
Dundas - St.Clarens Parkette
Urban Plaza, in the top tier overall (score 47, rank ~92th percentile). Strongest: enclosure; weakest: natural comfort.
Aerial — City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026
Dundas - St.Clarens Parkette scores 46.9 / 100. Strongest dimensions: enclosure / eyes on park and connectivity. Weakest: amenity diversity (11.9). Border-vacuum risk is low. This score is a transparent reading of Jane Jacobs-style vitality factors — not a definitive judgment.
Area · 0.10 ha
Weighted across six dimensions · confidence 65%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
Explain this score
Where did the 47 come from? Each weighted contribution against a neutral 50 baseline. Green = pushed up; red = pulled down.
Sum of contributions = the headline score. A negative bar means that dimension dragged the park below the city-wide neutral baseline.
Why this park works
What limits this park
Most distinctive characteristic
Jacobs reading
Tradeoffs
- Connectivity (74) significantly outpaces natural comfort (38) — well placed in the city but offers little shade or ecological respite.
Performance in context
- A modest overperformer for its urban plaza typology (+11 vs the median in pocket Urban Plaza).
Typology classification
Classified as Urban Plaza: 1026 m², paved (0% canopy), 45.5 buildings/100 m
Edge Activation
Within 100 m of the park edge: 8 active uses (transit_stop, restaurant) and 4 dead/hostile uses (parking_lot). Active edges keep "eyes on the park" through the day; parking lots, blank institutional walls, rail and highway frontages drain street life.
Source: OSM POIs (amenity/shop) + Toronto Building Footprints + land use
Connectivity
Connectivity blends paths, intersections, transit, entrances, and edge density. This park has 6 mapped paths/walkways and 19 sidewalk segments within 50 m; 16 street intersections within 100 m; 20 transit stops within a 400 m walk; 3 estimated access points across ~145 m of perimeter. edge density is healthy — no superblock penalty. Source coverage: centreline, pedestrian_network, transit_osm.
Source: Toronto Centreline V2 + Pedestrian Network + OSM transit stops
Amenity Diversity
1 distinct amenity types in the park (playground). Diversity, not raw count, drives the score so a park with many distinct activity types can outrank a larger park that repeats the same use.
Source: Toronto Parks & Recreation Facilities + OSM amenity tags
Natural Comfort
Natural-comfort components for this park: ~5.6% effective canopy (0.0% from contiguous tree polygons + scattered tree density); 8 city-mapped trees inside the polygon (8.0/ha). Reading: exposed. Source coverage: street_trees. Impervious surface is approximated (Toronto's authoritative layer ships only as a raster GeoTIFF).
Source: Toronto Treed Area + Ravine + Waterbodies + Street Tree Inventory
Enclosure / Eyes on Park
66 buildings within 25 m of the park edge (13 mid-rise, 52 low-rise, 1 tower); avg edge height 8.7 m (~3 floors); 45.5 buildings per 100 m of 145 m perimeter — strong frontage density; edges are low-rise (mostly 2–3 floors); 1 tower ≥ 40 m within 25 m of the edge. "Eyes on the park" come strongest from the 13 mid-rise edge buildings.
Source: Toronto 3D Massing (building footprints + heights)
Border Vacuum Risk
Border-vacuum factors within 50 m of the park: parking_lot. Jacobs warned that highways, rail, parking lots and blank institutional edges act as "vacuums" — they suppress foot traffic and isolate the park from its neighbourhood.
Source: Toronto Street Centreline (highways) + rail layer + OSM landuse + building footprints
Equity Context
Equity Context requires inputs not yet loaded for this park (Toronto Neighbourhood Profiles). Score is held at a neutral 50 with low confidence — read with caution.
