In the last post we compared international city density patterns. While travelling and reading Alain Bertaud’s excellent book Order without Design I decided to slightly expand on the initial images and add bar graphs showing radial density to get an aggregate understanding of density patterns, as well as adding timelines to show how densities have developed over time. I am getting increasingly interested in modelling urban economics, and understanding and quantifying urban densities is a part of that.
I saw the tanaka package fly by on twitter, and in particular liked the application to the world population grid. Cities are interesting beasts, and I like exploring the extent of cities free from political boundaries. I am travelling right now, but I like looking at different ways to calculate and visualize density and could not resist running some inter-city density comparisons. For this, we only show areas with at least 4 people per hectare (or about 1000 people per square mile, the cutoff used by US Census to designate areas as urban), and pick some population density cutoffs above that to show grades of population density.
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.
Recently the City of Vancouver pivoted their planning for RS (“single family”) and RT (“duplex”) neighbourhoods from downzoning, to slow the pace of teardowns to adding infill as an incentive to to keep older buildings through extensive renovations, to now proposing the Making Room program to allow stratification and higher unit density, and Mayor Robertson adding an amendment to direct staff to look into also allowing multiplexes. This change in policy grew out of a series of consultation processes, and it is quite interesting to browse through them chronologically and observe the shift in how participants talk about low density zoning.
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.