2021 Kitchener-Waterloo-Cambridge Population Density by Census Tract

What is this map?

This map projects the 2021 population density of the census tracts (CT) in the Kitchener-Waterloo-Cambridge census metropolitan area (CMA 541).

A census tract is a small geographic area with a population of usually (but not always) 2,500-7,500 people. Ideally, a CT is as compact as possible and its socioeconomic characteristics are as homogenous as possible. Census tracts appear in census metropolitan areas and the larger census agglomerations. Note that the Kitchener-Waterloo-Cambridge CMA includes only the urban, suburban, and exurban portions of the broader Waterloo Region. (Some rural areas have been tracted because they’re linked to the suburban/rural fringe either be geography or population.)

What do we see in this map?

Waterloo Region’s population density is higher – surprise surprise – in the core downtown Kitchener and uptown Waterloo neighbourhoods:

  • For Kitchener, much of its density is in its resurgent and compact downtown. This is common knowledge. The mapping of a single CT (54100017.00) over this geographically small area relative to its neighboring CT’s also accentuates the density of the downtown against the city’s original residential neighbourhoods, followed by its midcentury suburbs.
  • In Waterloo, there is a similar look and feel. Dwelling patterns along the midtown King St spine are more dense than the surrounding 1950s and ’60s suburbs. King Street’s density begins to increase further as you pass Union Street and move into CT 5410102.00. This tract includes the ongoing developments around Allen LRT, as well as recent growth around Wilfrid Laurier University, up to Noecker.  However, the larger spike appears between University and Columbia, moving westward from King: an area and CT where significant neighbourhood redevelopment and student highrise construction has taken place.
    • In both cases, I’m looking forward to getting my hands on population data at the dissemination area (DA) level and doing a comparison to 2016 to show the growth that has occurred in this region.

Whither Cambridge?

Oh Cambridge, you poor thing.  Suffering forever for a forced marriage of 3 townships in the 1970s. Galt, Preston, and Hespeler still show through on this map, if you know where to find them. The lack of dwellings in between the three towns still dominates the map, though – see CT 5410126.05 hugging Hespeler Road.

This is where I want to write about the region’s hopes for LRT-induced development in Cambridge, but without any real knowledge of Cambridge beyond the headlines in the papers, I’ll let others do the talking.  But if ever you’re in Galt, get me some Reid’s Chocolates and Monigram Coffee.   (“It’s worth the drive to Galt.”)

Will you always write so much about every map?

No.  I live in Waterloo Region, so I know a few things by having boots on the ground. It’s a lived experience, so take it for what you will. (Sorry that you had to scroll through all that, locals.)

Notes and Caveats

  • This map classifies census tracts by the Jenks classification method, in 7 categories.
  • Processed with QGIS and then exported to the web vis QGIS2WEB and leaflet.js. The base map is Stamen Toner.
  • I’m not a GIS expert.  I know StatCan better then most, but GIS is secondary for me. This is as good as or better than you’ll find in the local papers, but I’d bring in the pro’s if I ever planned to publish something. (and you should, too.)


Canada Population Growth, 2016 to 2021

What is this map?

This map shows Canada’s population growth in all its census divisions between 2016 and 2021 – the last two census years. Census divisions (CD’s) generally correspond to provincial regions, counties, and administrative areas. For example, Waterloo Region in Ontario is a census division, and so is Hants County in Nova Scotia. While many census divisions are simply numbered, their boundaries usually have real-world meaning since CD’s are essentially geographical divisions legislated by our provinces and territories.

What do we see in the map?

As expected, there is the usual growth in the suburbs around our population centres.  The usual suspects are here – the GTA in southern Ontario, the as-expected growth in Calgary, Edmonton, Vancouver’s lower mainland, etc. And, there is the typical negative, neutral, or nominal population growth in our rural, northern, and interior regions, e.g., compare northern Saskatchewan and northern Ontario to their southern counterparts.  Or, compare much of Newfoundland and Labrador and interior New Brunswick to regions with more prevalent cities and towns. The march of the nation’s peoples to the cities continue.

A Covid effect?

A potential outlier exists in the internal migration caused by Covid. We can’t confirm anything by this dataset alone (cf., taxfiler data and pending future census releases), but the growth around Halifax interests me. Halifax is a prosperous, thriving city, but I suspect the entire area has seen a bump in growth from Covid-related migration. Another potential example would be the growth in destination/resort and exurban areas beyond Toronto’s surburbs.  Collingwood is an example of this, and perhaps Windsor as well.  I’m sure many parts of Canada have examples like this.  How much of this growth is caused by Covid, and is permanent is too soon to tell.

Notes and Caveats

  • This map is based on actual Statistics Canada 2021 census data, as is the shapefile (i.e., the polygons)
  • This map is for illustrative purposes only.  I know the statistical data, but the most accurate representation on a map, you should go to a proper GIS expert.
    • Shading on the map is a comparison of population growth from one census division to another, across the country. (This can affect the representation of the census divisions and therefore is problematic.)
    • Including the north and interior regions in a map with all our population centres will skew the representation.  (This can affect the representation of the census divisions and therefore is problematic.)
  • This map uses a modified Jenks classification.  What this means is that the categories are automated by an algorithm that reduces the variance (or: increases the similarity) within the different classes of data while maximizing the variance between these classes.  I’ve modified two classes slightly to ensure that 0% change is a delineator.
    • See a decent plain language summary of the Jenks classification method here.

Southern Ontario Population Growth, 2016 to 2021

n.b. originally posted on exit278.ca.  Content transferred here with minor textual updates.)

I’m just going to park this here for now. This is a quick map showing population change from 2016 to 2021 in southern Ontario municipalities (i.e, census subdivisions). The division between “southern Ontario” and all else was a bit arbitrary, and the color range doesn’t bode well with the baselayer, but there are some interesting things here to discover all the same. Population change in the suburbs and exurbs is mad-high.  (e.g, Collingwood, Waterloo, Kitchener, Barrie area, Peterborough).  I suppose this confirms what the realtors were telling us about the covid.

Why the smattering of negative population growth?

You will see some red points here and there on the map. Note that many of these are IRI’s – First Nations/Indigenous communities.  Some of these geographies have very small populations, meaning that it doesn’t take much for a high-value population change (negative or positive) to occur.  And in some other cases, numbers were not reported in either 2016 or 2021, which leaves the value as null, causing the red mark.  I’ll fix this in a future update.

Future changes I’m thinking about

  • fixing the colour
    • [fixed. so long lime greens, hello cooler blues.  Stamen baselayer now works.)
  • all of Canada.  (comparatives won’t always be useful)
  • the increase in dwellings and of population in K-W CT’s.  (Watch the suburbs grow.)
    • Still TBD.  This would be its own map

Welcome back, blog.  I suppose i should match the content to the URL.