Source: Toronto Neighbourhood Profiles
Amenities (1 types · 1 records)
- playground
Nearby active-edge features (42)
- parking lot10 m
- transit stop — Lansdowne Avenue42 m
- restaurant — Acute Pizzeria44 m
- transit stop — Dundas Street West47 m
- parking lot62 m
- parking lot65 m
- transit stop — Dundas Street West South Side67 m
- transit stop — Dundas Street West80 m
- parking lot87 m
- restaurant — Bairradino Rotisserie & Grill89 m
- transit stop — College Street99 m
- transit stop — Lansdowne Avenue100 m
- transit stop101 m
- cafe — Tim Hortons108 m
- restaurant — Papa John's110 m
- parking lot114 m
- retail — Ultramar114 m
- parking lot118 m
- retail — Oscar's Auto Repairs118 m
- retail — S Market119 m
- retail — Salon Soap120 m
- retail — Savage Vape120 m
- restaurant — Subway121 m
- retail — College Vape123 m
- restaurant — Wallflower125 m
- transit stop — Lansdowne Avenue134 m
- transit stop — Lansdowne Avenue139 m
- parking lot148 m
- transit stop154 m
- transit stop — College Street155 m
- parking lot160 m
- retail — Real Coin Laundry164 m
- restaurant — Euro Sports Bar & Cafe167 m
- retail — De Floured Bakery172 m
- parking lot173 m
- restaurant — Town Wings175 m
- retail — The Proudest Pony Hair & Co.178 m
- rail — Newmarket Subdivision184 m
- parking lot184 m
- restaurant — Swan Dive194 m
- retail — Souvenir198 m
- rail — Weston Subdivision198 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality92th
- Edge activation84th
- Connectivity95th
- Amenity diversity78th
- Natural comfort31th
- Enclosure96th
Most similar parks
Closest in metric space across the five structural dimensions.
- Westmoreland Avenue ParketteUrban Plaza40
- Rita Cox ParkUrban Plaza45
- Victoria Memorial Square ParkCivic Square47
- Bob Acton ParkNeighbourhood Park49
- Stanley G. Grizzle ParkUrban Plaza46
Most opposite parks
Furthest in metric space — useful for recognising what kind of park this isn’t.
- Trca Lands ( 26)Ravine / Naturalized Park27
- Toronto Islands - Muggs Island ParkRavine / Naturalized Park25
- Rouge ParkRavine / Naturalized Park28
- Rouge ParkWaterfront Park25
- Rouge ParkRavine / Naturalized Park26
Human activity signals — not available
No activity signals have landed for this park yet. The model has scored its physical form but it can’t yet say how often it’s programmed, photographed, or walked through. See /data-ethics for what we will and will not collect.
Does this score feel accurate?
Your read of Dundas - St.Clarens Parkettematters. We’re testing whether the model lines up with how people actually use the park. Submissions are stored locally; no account needed.
Tell us how this park feels
We measure structure (canopy, edges, connectivity). You measure feeling. Both matter — and disagreement is itself useful civic data.
What would improve this park?
Generated from the weakest measured dimensions — a starting point, not a prescription.
- Activate the edges: encourage cafés, retail or community uses on the streets that face the park; replace blank or parking-lot edges where possible.
- Diversify what people can do in the park — playground, washroom, water, shade, performance, sport, garden — even small additions raise this score.
- Increase canopy and reduce paved area. Shade and water features extend usable hours and seasons.
Data sources
- City of Toronto Open Data — Parks (Green Space)Polygon boundaries, official names, types.
- Parks & Recreation FacilitiesInventory of in-park amenities (washrooms, fields, rinks…).
- Toronto Pedestrian NetworkSidewalk segments around and through parks; estimated park entrances.
- Toronto Centreline V2Street segments + intersection nodes near park edges; trails and walkways.
- Toronto 3D MassingBuilding footprints + heights for edge-building counts, frontage density, and tower-in-the-park risk.
- Toronto Treed AreaTree canopy share inside park polygons via stratified-grid sampling.
- Toronto Waterbodies & RiversWater surface inside parks + nearest-water distance for cooling.
- Ravine & Natural Feature ProtectionRavine overlap as a cooling / natural-comfort signal.
- Toronto Street Tree InventoryTree count + density inside park polygons.
- Neighbourhood Profiles(Pending) Equity context proxy.
- OpenStreetMap (Overpass API)Cafés, restaurants, retail, transit stops, parking, highways, rail.