Traveltime routing & catchment extension for the QGIS IDF router
As announced in Salzburg a few days ago, I’m happy to present the lastest enhancement to my IDF router for QGIS: travel time routing and catchment computation.
Travel times for pedestrians and cyclists are computed using constant average speeds, while car travel times depend on the speed values provided by the road network data.
Catchment computations return the links that can be traversed completely within the given time (or distance limit). The current implementation does not deal with links at the edge of the catchment area, which can only be traversed partially.
Loading the whole network (2.7GB unzipped IDF) currently requires around 10GB of memory. One of the next plans therefore is to add a way to only load features within a specified bounding box.
Plans to turn this into a full-blown plugin will most likely have to wait for QGIS 3, which will ship with Python 3 and other updated libraries.
Free and Open Source GIS Ramblings 
That’s awesome! I was woundering how do you plan to deal with edges traversed partially? (As I’m facing the same issue with pgrouting).
Anyway great work!
Planning on making it a plugin for the future QGIS is pretty exiting and will continue to make this software an incredible versatile tool. (Indeed the network algorithms from Grass are effective but not always easy to approach)
Hi Gabriel,
Using the QGIS API, it should be rather straightforward to find out how much time/distance is left and compute the possible partial traversals. It would be easier with a “normal” routing graph though than with the IDF routing graph which is slightly more complex since it models turn restrictions.
It´s great paper, you took like geography of perception , isn´t it?
Thank you Nestor! I assume you’re referring to my previous post https://anitagraser.com/2016/07/12/videos-and-slides-from-fossgis-agit-osgeo-day/, right? I read quite a lot of papers describing how pedestrians navigate and found that current technology is still rather lacking. It’s great to see that so many people are now working on this topic.
great job