BikeNodePlanner: A data-driven decision support tool for bicycle node network planning
- Anastassia Vybornova,
- Ane Rahbek Vierø,
- Kirsten Krogh Hansen,
- ,
- ,
- Dansk Kyst- og Naturturisme (DKNT),
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 1771-1780 (10 pages)Journal (Volume, Issue Number)
Environment and Planning B: Urban Analytics and City Science (Volume 52, Issue 7)Publication milestones
- Published - 09/2025
Publication status
Published - 09/2025
ISSN
2399-8083Publication IDs
- Scopus: 105013514535
Abstract
A bicycle node network is a wayfinding system targeted at recreational cyclists, consisting of numbered signposts placed alongside already existing infrastructure. Bicycle node networks are becoming increasingly popular as they encourage sustainable tourism and rural cycling, while also being flexible and cost-effective to implement. However, the lack of a formalized methodology and data-driven tools for the planning of such networks is a hindrance to their adaptation on a larger scale. To address this need, we present the BikeNodePlanner: A fully open-source decision support tool, consisting of modular Python scripts to be run in the free and open-source geographic information system QGIS. The BikeNodePlanner allows the user to evaluate and compare bicycle node network plans through a wide range of metrics, such as land use, proximity to points of interest, and elevation across the network. The BikeNodePlanner provides data-driven decision support for bicycle node network planning and can hence be of great use for regional planning, cycling tourism, and the promotion of rural cycling.
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Funding Details
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was support by the Danish Ministry of Transport, grant number: CP21-033
