Quote:
Originally Posted by O-tacular
I agree with everything you said.
I've come to appreciate the older brutalist type elements of Calgary's DT that I used to find ugly. They offer a nice counter balance to all of the glass towers.
But what really sets Calgary apart from many cities for me is the amount of natural parkland that we have. You can go to Fish Creek, Nosehill, Edworthy Park or the Inglewood bird sanctuary from deep inside the city and feel like you're in the middle of nature. We may suffer from urban sprawl but I'm proud of the legacy parks that have been preserved.
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Yes, agree on those points, I've also come to appreciate Edmonton's office towers from the 70's and 80's for the same reason.
Fish Creek is a fantastic park, one of the best I've been to in any city, you really do feel like you're in the middle of the forest with a nice river running through it. Plus plenty of picnic spaces, parking etc, never feels busy there.
Mind you that area of Calgary, heck all of Calgary is way overbuilt in terms of car infrastructure. That can be seen as a benefit as someone mentioned above in terms of little traffic congestion and ease of getting around. But here's an example close to Fish Creek. First off the actual residential streets are crazy wide, and below is a side street off a cul de sac and next to it is the main highway. Basically there is no traffic on this road, all the cars you see here were parked. Why is this so incredibly wide, what's the purpose?
Calgary - Woodbine, June 30, 2023 by
JohnnyJayEh, on Flickr
I'd like to see a ban on any future strip malls in Calgary with their eventual replacement of current ones by proper mixed use neighbourhoods. I think this will happen over time as we see in the big 3.
So I tried Chat GPT to ask about building density - some interesting insights and basically a guesstimate at best based on assumptions when pressed. I didn't want to follow the recommended approach as who has time for that, lol:
Quote:
What to use
1) Downtown boundaries (official + consistent across cities)
Statistics Canada defines “downtown neighbourhoods” (primary/secondary) and provides boundaries for all CMAs. Use these shapes so you’re comparing like with like.
2) Building geometry/attributes (per city)
Grab the city’s open building layers, clip to the downtown boundary, and compute total gross floor area (approx. footprint_area × number_of_storeys or footprint_area × height ÷ typical floor-to-floor).
Recipe (repeatable)
Load StatCan downtown polygon for your city (primary downtown).
Statistics Canada
Load building footprints; if the layer lacks storeys, bring in a height or storey estimate (from a 3D/massing layer or LiDAR-derived height).
Open Calgary
City of Vancouver Open Data Portal
Clip buildings to the downtown polygon.
Compute GFA per building:
If storeys exists: GFA = footprint_area × storeys.
If height exists: GFA ≈ footprint_area × (height ÷ 3.2 m) (adjust floor-to-floor as appropriate).
Sum all GFA, then divide by the land area of the downtown polygon → average FAR/FSI. (This is standard practice in planning; FAR = gross floor area ÷ site/area.)
Here are ballpark average FAR/FSI estimates (total building floor area ÷ downtown land area) for the city-defined downtowns. I’ve shown the simple math so you can tweak any assumption.
Vancouver (city “Downtown” local area)
Land area: ~3.7–3.8 km² (≈ 40.9M ft²).
Vancouver
Wikipedia
Office floor area (downtown only): ≈ 23.8M ft² (2022).
Storeys
Residential (quick proxy): pop. ~62,030 → ~38,770 dwellings (assuming 1.6 persons/household) × ~650 ft² avg unit ≈ 25.2M ft². (Population cited; household size & unit size are stated assumptions.)
Wikipedia
Add retail/hotel/institutional “other”: +~25% to cover non-office/non-residential floor area (assumption).
Result:
Without “other”: (23.8 + 25.2) = ~49.0M ft² → FAR ≈ 1.20 (49.0 / 40.9).
With +25% “other”: ~61.3M ft² → FAR ≈ 1.50.
Takeaway (Vancouver): FAR ≈ 1.2–1.5 depending on what you include.
Calgary (city “Downtown Calgary”)
Land area: ~6.0 km² (≈ 64.6M ft²).
Wikipedia
Office floor area (downtown only): ~42.8M ft² (CBRE Q1-2023; still a good order-of-magnitude anchor).
RENX
Residential (proxy): pop. ~38,663 → ~24,164 dwellings (1.6 persons/household) × ~750 ft² avg unit ≈ 18.1M ft². (Population cited; household size & unit size are assumptions.)
Wikipedia
Add retail/hotel/institutional “other”: +~25% (assumption).
Result:
Without “other”: (42.8 + 18.1) = ~60.9M ft² → FAR ≈ 0.94 (60.9 / 64.6).
With +25% “other”: ~76.2M ft² → FAR ≈ 1.18.
Takeaway (Calgary): FAR ≈ 0.95–1.2.
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So ChatGPT is using a larger downtown area for Calgary and a few other estimated variables. None of this really matters, I was just curious if there was an actual way to 'accurately' determine building density.
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