ARCHIVES - TORONTO - Building Grounds
Parkette, middle of the pack overall (score 36, rank ~60th percentile). Strongest: enclosure; weakest: amenity diversity.
Aerial — City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026
ARCHIVES - TORONTO - Building Grounds scores 36.2 / 100. Strongest dimensions: enclosure / eyes on park and connectivity. 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 · 0.66 ha
Weighted across six dimensions · confidence 59%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
Explain this score
Where did the 36 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 (92) but the surrounding streets are quiet (edge activation 1) — frame without animation.
Typology classification
Classified as Parkette: small (6632 m²) with strong building frontage (13.4 per 100 m)
Edge Activation
Within 100 m of the park edge: 3 active uses (retail, transit_stop) and 4 dead/hostile uses (rail, 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 0 mapped paths/walkways and 12 sidewalk segments within 50 m; 8 street intersections within 100 m; 17 transit stops within a 400 m walk; 0 estimated access points across ~402 m of perimeter. moderate edge density — small superblock penalty applied. 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: ~14.0% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~963 m; 20 city-mapped trees inside the polygon (20.0/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
54 buildings within 25 m of the park edge (27 mid-rise, 27 low-rise, 0 tower); avg edge height 10.3 m (~3 floors); 13.4 buildings per 100 m of 402 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 27 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. 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
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 (42)
- parking lot0 m
- transit stop — Spadina Rd at Davenport Rd29 m
- transit stop — Spadina Road33 m
- rail52 m
- rail — North Toronto Subdivision56 m
- rail — North Toronto Subdivision60 m
- retail — Bruno Men's Hair Stylists85 m
- restaurant — The Backyard Smokehouse111 m
- retail — Polish Me Nails and Beauty Bar111 m
- transit stop — Northwest Entrance114 m
- retail114 m
- cafe — Wey Cup114 m
- retail — D&D Express Mart114 m
- restaurant — Subway114 m
- transit stop — Dupont Street114 m
- retail — XC Art Restoration114 m
- retail — Euphoria Cake and Dessert114 m
- retail — Bete Suk114 m
- restaurant — Casa Mezcal114 m
- transit stop — Dupont116 m
- transit stop — Dupont116 m
- parking lot116 m
- retail — Modern Laundry & Dry Cleaning117 m
- restaurant — Krispy Kreme121 m
- transit stop — Dupont St at Spadina Rd122 m
- rail126 m
- cafe — Ezra's Pound127 m
- transit stop — Dupont St at Spadina Rd139 m
- transit stop — Southeast Entrance141 m
- rail — North Toronto Subdivision145 m
- rail — North Toronto Subdivision148 m
- transit stop — Dupont Street150 m
- parking lot152 m
- restaurant — Roti Cuisine of India154 m
- transit stop — Davenport Rd at Walmer Rd159 m
- transit stop — Dupont St at Huron St164 m
- parking lot176 m
- parking lot176 m
- parking lot182 m
- transit stop — Dupont St at Huron St190 m
- parking lot194 m
- retail — Value Buds195 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality60th
- Edge activation64th
- Connectivity63th
- Amenity diversity36th
- Natural comfort54th
- Enclosure97th
Most similar parks
Closest in metric space across the five structural dimensions.
- St. Alban'S SquareCivic Square36
- MARJORY CARTON APARTMENTS - Building GroundsUrban Plaza33
- St. Michael'S CemeteryNeighbourhood Park27
- Maher Circle ParketteUrban Plaza36
- Park - Rosedale Traffic IslandRavine / Naturalized Park35
Most opposite parks
Furthest in metric space — useful for recognising what kind of park this isn’t.
- Toronto Islands - Island ParkWaterfront Park52
- Kew GardensNeighbourhood Park71
- Toronto Islands - Muggs Island ParkRavine / Naturalized Park25
- Trca Lands ( 26)Ravine / Naturalized Park27
- Rouge ParkWaterfront Park25
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 ARCHIVES - TORONTO - Building Groundsmatters. 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.