
Budd Sugarman Park
Urban Plaza, middle of the pack overall (score 39, rank ~68th percentile). Strongest: enclosure; weakest: natural comfort.
Aerial, City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026
Budd Sugarman Park scores 38.8 / 100. Strongest dimensions: enclosure / eyes on park and connectivity. Weakest: edge activation (19). Border-vacuum risk is elevated (100). This score is a transparent reading of Jane Jacobs-style vitality factors, not a definitive judgment.
Area · 0.21 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.
Loading map…
The parks map is loading.Boundary: OpenStreetMap contributors (ODbL).
Explain this score
Where did the 39 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
Budd Sugarman Park works because its enclosure score (95) is one of the city's strongest and its amenity diversity (33) is also top quartile (25 mid-rise buildings frame the edge with passive surveillance).
What limits this park
Budd Sugarman Park is held back by natural comfort (35, bottom quartile): only 0% canopy means little summer shade; border-vacuum risk is also elevated (100).
Most distinctive characteristic
Most distinctive feature: exceptionally high enclosure (95, top decile).
Jacobs reading
Budd Sugarman Park sits between an urban social park and an ecological retreat: moderately useful for both, exceptionally suited to neither.
Tradeoffs
- Connectivity (63) significantly outpaces natural comfort (35): well placed in the city but offers little shade or ecological respite.
- The park is enclosed by buildings (95) but the surrounding streets are quiet (edge activation 19): frame without animation.
- High connectivity coexists with high border-vacuum risk (100): much of that connectivity is to highways, rail, or parking lots, not to neighbourhoods.
Typology classification
Classified as Urban Plaza: 2128 m², paved (0% canopy), 26.6 buildings/100 m
Edge Activation
Within 100 m of the park edge: 18 active uses (transit_stop, restaurant, cafe, retail) and 7 dead/hostile uses (rail, 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 21 sidewalk segments within 50 m; 15 street intersections within 100 m; 23 transit stops within a 400 m walk; 0 estimated access points across ~229 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
4 distinct amenity types in the park (bench, drinking_water, garden, picnic). 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: ~2.1% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~832 m; 3 city-mapped trees inside the polygon (3.0/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
61 buildings within 25 m of the park edge (25 mid-rise, 36 low-rise, 0 tower); avg edge height 11.3 m (~4 floors); 26.6 buildings per 100 m of 229 m perimeter (strong frontage density); edges are at a Jacobs-scale walkable mid-rise (3 to 7 floors); no towers immediately adjacent. "Eyes on the park" come strongest from the 25 mid-rise edge buildings.
Source: Toronto 3D Massing (building footprints + heights)
Border Vacuum Risk
Border-vacuum factors within 50 m of the park: Line 1 Yonge-University, parking_lot, Yonge Street, Yonge Street, Yonge Street, Yonge Street. 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 (4 types · 8 records)
- bench
- drinking water
- garden
- picnic
Nearby active-edge features (68)
- highway: Yonge Street9 m
- highway: Yonge Street10 m
- transit stop: Rosedale16 m
- transit stop: Belmont Street17 m
- transit stop: Rosedale21 m
- highway: Yonge Street28 m
- transit stop: Aylmer Avenue28 m
- cafe: Spring Cafe Bistro33 m
- rail: Line 1 Yonge-University47 m
- parking lot49 m
- highway: Yonge Street49 m
- rail: Line 1 Yonge-University51 m
- transit stop: Rosedale Station52 m
- retail: Christian Science Reading Room53 m
- retail: Pearl Alteration62 m
- transit stop: Crescent Road63 m
- transit stop: Crescent Road71 m
- transit stop: Cresecent Road Entrance73 m
- retail: Rosedale Computers74 m
- cafe: Spark Shop & Coffee77 m
- retail: Silver4U81 m
- restaurant: El Tenedor Restaurant Bar86 m
- transit stop: Frichot Avenue87 m
- restaurant: WeYonge93 m
- restaurant: Black Camel100 m
- retail: Way Young Tech Aesthetics101 m
- retail: Paris Grocery101 m
- retail: JDED Barber Shop105 m
- retail: Dogfather & Co108 m
- restaurant: uTea108 m
- retail: In Style Home & Rugs110 m
- retail: INS Market110 m
- restaurant: Monkey Sushi112 m
- highway: Yonge Street112 m
- restaurant: Rollstar Sushi113 m
- restaurant: Robot Boil House117 m
- retail: Clementine's118 m
- retail: Farideh Spa119 m
- retail: Lather & Steele121 m
- retail: Lather & Steel121 m
- retail: Dry Cleaners Plus124 m
- retail: Expedia Cruises128 m
- retail: colour lab128 m
- retail: Gentle Beau Cleaners131 m
- retail: House of Tea132 m
- restaurant: Tao Tea Leaf133 m
- restaurant: Subway138 m
- retail: Civello145 m
- parking lot146 m
- retail: Paul Hahn & Co.148 m
- retail: Tire Biter149 m
- retail: Owl Hearing153 m
- cafe: Coffee Lunar153 m
- retail: Shopnyla157 m
- restaurant: Happy Burger158 m
- highway: Yonge Street161 m
- retail: Coco Market164 m
- highway: Yonge Street169 m
- cafe: The Alaska169 m
- restaurant: Mineral171 m
- parking lot173 m
- restaurant: The Rebel House174 m
- retail: European Flooring177 m
- retail: James Perse180 m
- parking lot186 m
- retail188 m
- transit stop190 m
- parking lot200 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality68th
- Edge activation78th
- Connectivity81th
- Amenity diversity86th
- Natural comfort22th
- Enclosure99th
Most similar parks
Closest in metric space across the five structural dimensions.
- REGENT PARK COMMUNITY CENTRE - Building GroundsUrban Plaza48
- Gerrard - Carlaw ParketteUrban Plaza42
- Amsterdam SquareCivic Square48
- KEELE COMMUNITY CENTRE - Building GroundsOther49
- Alexander The Great ParketteUrban Plaza39
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 Park28
- Rouge ParkWaterfront Park25
- Rouge ParkRavine / Naturalized Park26
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 Budd Sugarman 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. 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.