Sometimes I'll hear people in Toronto talk pejoratively about all of the development that's been happening at Yonge & Eglinton (in midtown). They'll say it's too much density.

But then you come across charts like the ones above (source previously shared here) and you realize that this location is the only section along the new Eglinton Crosstown LRT line that is actually starting to have enough people.

Based on 2021 Census data, there were about 40k people within 800m of the future Eglinton and Mount Pleasant stations. In contrast, there are many downtown stations along the Ontario Line (also under construction) with around 80k people.

Why this is important is because if the objective is to get people to ride this new transit and collect a lot of fares, then the single most important factor is going to be the amount of people that live, work, and play adjacent to each station.

Now, I'm not a transportation planner, but in my mind there are three simple ways to think and go about optimizing for this:

1. You can look at where population densities are already high and then add new transit to service these densities. This is what is happening with the Ontario Line and it was long overdue. We know that ridership is going to be relatively high because of the chart at the top of this post.

2. You can look at where there's existing transit and then work to optimize the land uses around it. This is what we should be doing a better job of along the Bloor-Danforth line, where certain station areas have actually lost people over the last few decades. This is the opposite of what you want next to transit investments.

3. Lastly, you can also proactively plan new transit while simultaneously encouraging more density. An example of this would be the Vaughan Metropolitan Centre (just north of Toronto). Extend the line and encourage growth. This is good. The only thing with this approach is that it can seem a bit misaligned if you're currently failing at #1 and #2.

This is a telling map from Jens von Bergmann. It shows the changes in population density across Toronto from 1971 to 2021 (measured in people per hectare). What is obvious is the spikiness of our city. We have been very effective at adding lots of people downtown, along the central waterfront, and in certain other pockets. But at the same time, we have let our older inner city neighborhoods move in the opposite direction and lose people.

The irony of this outcome is that we have long created policies that refer to these areas as being "stable" neighborhoods. The idea was that they weren't supposed to change, at least not too much. But what this data shows is the opposite. By restricting growth, we actually created the right conditions for them to lose people as demographics changed and household sizes got smaller, among other things. We created unstable neighborhoods.

Thankfully, we have started to change course and allow some intensification. We're not there yet, but I do believe that the next 50-year map will look quite different than the one you see here.

Boy, population densities can be so misleading. The typical approach is to just take the number of people and divide it by a given area. This then gives you something like X number of "people per square kilometer." The problem with this approach is that there are countless factors that can skew your result.

Hong Kong, for instance, is really dense. But as a city, it also has a lot of green space, mountains, and other undeveloped areas. Only about a quarter of Hong Kong's land is developed. So when you divide total people by its administrative boundary area, it is going to appear less dense than it really is.

One alternative approach is to use a method known as population-weighted density. The way this works is that you take the average densities of smaller more granular subareas and then weight them by the population of each subarea. It is a little more complicated to calculate, but the overall intent is to try and capture a density figure that more accurately reflects what the average person experiences on the ground.

And this is exactly the method that Jonathan Nolan decided to use in his new website CityDensity.com. What his site allows you to do is compare population-weighted densities across various cities, and then see how it tapers off as you move outward from their city centers.

Once again, it is hard to beat Paris' supremely dense mid-rise built form:

Well, that is, until you check out Hong Kong:

Charts: CityDensity.com