Map of Paris: Visualizing Urban Transportation

Update: If you are interested in isochronic maps, I have more detailed explaination of the process in my graduate thesis Seeing Differently: Cartography for Subjective Maps Based on Dynamic Urban Data, and the source code (Processing) is on GitHub.

What is your mental map of a city? I bet it’s not measured in miles. This project is part of my work in the SENSEable City’s workshop this semester. In these distorted maps of Paris, the distance between a spot and the city center is not proportional to their geographical distance, but the cost taken to get there.

Standard map vs. driving time map of Paris: the city center expands from congestion, and the edge is denser.

Comparing the isochronic map of Paris under different transportation modes: (unit: minutes, click to zoom in)

Think driving is better? However, if we map the city using carbon footprint as distance: (unit: kg CO2, click to zoom in)

In the workshop I proposed an alternative to Google Maps on smartphone map services. I call it an isogreenic map. This would have a psychological influence on the user when he decides which transportation makes the trip easier:

Made with Processing.
Vector map:
Connection data: Google Directions,

A demo video that shows how the transformation works:

15 Replies to “Map of Paris: Visualizing Urban Transportation”

    1. Thanks! Do you know how the system measures the pollution level of a given route? What is the resolution of their data and is it updated real-time?
      We had a similar project the Copenhagen Wheel last year, using crowd sourcing to monitor fine-grid environment quality of the city.

  1. Hi,

    It’s wonderfull what you have done, but I think the sources are not quitte good. Eg: from Louvre to Massy(91) it takes me 1h on sunday by bicycle, by N20. And I’m not Lance Armstrong !
    So, the ideea is excellent, but pay attention to sources.

    Ty !

  2. hi there, I saw your map on visualcomplexity.
    I’m really impressed by your work !
    Do you take traffic jam/density into account for the time calculation ?
    I imagine it’s difficult but possible to work this out with GPS in the area or something like that.

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