J.A. Leslie Tot Lot
Urban Plaza, middle of the pack overall (score 30, rank ~31th percentile). Strongest: enclosure; weakest: natural comfort.
Aerial, City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026
J.A. Leslie Tot Lot scores 30.1 / 100. Strongest dimensions: enclosure / eyes on park and natural comfort. Weakest: edge activation (8). Border-vacuum risk is low. This score is a transparent reading of Jane Jacobs-style vitality factors, not a definitive judgment.
Area · 0.30 ha
What's here
Weighted across six dimensions · confidence 66%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
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The parks map is loading.Explain this score
Where did the 30 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
J.A. Leslie Tot Lot works because its enclosure score (84) is in the top tier and its edge activation (8) is also above-average (4 mid-rise buildings frame the edge with passive surveillance).
What limits this park
J.A. Leslie Tot Lot is held back by natural comfort (33, bottom quartile): only 0% canopy means little summer shade.
Most distinctive characteristic
Most distinctive feature: exceptionally high enclosure (84, top quartile).
Jacobs reading
J.A. Leslie Tot Lot is currently underperforming on both axes: neither integrated into the city nor offering deep natural respite. A candidate for design intervention.
Tradeoffs
- The park is enclosed by buildings (84) but the surrounding streets are quiet (edge activation 8): frame without animation.
Performance in context
- Reads as a modest underperformer relative to comparable parks (gap -11; cohort: small Urban Plaza).
- Citywide rank is high (31st) but typology rank is more modest (11th): the strength likely comes from the dataset average pulling lower than this typology’s baseline.
Typology classification
Classified as Urban Plaza: 3036 m², paved (0% canopy), 15.7 buildings/100 m
Edge Activation
Within 100 m of the park edge: 4 active uses (transit_stop) and 4 dead/hostile uses (parking_lot, highway). 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 0 mapped paths/walkways and 1 sidewalk segments within 50 m; 3 street intersections within 100 m; 13 transit stops within a 400 m walk; 0 estimated access points across ~306 m of perimeter. low edge density, significant superblock penalty applied. 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 (tennis). 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: ~1.4% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~1213 m; 2 city-mapped trees inside the polygon (2.0/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
48 buildings within 25 m of the park edge (4 mid-rise, 40 low-rise, 4 tower); avg edge height 9.4 m (~3 floors); 15.7 buildings per 100 m of 306 m perimeter (strong frontage density); edges are at a Jacobs-scale walkable mid-rise (3 to 7 floors); 4 towers ≥ 40 m within 25 m of the edge. "Eyes on the park" come strongest from the 4 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" that 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 (1 types · 1 records)
- tennis
Nearby active-edge features (16)
- parking lot22 m
- parking lot28 m
- transit stop45 m
- transit stop: Midland Ave at Park St60 m
- parking lot64 m
- transit stop65 m
- highway: Kingston Road91 m
- transit stop: Park St at Midland Ave94 m
- highway: Kingston Road109 m
- highway: Kingston Road109 m
- transit stop121 m
- highway: Kingston Road146 m
- parking lot170 m
- transit stop: Midland Avenue175 m
- highway: Kingston Road187 m
- highway: Kingston Road187 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality31th
- Edge activation67th
- Connectivity19th
- Amenity diversity57th
- Natural comfort17th
- Enclosure90th
Most similar parks
Closest in metric space across the five structural dimensions.
- EAST SCARBOROUGH STOREFRONT - Building GroundsUrban Plaza30
- Beaty Avenue ParketteUrban Plaza32
- Bedford ParketteUrban Plaza32
- Lucy Maud Montgomery ParkUrban Plaza33
- Long Branch Park & CenotaphCivic Square31
Most opposite parks
Furthest in metric space. Useful for recognising what kind of park this isn’t.
- Kew GardensNeighbourhood Park75
- Leslie Grove ParkParkette73
- Toronto ZooWaterfront Park67
- Bellevue Square ParkCivic Square73
- David Crombie ParkCorridor / Linear Park70
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 J.A. Leslie Tot Lotmatters. 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.
- Add or open more entrances and improve sidewalk continuity around the park. More permeability means more spontaneous use.
- 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. Boundaries are reconciled against OpenStreetMap (ODbL) for new and updated parks.
- 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.