Parkettecluster ·Walkable Mid-Rise Neighbourhood Parks (enclosure-leaning)Stonegate-Queensway (16)confidence moderatereal Toronto data

Bell Manor Park

Parkette, middle of the pack overall (score 33, rank ~46th percentile). Strongest: enclosure; weakest: edge activation.

Aerial — City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026

Bell Manor Park scores 33.3 / 100. Strongest dimensions: enclosure / eyes on park and connectivity. Weakest: edge activation (0). Border-vacuum risk is elevated (72). This score is a transparent reading of Jane Jacobs-style vitality factors — not a definitive judgment.

Best for:a quiet siteveryday neighbourhood use

Area · 0.85 ha

Vitality Score

33/100

Weighted across six dimensions · confidence 68%

Data Confidence

33.3 / 100

Citywide

46th

of all 3,273 parks

Among Parkette

51st

same primary typology

Expected for similar parks

median in small Parkette (n=218)

Performance gap

-3

raw − expected · context confidence high

typical

Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.

Explain this score

Where did the 33 come from? Each weighted contribution against a neutral 50 baseline. Green = pushed up; red = pulled down.

Download JSON

What pushed this score up or down vs a neutral 50weight × score

Edge Activation0 · p27

-12.5

Amenity Diversity12 · p73

-7.6

Enclosure / Eyes on Park93 · p98

+4.3

Connectivity62 · p78

+2.5

Border Vacuum Risk72 (risk)

-2.2

Natural Comfort42 · p42

-1.1

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

Bell Manor Park works because its enclosure score (93) is one of the city's strongest and its connectivity (62) is also top quartile (39 mid-rise buildings frame the edge with passive surveillance).

What limits this park

Bell Manor Park is held back by edge activation (0, below-average)— the surrounding streets carry too few active uses to spill into the park; border-vacuum risk is also elevated (72).

Most distinctive characteristic

Most distinctive feature: exceptionally high enclosure (93, top decile).

Jacobs reading

Bell Manor Park sits between an urban social park and an ecological retreat — moderately useful for both, exceptionally suited to neither.

Tradeoffs

The park is enclosed by buildings (93) but the surrounding streets are quiet (edge activation 0) — frame without animation.
High connectivity coexists with high border-vacuum risk (72) — much of that connectivity is to highways, rail, or parking lots, not to neighbourhoods.

Typology classification

confidence 70%

Parkette

Classified as Parkette: small (8535 m²) with strong building frontage (15.4 per 100 m)

Edge Activation

25% weightpartial 60%

0.0 / 100

Within 100 m of the park edge: 2 active uses (transit_stop) and 8 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

20% weightmeasured 85%

62.4 / 100

Connectivity blends paths, intersections, transit, entrances, and edge density. This park has 5 mapped paths/walkways and 12 sidewalk segments within 50 m; 6 street intersections within 100 m; 12 transit stops within a 400 m walk; 4 estimated access points across ~370 m of perimeter. edge density is healthy — no superblock penalty. Source coverage: centreline, pedestrian_network, transit_osm.

Streets within 25 m5

Intersections within 100 m6

Paths/walkways (50 m)5

Sidewalk segments (50 m)12

Transit stops (400 m)12

Estimated entrances4

Edge connections / 100 m perimeter1.35

Park perimeter370 m

Source: Toronto Centreline V2 + Pedestrian Network + OSM transit stops

Amenity Diversity

20% weightmeasured 75%

11.9 / 100

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

15% weightpartial 45%

42.4 / 100

Natural-comfort components for this park: ~7.0% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~400 m; 10 city-mapped trees inside the polygon (10.0/ha). Reading: exposed. Source coverage: waterbodies, street_trees. Impervious surface is approximated (Toronto's authoritative layer ships only as a raster GeoTIFF).

