16.

  • Type: Journal Article
  • Keywords: Social network analysis; Local betweenness centrality; Local closeness centrality; Radiation model; Spatial urban dynamics; Sustainable urban mobility;
  • ISBN/ISSN: 2046-6099
  • URL: https://doi.org/10.1108/SASBE-10-2017-0058
  • Abstract:
    The most sustainable forms of urban mobility are walking and cycling. These modes of transportation are the most environmental friendly, the most economically viable and the most socially inclusive and engaging modes of urban transportation. To measure and compare the effectiveness of alternative pedestrianization or cycling infrastructure plans, the authors need to measure the potential flows of pedestrians and cyclists. The paper aims to discuss this issue. Design/methodology/approach The authors have developed a computational methodology to predict walking and cycling flows and local centrality of streets, given a road centerline network and occupancy or population density data attributed to building plots. Findings The authors show the functionality of this model in a hypothetical grid network and a simulated setting in a real town. In addition, the authors show how this model can be validated using crowd-sensed data on human mobility trails. This methodology can be used in assessing sustainable urban mobility plans. Originality/value The main contribution of this paper is the generalization and adaptation of two network centrality models and a trip-distribution model for studying walking and cycling mobility.