Wexford Park
Ravine / Naturalized Park, above average overall (score 41, rank ~79th percentile). Strongest: amenity diversity; weakest: enclosure.
Photo by Michael M via Google Places · cached 5/9/2026
Wexford Park scores 40.9 / 100. Strongest dimensions: connectivity and enclosure / eyes on park. Weakest: edge activation (0). Border-vacuum risk is low. This score is a transparent reading of Jane Jacobs-style vitality factors — not a definitive judgment.
Area · 4.68 ha
Weighted across six dimensions · confidence 72%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
Street context
Park polygon highlighted on the citywide map. Connectivity, transit, and edge conditions read at a glance.
Top-down view
City of Toronto orthophoto, ~8 cm/px. Reads the park’s footprint, paths, treed area, and edge conditions from above.
City of Toronto Orthophoto · cot_ortho most-current MapServer
Explain this score
Where did the 41 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
Performance in context
- A modest overperformer for its ravine / naturalized park typology (+5 vs the median in medium Ravine / Naturalized Park ravine).
Typology classification
Classified as Ravine / Naturalized Park: 68% ravine overlap, 0% canopy. Secondary read: Neighbourhood Park (4.7 ha, framed by 0 mid-rise vs 0 towers).
Edge Activation
Within 100 m of the park edge: 0 active uses (none) and 1 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 10 mapped paths/walkways and 9 sidewalk segments within 50 m; 8 street intersections within 100 m; 7 transit stops within a 400 m walk; 6 estimated access points across ~968 m of perimeter. moderate edge density — small superblock penalty applied. 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 (picnic, playground, sports_field, washroom). 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: ~3.6% effective canopy (0.4% from contiguous tree polygons + scattered tree density); 68.3% inside the ravine system; nearest waterbody ~761 m; 24 city-mapped trees inside the polygon (5.1/ha). Reading: ravine-cooled. Source coverage: treed_area, ravine, 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
102 buildings within 25 m of the park edge (0 mid-rise, 102 low-rise, 0 tower); avg edge height 4.2 m (~1 floors); 10.5 buildings per 100 m of 968 m perimeter — strong frontage density; edges are barely there or single-storey; no towers immediately adjacent. "Eyes on the park" come strongest from the 0 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 (4 types · 4 records)
- picnic
- playground
- sports field
- washroom
Nearby active-edge features (3)
- parking lot0 m
- parking lot153 m
- parking lot196 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality79th
- Edge activation58th
- Connectivity71th
- Amenity diversity98th
- Natural comfort64th
- Enclosure26th
Most similar parks
Closest in metric space across the five structural dimensions.
- Iroquois ParkAthletic / Recreation Park40
- Fairhaven ParkCorridor / Linear Park36
- Fenside ParkAthletic / Recreation Park40
- Birchmount ParkNeighbourhood Park34
- Broadlands ParkAthletic / Recreation Park42
Most opposite parks
Furthest in metric space — useful for recognising what kind of park this isn’t.
- Market Lane ParkUrban Plaza63
- ALEX WILSON COMMUNITY GARDEN - Open Green SpaceUrban Plaza59
- Bernard Avenue Road AllowanceUrban Plaza54
- Ryerson Community ParkUrban Plaza60
- Manor Community GreenUrban Plaza57
Visitor signals
Public attention measured by Google Places aggregates. This proxies attention, not occupancy. Aggregate-only — no usernames, no review text, no extra photos beyond the cached hero.
p84 citywide · p82 within Ravine / Naturalized Park
Source: Google Places API · match high (0.97 composite confidence) · last refreshed 5/9/2026. Privacy contract. Measures public attention, not occupancy.
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 public attention / mentions. Source coverage: google-places.
Does this score feel accurate?
Your read of Wexford 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.