
Woolner Park
Parkette, one of the city's strongest overall (score 51, rank ~96th percentile). Strongest: amenity diversity; weakest: enclosure.
Aerial — City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026
Woolner Park scores 50.6 / 100. Strongest dimensions: connectivity and enclosure / eyes on park. Weakest: edge activation (22.5). Border-vacuum risk is low. This score is a transparent reading of Jane Jacobs-style vitality factors — not a definitive judgment.
Area · 0.97 ha
Weighted across six dimensions · confidence 68%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
Explain this score
Where did the 51 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
- The park is enclosed by buildings (70) but the surrounding streets are quiet (edge activation 23) — frame without animation.
- Strong physical conditions (score 51) but weak observed activity signals (7) — the model says this should work, but events, mentions, and counters say it isn't being used at the level the urban form would predict.
- High connectivity (75) coexists with little programming evidence — easy to reach, but no recurring civic life detected.
Performance in context
- This park is a strong overperformer for its cohort — raw 51 versus an expected 36 for similar parks (small Parkette) (gap +15).
Typology classification
Classified as Parkette: small (9712 m²) with strong building frontage (19.8 per 100 m)
Edge Activation
Within 100 m of the park edge: 10 active uses (transit_stop, restaurant, retail) and 5 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 7 mapped paths/walkways and 36 sidewalk segments within 50 m; 9 street intersections within 100 m; 19 transit stops within a 400 m walk; 7 estimated access points across ~404 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
4 distinct amenity types in the park (basketball, dog_area, fitness, 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: ~30.8% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~483 m; 44 city-mapped trees inside the polygon (44.0/ha). Reading: partially shaded. Source coverage: waterbodies, 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
80 buildings within 25 m of the park edge (3 mid-rise, 77 low-rise, 0 tower); avg edge height 5.5 m (~2 floors); 19.8 buildings per 100 m of 404 m perimeter — strong frontage density; edges are barely there or single-storey; no towers immediately adjacent. "Eyes on the park" come strongest from the 3 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, 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 (4 types · 4 records)
- basketball
- dog area
- fitness
- playground
Nearby active-edge features (29)
- parking lot0 m
- retail — VN Nails Spare3 m
- retail — Express Coin Laundry6 m
- restaurant — 241 Pizza10 m
- retail — Wonderfood13 m
- retail — Vape Culture by 24x7 Vapes15 m
- transit stop — Woolner Avenue19 m
- parking lot21 m
- retail — Diaper & Gift Outlet36 m
- transit stop — Foxwell St at Jane St47 m
- transit stop — Foxwell Street53 m
- transit stop — Foxwell St at Jane St59 m
- parking lot65 m
- parking lot69 m
- parking lot79 m
- parking lot106 m
- transit stop — Pritchard Avenue127 m
- retail — S and A Variety Store127 m
- parking lot128 m
- transit stop — Pritchard Ave at Jane St133 m
- restaurant144 m
- transit stop — Pritchard Ave at Jane St144 m
- transit stop — Pritchard Avenue145 m
- parking lot146 m
- parking lot165 m
- parking lot165 m
- transit stop170 m
- parking lot184 m
- transit stop185 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality96th
- Edge activation79th
- Connectivity95th
- Amenity diversity96th
- Natural comfort73th
- Enclosure68th
Most similar parks
Closest in metric space across the five structural dimensions.
- Trethewey Park WestAthletic / Recreation Park51
- Westmount ParkNeighbourhood Park51
- East Lynn ParkNeighbourhood Park43
- Pearen ParkNeighbourhood Park40
- Bayview Village ParkRavine / Naturalized Park50
Most opposite parks
Furthest in metric space — useful for recognising what kind of park this isn’t.
- Toronto Islands - Muggs Island ParkRavine / Naturalized Park25
- Trca Lands ( 26)Ravine / Naturalized Park27
- Rouge ParkRavine / Naturalized Park21
- Rouge ParkRavine / Naturalized Park18
- Trca Lands ( 58)Waterfront Park18
Human activity signals
Programming, social attention, temporal rhythm, and nearby pedestrian / cycling flow. An experimental aggregate layer that complements the spatial scores — partial coverage, partial confidence.
Activity reading: no inputs available. The strongest signal is consistent rhythm across the day. Source coverage: google-places.
Does this score feel accurate?
Your read of Woolner Parkmatters. 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.
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.