# BikeNetKit

_Better bike networks through data science_

Published: 2026-11-09

Live project: [bikenetkit.org](https://bikenetkit.org/)

Can open-source data tools accelerate the green transition of European cities? [BikeNetKit](https://bikenetkit.org) presents a suite of tools to grow, link and fix bicycle networks, based on cutting-edge research algorithms. The website features five interactive maps with precomputed results for 412 European cities, made for planners, cycling advocates and anyone who wants to argue for a better bike network in their town.

## Key visuals

- BikeNetKit logo and the line Open source tools to grow, link and fix bike networks on dark green, with screens of the website fanned out beside it
- BikeNetKit landing page: a proposed bicycle network for Turin drawn in green over the existing network in purple on a white map
- GrowBikeNet for Budapest with the schools focus: a dense green grid of proposed links around the centre, black dots marking the schools it grew from
- FixBikeNet for Copenhagen zoomed in on Knippelsbro, the top-ranked gap, with a panel listing the five most severe gaps
- superblockify for Barcelona: street blocks of the Eixample and Sarrià coloured in pastel green, blue, purple and orange, one colour per superblock
- LinkBikeNet for Budapest: the fragmented existing network in purple with the links that join it in green, and a chart of connectivity gain
- SortBikeNet for Paris: the planned network coloured from dark green (built first) to light (built last), with area-covered and built counters
- Landing page section with a map of the 412 covered cities, a city search, and one tile per tool asking its planning question
- Cities index with round map thumbnails for Aachen, Aalborg, Aarhus and other cities in alphabetical order

## From network science to planning tools

![BikeNetKit launch slide: the logo and the line Open source tools to grow, link and fix bike networks on dark green, with the landing page, a tool page and a GrowBikeNet map fanned out beside it]()

The [NERDS group](https://nerds.itu.dk/) at the IT University of Copenhagen has spent years on what they call the science of bicycle networks: algorithms that compute where a network should grow next, which gaps hurt most, how fragmented pieces connect best, and where calm neighbourhoods could be carved out of a street grid. The results lived in papers and in two early prototypes, [growbike.net](https://growbike.net) and [fixbike.net](https://fixbike.net).

Over 2026, I worked with Michael Szell and his team to turn this into a public platform. My part covered the concept and information architecture, the visual identity built around [Andreas Brietzke](http://brietzke.com/)'s logo, the design of the maps and tool interfaces, and the full front-end implementation, plus the tooling that renders screenshots and videos from the same code base.

![Learn, analyze and take action: the three cards of a tool page, with install instructions, the research paper and the Take action panel]()

## Maps for specific city-planning questions

Each tool answers one planning question, and each gets the same kind of page: a short explanation, the research paper behind it, instructions for running it on your own data, and the interactive results for the cities it covers.

- [GrowBikeNet](https://bikenetkit.org/growbikenet): where should a bike network grow, from scratch or from what already exists?
- [LinkBikeNet](https://bikenetkit.org/linkbikenet): how can the fragmented pieces of a network be joined up?
- [FixBikeNet](https://bikenetkit.org/fixbikenet): which gaps should be closed first?
- [SortBikeNet](https://bikenetkit.org/sortbikenet): in what order should a planned network be built? So far for Paris, where the plan can be played in different orders, including the one the city actually built.
- [superblockify](https://bikenetkit.org/superblockify): where could through-traffic be reorganised into calmer neighbourhoods?

![GrowBikeNet for Budapest with the schools focus: a dense green grid of proposed links around the centre, black dots marking the schools it grew from]()

The maps share one interaction model. All results are computed in advance by the Python tools. A timeline plays through the build order of a network step by step, while the legend and the kilometre counters update. Every segment carries a score from 1 to 10 for its importance, gap severity or connectivity gain, and the colour ramp follows that score. Settings in the sidebar switch between seed points (an even grid, rail stations, schools), ranking metrics (betweenness, closeness) and starting networks. 

![FixBikeNet for Copenhagen zoomed in on Knippelsbro, the top-ranked gap, with a panel listing the five most severe gaps]()

Every map can be downloaded as PNG, SVG or GeoJSON, opened as a data table, embedded in another site, and shared by URL, since city, tool and settings are all part of the address. A "Take action" panel links to the city's cycling organisations, the municipality and the national transport ministry, so that what you see on the map has somewhere to go.

![Which tool is right for your city? The landing page search card over a map of Europe with the covered cities as dots]()

![Cities index with round map thumbnails for Aachen, Aalborg, Aarhus and other cities in alphabetical order]()

![Tool coverage table: one row per city, one column per tool, with stars for recommended analyses and circles for available ones]()

## Visual language

![Hero still for Lyon: LinkBikeNet joining the fragmented existing network, with a monospaced readout of city, tool, metric and camera position in the corners]()

The design language for the project is documented on [bikenetkit.org/design](https://bikenetkit.org/design). This page renders every colour token, type setting and UI component from the same CSS the site runs on, so it cannot drift from what is deployed. There is also a coding-agent-friendly DESIGN.md and a design token file, which make it easy to use the design language in different contexts.

![Top of the BikeNetKit design system page with its download cards for the DESIGN.md spec and the design tokens as JSON]()

## Built to last

One requirement shaped most technical decisions: the site should work for years without maintenance. Accordingly, everything is pre-rendered, nothing loads from a third-party origin at runtime. Basemap tiles, fonts and map glyphs are self-hosted like all the GeoJSON files driving the maps. There are no cookies and no tracking scripts; usage statistics are done only from anonymized server logs.

The stack is [SvelteKit](https://svelte.dev/docs/kit) with Svelte 5 and Tailwind 4, [MapLibre GL JS](https://maplibre.org/) for the maps, a self-hosted [Protomaps](https://protomaps.com/) basemap as a single [PMTiles](https://github.com/protomaps/PMTiles). The site is open source under the AGPL and comes with documentation for adding a city, adding a tool and editing content, so the ITU team can run and extend it on their own. 

The code for the project was created using [Claude Code](https://claude.ai/).

![superblockify for Vienna: the whole city partitioned into superblocks in pastel green, blue, purple and orange]()

BikeNetKit was launched in November 2026. Explore the tools at [bikenetkit.org](https://bikenetkit.org/), read the [FAQ](https://faq.bikenetkit.org/) or browse the [code on GitHub](https://github.com/BikeNetKit).

## Credits

For [Michael Szell](https://michael.szell.net/) and the [NERDS](https://nerds.itu.dk/) research group at the IT University of Copenhagen. Logo: [Andreas Brietzke](http://brietzke.com/). Funded by Innovation Fund Denmark and the EU Horizon project JUST STREETS.

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