James Trimbee Park
Urban Plaza, in the top tier overall (score 45, rank ~89th percentile). Strongest: connectivity; weakest: natural comfort.
Photo by Matthew Marsili via Google Places · cached 5/9/2026
James Trimbee Park scores 45 / 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 · 0.59 ha
Weighted across six dimensions · confidence 68%
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 45 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 (74) but the surrounding streets are quiet (edge activation 14) — frame without animation.
- Strong physical conditions (score 45) but weak observed activity signals (9) — 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.
Performance in context
- A modest overperformer for its urban plaza typology (+6 vs the median in small Urban Plaza).
Typology classification
Classified as Urban Plaza: 5894 m², paved (0% canopy), 38.6 buildings/100 m
Edge Activation
Within 100 m of the park edge: 1 active uses (transit_stop) and 0 dead/hostile uses (none). 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 8 mapped paths/walkways and 10 sidewalk segments within 50 m; 10 street intersections within 100 m; 19 transit stops within a 400 m walk; 7 estimated access points across ~342 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: ~19.6% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~569 m; 28 city-mapped trees inside the polygon (28.0/ha). Reading: exposed. 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
132 buildings within 25 m of the park edge (3 mid-rise, 129 low-rise, 0 tower); avg edge height 6.2 m (~2 floors); 38.6 buildings per 100 m of 342 m perimeter — strong frontage density; edges are low-rise (mostly 2–3 floors); 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
Park edges face the city — no significant border vacuum detected.
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 (19)
- transit stop — Wright Ave at Gibson Ave81 m
- parking lot117 m
- parking lot155 m
- transit stop — Jane St at Harding Ave160 m
- parking lot167 m
- parking lot169 m
- parking lot172 m
- transit stop — Wright Ave at Jane St183 m
- restaurant — Ola Restaurant186 m
- transit stop — Jane St at Harding Ave186 m
- retail — Oyato Food189 m
- retail — Koodo190 m
- retail — Belmont Super Variety190 m
- retail — Green Way Cleaners191 m
- retail — Diamond Cutz191 m
- retail — Adult 2 for 1191 m
- restaurant — Chicken Tender195 m
- retail — Pay2Day198 m
- parking lot198 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality89th
- Edge activation73th
- Connectivity90th
- Amenity diversity75th
- Natural comfort64th
- Enclosure75th
Most similar parks
Closest in metric space across the five structural dimensions.
- SWANSEA COMMUNITY RECREATION CENTRE - Building GroundsRavine / Naturalized Park41
- Henrietta ParkUrban Plaza44
- Elmbrook ParkNeighbourhood Park41
- June Callwood ParkCivic Square42
- Ferrand Drive ParkParkette44
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 ParkWaterfront Park25
- Rouge ParkRavine / Naturalized Park26
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.
p45 citywide · p33 within Urban Plaza
Source: Google Places API · match high (0.96 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 James Trimbee 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.