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The influence of space syntax on cycling movement in Manta, Ecuador

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

Abstract

This study explores the effect of street network structure on cycling movement patterns in the city of Manta, Ecuador at street segment level, using crowdsourced information from STRAVA Metro and OpenStreetMap. Multiple linear regression models were used to determine the influence of the network structure on cycling activity when controlling for other variables such as household density, socioeconomic status, cycling infrastructure and topography. Also, the variation between weekday and weekend activities, and between commuting and sport cycling was explored. Results show positive significant correlations between STRAVA cycling activity volumes and Normalised Angular Choice weighted by segment length (sl_NACH) in the study area. The final regression model including the influence of the network structure for the overall number of cyclists explained 4.6% of the log-likelihood of the intercept model, which represents an important improvement compared with the base model (2.7%). The Incidence Rate Ratio for Normalised Angular Choice weighted by segment length at 4500m radii was 2.75, implying that for an increase of one standard deviation of (sl_NACH) above the mean, there is an expected increase of about 275% in cycling activity. These results are useful for modelling scenarios where cycling infrastructure use can be potentiated using the increase this Space Syntax measure as design guidance.

Original languageEnglish
StatePublished - 2019
Event12th International Space Syntax Symposium, SSS 2019 - Beijing, China
Duration: 8 Jul 201913 Jul 2019

Conference

Conference12th International Space Syntax Symposium, SSS 2019
Country/TerritoryChina
CityBeijing
Period8/07/1913/07/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Active mobility
  • Cycling movement patterns
  • Space syntax
  • Urban morphology

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