
Charles Brereton Park
Parkette, in the top tier overall (score 48, rank ~93th percentile). Strongest: edge activation; weakest: natural comfort.
Photo by Tia via Google Places · cached 5/9/2026
Charles Brereton Park scores 48.2 / 100. Strongest dimensions: connectivity and enclosure / eyes on park. Weakest: amenity diversity (0). Border-vacuum risk is low. This score is a transparent reading of Jane Jacobs-style vitality factors, not a definitive judgment.
Area · 0.17 ha
Weighted across six dimensions · confidence 57%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
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Explain this score
Where did the 48 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
Charles Brereton Park works because its edge activation score (47) is in the top tier and its connectivity (66) is also top quartile.
What limits this park
Charles Brereton Park doesn't have a clear weakness. Every measured dimension is at or above the middle of the pack.
Most distinctive characteristic
Most distinctive feature: exceptionally high edge activation (47, top decile).
Jacobs reading
Charles Brereton Park sits between an urban social park and an ecological retreat: moderately useful for both, exceptionally suited to neither.
Performance in context
- This park is a strong overperformer for its cohort: raw 48 versus an expected 31 for similar parks (pocket Parkette) (gap +17).
Typology classification
Classified as Parkette: small (1730 m²) with strong building frontage (52.9 per 100 m)
Edge Activation
Within 100 m of the park edge: 10 active uses (retail, transit_stop, restaurant, cafe) and 2 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 12 sidewalk segments within 50 m; 8 street intersections within 100 m; 12 transit stops within a 400 m walk; 3 estimated access points across ~187 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
No amenities recorded. Score is 0 until inventory is loaded.
Source: Toronto Parks & Recreation Facilities + OSM amenity tags
Natural Comfort
Natural-comfort components for this park: ~11.9% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~1095 m; 17 city-mapped trees inside the polygon (17.0/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
99 buildings within 25 m of the park edge (0 mid-rise, 99 low-rise, 0 tower); avg edge height 6.0 m (~2 floors); 52.9 buildings per 100 m of 187 m perimeter (strong frontage density); edges are low-rise (mostly 2 to 3 floors); 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
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 (0)
No amenities recorded for this park.
Nearby active-edge features (27)
- transit stop3 m
- transit stop: Earlsdale Avenue24 m
- retail: Peter's Variety27 m
- cafe: Primose Bagel Co.32 m
- retail33 m
- parking lot51 m
- parking lot62 m
- retail63 m
- restaurant: Neiva's Sports Bar76 m
- retail81 m
- restaurant: Gabriel's Horn87 m
- retail: Oakwood Coin Laundry92 m
- retail: M. Ricci100 m
- restaurant: Nona Lia111 m
- retail: Yip's Fruit and Flower Market118 m
- transit stop: Earnscliffe Road136 m
- cafe: Oakwood Espresso139 m
- retail: Canada Tailoring142 m
- parking lot154 m
- retail156 m
- retail: Mor's Dollarama158 m
- parking lot162 m
- transit stop: Earnscliffe Road164 m
- retail: Sansa Bakery & Cafe165 m
- cafe: Mastro Cafe173 m
- restaurant: Domino's173 m
- retail: JR's Hair Studio191 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality93th
- Edge activation95th
- Connectivity85th
- Amenity diversity50th
- Natural comfort48th
- Enclosure61th
Most similar parks
Closest in metric space across the five structural dimensions.
- Don Panos ParketteParkette44
- City Wide Open SpaceCorridor / Linear Park46
- GEORGE SYME COMMUNITY SCHOOL - Building GroundsNeighbourhood Park42
- WATERFRONT NEIGHBOURHOOD CENTRE - Building GroundsWaterfront Park49
- Sanctuary Park CemeteryNeighbourhood Park42
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 Park26
- Rouge ParkRavine / Naturalized Park28
- Rouge ParkWaterfront Park25
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.
p48 citywide · p47 within Parkette
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: 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 Charles Brereton 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.
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.