Abstract

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies Cycling has been considered a viable option to generate a modal shift from fossil dependent transportation modes. In this framework, measurements and tools that aid connected bicycle infrastructure planning have been developed. This is the case of the Bicycle Network Analysis score, a connectivity measure adapted for the U.S. It is based on the Levels of Traffic Stress methodology and computed mainly with OpenStreetMap data. Its aim is to quantify how well the low-stress bicycle network in a city connects people with the places they want to go. For this research, the BNA open source tool is adapted to a European context to validate its ability of quantifying low-stress connectivity. Three core elements are evaluated: stress network, destinations, and the overall score itself. They are related to cycling behaviors from two validation data sources: travel to work data in England and Wales, and crowdsourced bicycle trip routes in The Netherlands. The results indicate that in England and Wales, there is a significantly higher percentage of bicycle trips performed between origin-destination pairs with a low-stress connection between them. Additionally, a positive correlation is found between the percentage of bicycle trips within a city and its overall BNA score. In the Dutch case, the destinations core element is evaluated, determining that the destinations contemplated in the BNA score calculation are also among the highly frequented by cyclists. However, their importance within the score computation might require adjustments. Although a comprehensive validation cannot be achieved due to data limitations, evidence that providing low-stress connections between origins and destinations relates to bicycle commuting in cities is found. Therefore, special attention should be given to those measures that can greatly benefit the decision-making process when planning for sustainable cities.


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Published on 01/01/2019

Volume 2019, 2019
Licence: CC BY-NC-SA license

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