The Python package linkbikenet finds links between the disconnected components in a city's bicycle network. You can download street and bike network data with a single line of code, simulate different bicycle network linking scenarios, and export and plot the resulting prioritized linking steps.
Note
LinkBikeNet is currently in Beta: It is core-feature complete, stable to use, but could still contain bugs. More features and breaking changes may be added anytime. Please let us know if you find issues or ways to improve.
LinkBikeNet is a decision support tool for urban planners. It is also useful for proactive citizens to create a compelling vision for urban cycling in their city, and it aims to foster research on bicycle networks.
LinkBikeNet works well for cities that have some bicycle infrastructure in the form of disconnected components. This is the case for most cities in Europe. Recommended example cities to link components: Budapest, Dublin, Tirana
For alternative approaches, consider using GrowBikeNet or FixBikeNet.
The currently recommended way to install LinkBikeNet is using conda:
conda install linkbikenet
See our installation docs for details.
We provide a minimum working example in two formats:
- Python script (examples/mwe.py)
- Jupyter notebook (examples/mwe.ipynb)
Find more information in our docs: https://docs.bikenetkit.org/LinkBikeNet/
The source code builds on the code from the research paper Data-driven strategies for optimal bicycle network growth.
Publication: https://doi.org/10.1098/rsos.201130
If you use LinkBikeNet, please cite the paper:
L.G. Natera Orozco, F. Battiston, G. Iñiguez, M. Szell. Data-driven strategies for optimal bicycle network growth. Royal Society Open Science 7:201130 (2020) DOI: 10.1098/rsos.201130
Development of BikeNetKit/LinkBikeNet is supported by the Innovation Fund Denmark and the EU HORIZON project JUST STREETS.
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