Canopy coverage0.0%

Canopy area0.00 ha

Inside ravine system0.0%

Water surface inside park0.0%

Nearest water (if outside park)400 m

Estimated green100.0%

City-mapped trees inside polygon10

Tree density10.0 / ha

Cover diversity (Shannon, 0–100)0.0

Sample points used58

Source: Toronto Treed Area + Ravine + Waterbodies + Street Tree Inventory

Enclosure / Eyes on Park

10% weightmeasured 80%

93.3 / 100

57 buildings within 25 m of the park edge (39 mid-rise, 18 low-rise, 0 tower); avg edge height 9.8 m (~3 floors); 15.4 buildings per 100 m of 370 m perimeter — strong frontage density; edges are at a Jacobs-scale walkable mid-rise (3–7 floors); no towers immediately adjacent. "Eyes on the park" come strongest from the 39 mid-rise edge buildings.

Buildings within 25 m57

Buildings within 50 m57

Avg edge height9.8 m (~3 floors)

Tallest edge building21.2 m

Mid-rise (3–7 floors)39

Low-rise (< 3 floors)18

Towers (≥ 13 floors)0

Frontage density15.42 per 100 m perimeter

Mid-rise share of edge68%

Tower share of edge0%

Blank-edge share (proxy)0%

Park perimeter370 m

Source: Toronto 3D Massing (building footprints + heights)

Border Vacuum Risk

10% weightpartial 60%

72.0 risk

Border-vacuum factors within 50 m of the park: parking_lot, parking_lot, parking_lot, parking_lot, 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

contextinferred 15%

50.0 / 100

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 (35)

parking lot8 m
parking lot17 m
parking lot24 m
parking lot28 m
parking lot37 m
parking lot41 m
parking lot62 m
transit stop — Berry Rd at Park Lawn Rd76 m
parking lot90 m
transit stop — Berry Rd at Park Lawn Rd90 m
parking lot103 m
parking lot108 m
parking lot116 m
transit stop123 m
parking lot133 m
parking lot136 m
parking lot138 m
parking lot140 m
parking lot140 m
parking lot140 m
parking lot143 m
parking lot144 m
transit stop — Cloverhill Road144 m
parking lot148 m
parking lot149 m
parking lot150 m
parking lot150 m
transit stop — Berry Rd at Park Lawn Rd156 m
parking lot164 m
transit stop — Park Lawn Rd at Kinsdale Blvd164 m
parking lot167 m
parking lot192 m
parking lot196 m
parking lot197 m
parking lot198 m

Park profile

Five-axis radar across the structural dimensions.

Citywide percentile ranks

Across all Toronto parks in the dataset.

Overall vitality
46th
Edge activation
27th
Connectivity
78th
Amenity diversity
73th
Natural comfort
42th
Enclosure
98th

Most similar parks

Closest in metric space across the five structural dimensions.

Mount Royal ParketteUrban Plaza40
Erwin Krickhahn ParkUrban Plaza40
Winchester ParkParkette40
Greenbelt ParkUrban Plaza40
John Chang Neighbourhood ParkUrban Plaza41

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 ParkWaterfront Park25
Rouge ParkRavine / Naturalized Park28
Mclevin Woods ParkRavine / Naturalized Park49

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 Bell Manor 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.
Increase canopy and reduce paved area. Shade and water features extend usable hours and seasons.
Mitigate border vacuums (highways, rail, parking) with active programming on the still-permeable edges and treat the hostile edge as a design challenge.

Data sources

City of Toronto Open Data — Parks (Green Space)
Polygon boundaries, official names, types.
Parks & Recreation Facilities
Inventory of in-park amenities (washrooms, fields, rinks…).
Toronto Pedestrian Network
Sidewalk segments around and through parks; estimated park entrances.
Toronto Centreline V2
Street segments + intersection nodes near park edges; trails and walkways.
Toronto 3D Massing
Building footprints + heights for edge-building counts, frontage density, and tower-in-the-park risk.
Toronto Treed Area
Tree canopy share inside park polygons via stratified-grid sampling.
Toronto Waterbodies & Rivers
Water surface inside parks + nearest-water distance for cooling.
Ravine & Natural Feature Protection
Ravine overlap as a cooling / natural-comfort signal.
Toronto Street Tree Inventory
Tree count + density inside park polygons.
Neighbourhood Profiles
(Pending) Equity context proxy.
OpenStreetMap (Overpass API)
Cafés, restaurants, retail, transit stops, parking, highways, rail.