Brussels Cycling Potential

Let’s use Open Data to find out which streets are under- or over-used by cyclists

Manuel Claeys Bouuaert
Thursday 17 November 2022
FOSS4G / State of the Map
Brussels, Belgium


I’m cycling through Brussels and wondering…


Is my mental map any good?

What would a map of generally useful streets look like?

Do people know and use the useful streets?


There’s Open Data on this!

Image Not Showing Possible Reasons
  • The image file may be corrupted
  • The server hosting the image is unavailable
  • The image path is incorrect
  • The image format is not supported
Learn More →

Adopted by Open Knowledge Belgium


What’s the question?

How does actual and predicted cycling compare for each street

In other words: are bikers taking the shortest, or unexpected routes?


What’s the plan?

  • Draw the actual trips from Open Data

  • Compute and draw predicted trips through each street

  • Compare both


QGIS features that make this possible


1) Computing all shortest paths

‘Betweenness Centrality’ from the GRASS tools!

Implemented as v.net.centrality


2) Extracting vertices from the network

Extract Specific Vertices in Processing Toolbox







3) Data geo-juggling

Smooth results to account for nearby parallel roads.

Then bring predicted trip count from nodes to (touching) edges.

Using Join attributes by location (summary), twice




4) Making data comparable using virtual field

Using a virtual field

(It's fast and light-weight)




Time to put it on the web

The mbtiles format is useful here.

Had to make them custom, using the FOSS tool tippecanoe.



link


What we find

  • Actual trips seem quite recreational

  • Predicted trips include long straight roads and clever connections

  • Comparison shows a.o. that chaussée/steenwegen are under-used


What do you see?


Caveats

  • The data is sparse, recreational and from willing donors.

  • The algorithm computes the simplest shortest paths and ignores alternatives.


How might we take this further?


Select a repo