2016 Waterloo Region CMA Population Density (by Census Tract)

One of the variables from the StatCan’s 2016 Population and Dwelling Counts that always gets a lot of attention is population density. This map shows the density of the Waterloo Region Census Metropolitan Area (CMA) by Census Tract (CT). Note that the Waterloo Region CMA doesn’t include all of Waterloo Region; a CMA consists only urban and suburban areas.  Rural areas are not included.

Of no surprise, of course, is that the densest areas in Waterloo Region are the urban cores of Waterloo and Kitchener, as well as Cambridge.  A line of blue runs east-west along Victoria St, with DTK just to its south; one can see how higher density communities are found in the old core neigbourhoods (e.g., East Ward) as well as in the resurgent downtown itself.

A few notes here:

  • Some Census Tracts do not have data.  I’ve marked these in grey.  If you look at the table from StatCan and then try to plot them yourself, you will see these three gaps in the Waterloo Region CMA.  I haven’t found an official document yet, but I’m presuming that these three areas are suppressed for data quality and/or privacy concerns.  (i.e., low populations).  This is a common measure by StatCan.  StatCan will not release data that might jeopardize a respondent’s privacy and anonymity, and nor will it release poor data.
  • The Census Tract encompassing the University of Waterloo campus isn’t as dense as some expect it to be.  Recall that UW has a lot of land. And the census is enumerated in May. Even for a co-op-heavy school such as UW, this will have an effect on numbers.

Finally, note that I’m using census tracts here.  The CT is the most common geography to use when projecting numbers onto “neighbourhoods”.  CT’s have historic value since they’ve been employed for decades.  I’m interested to project this map in the future, however, with StatCan’s new level of geography, the aggregated dissemination area.  These are slightly larger than the CT, but I think they’ll give a better sense of community understanding than the CT can for medium-sized centres like Kitchener, which don’t have the density of the largest cities in Canada.

 

(view the map in full-screen here.)

On developing the map itself:

Kitchener-Waterloo-Cambridge Population Change, 2011 to 2016

Here’s the first in a series of maps on Kitchener-Waterloo and the greater Waterloo Region from the 2016 Census.   This map interprets population change per census tract between 2011 and 2016.  Click on the full-screen icon in the lower-right corner to get the full view.

Some notes, here.  Keeping in mind that we’re looking at population change:

  • I’ve rounded out the coloring on the high end and low end to take in account the outliers at both ends of the spectrum.  Some of the rural census tracts show a significant population change between censal years.  Double-digit percentage swings on low populations are more common than in geographies with higher populations.
  • There should be no surprise that the greatest positive change is occuring in the Waterloo and Kitchener cores.
    • Kitchener is benefiting from the redevelopment of its core, but it still has a ways to go in terms of residential
    • Waterloo near King and University is showing a significant positive change, given the construction of so much new housing in that area
  • Remember that a no-change or little-change population density census tract doesn’t mean progress or decline.  it just means no change.  A good example of this is in some of the old-stock neighbourhoods around uptown and downtown, where change is  sometimes minuscule. They might be right on the edge of the downtown/uptown core, but residential change can be hard to come by since the neighbourhoods are firmly established with single-dwelling units and households.

 

 

This map was developed with Tableau.  I used to hack out maps with leaflet.js but turned to Tableau to improve development times.  I’m not too happy with the speed in which it renders to the user, though.  A switch back to Leaflet may be in order.