land use
After our recent posts on multi-census comparisons I was pointed to a semi-custom tabulation for census timelines back to 1971 for Vancouver and Toronto. That’s data for the 1971, 1981, 1986, 1991, 1996, 2001, 2006 and 2011 censuses on a common 2016 DA geography for the two CMAs. This is really cool, not just that it eliminates the need to tongfen the geographies, but in particular because Statistics Canada does not even haven publicly available geographic boundary files for censuses before 2001.
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.
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.
Last year we took a detailed look at Single Family teardowns in Vancouver, that is houses in RS or “Single Family” zoning that got torn down. We focused exclusively on those homes in RS zoning because these have to be replaced by another, often bigger, Single Family home. Using historical data we build a probabilistic model to predict future teardowns in Vancouver. If you haven’t taken the time yet to read through the data story, you probably should do that right now.
Jim has been using the Copernicus building height data for select European cities to understand the height profiles of cities. Building heights by distance from city centre in London and Paris, from 2012 EU Copernicus data. On average, buildings in Paris are taller throughout. pic.twitter.com/rtGiiBC7pd
— Jim Gleeson (@geographyjim) May 11, 2018 We thought these were pretty cool. Sadly we don’t have a dataset like this for Canadian metro areas, but we can hack together something similar using LIDAR survey data.
