When we (Denis and Jens) got together for coffee the other day, Denis showed off some maps of renter density in the frequent transit network that he was working on. The idea immediately clicked and we decided to work this out together. Motivated by the issue of renter demoviction caused by the 2017 Metrotown Plan, we set out to quantify how one could plan for displacement on a regional level, instead of treating it as an unwelcome consequence of development at the lot level.
A friend of mine is looking for a new rental, which reminded me that I always wanted to do a quick map of rents near skytrain stations. Should not be too hard.
Skytrain station data
Mitchell Reardon asked me a question about lanes in the City of Vancouver: “Do you happen to have a figure (or quick way to calculate) the number of laneways in Vancouver, and the amount of space they take up?” I have looked at the overall space taken up by roads before using the Metro Vancouver land use dataset, but never looked just at lanes. But that’s easy enough to do thanks to the streets package in Vancouver’s Open Data Catalogue.
The other day I was catching a bus home later at night, which made me acutely aware that I should not take the frequent daytime transit in Vancouver for granted. On the ride home I decided to dig into this and grab some transit data. We have played with transit data before, but since this was going to be the second time it was high time for a quick R package to standardize our efforts and simplify things for the next time around.
Two days ago we took a first look at motor vehicle traffic counts, now it is time to turn to pedestrian lights. Everyone knows the “beg buttons” that pedestrians need to push for the pedestrian signal to turn green. If you forget to push the pedestrian light might stay red even if parallel motor vehicle traffic has a green light, all in the name of efficiency of motor vehicle traffic.