METROPOLITAN UNITED CHURCH GROUNDS - Building Grounds
Parkette, one of the city's strongest overall (score 51, rank ~96th percentile). Strongest: edge activation; weakest: natural comfort.
Photo by Karl Desjardins via Google Places · cached 5/9/2026
METROPOLITAN UNITED CHURCH GROUNDS - Building Grounds scores 51.4 / 100. Strongest dimensions: enclosure / eyes on park and edge activation. 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 · 0.61 ha
Weighted across six dimensions · confidence 59%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
Street context
Park polygon highlighted on the citywide map. Connectivity, transit, and edge conditions read at a glance.
Top-down view
City of Toronto orthophoto, ~8 cm/px. Reads the park’s footprint, paths, treed area, and edge conditions from above.
City of Toronto Orthophoto · cot_ortho most-current MapServer
Explain this score
Where did the 51 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
- 44 nearby towers cast wind and shadow without contributing canopy — passive surveillance is plentiful but human-scale comfort is not.
- Strong physical conditions (score 51) but weak observed activity signals (9) — the model says this should work, but events, mentions, and counters say it isn't being used at the level the urban form would predict.
Performance in context
- This park is a strong overperformer for its cohort — raw 51 versus an expected 36 for similar parks (small Parkette) (gap +15).
Typology classification
Classified as Parkette: small (6091 m²) with strong building frontage (30.5 per 100 m)
Edge Activation
Within 100 m of the park edge: 29 active uses (restaurant, retail, cafe, transit_stop) 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 0 mapped paths/walkways and 18 sidewalk segments within 50 m; 12 street intersections within 100 m; 34 transit stops within a 400 m walk; 0 estimated access points across ~414 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: ~7.7% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~1262 m; 11 city-mapped trees inside the polygon (11.0/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
126 buildings within 25 m of the park edge (67 mid-rise, 15 low-rise, 44 tower); avg edge height 36.8 m (~12 floors); 30.5 buildings per 100 m of 414 m perimeter — strong frontage density; edges lean tall but still framed; 44 towers ≥ 40 m within 25 m of the edge. "Eyes on the park" come strongest from the 67 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 (80)
- parking lot22 m
- retail — Henry's Outlet Centre23 m
- retail — Queen's Own Bakery23 m
- retail — Crown Variety & Snack24 m
- retail — McTamney's24 m
- transit stop — Queen Street East27 m
- restaurant — McDonald's33 m
- retail — Zara Spa & Hair Studio37 m
- restaurant — Druxy's Famous Deli44 m
- transit stop — Church Street48 m
- restaurant — T.C.J. Restaurant50 m
- restaurant — Subway53 m
- cafe — Second Cup60 m
- retail — Deals 4 U62 m
- retail — Downtown Camera65 m
- retail — UnideLuxe66 m
- restaurant — A&W68 m
- retail — Jewellery Plus Pawnshop70 m
- parking lot70 m
- retail — Evershine Print & Parcel73 m
- retail77 m
- retail — Beauty & Health Spa80 m
- restaurant — Hawthorne Food & Drink82 m
- retail — Royal Dry Cleaners82 m
- restaurant — Wild Wing84 m
- restaurant — The Carbon Bar85 m
- retail — Jacob Mercari88 m
- retail — Illy95 m
- retail — Henry's96 m
- retail — No Frills97 m
- retail — AAA Diamonds100 m
- cafe — Tim Hortons103 m
- restaurant — McVeigh's105 m
- restaurant — Makilala110 m
- cafe — Mast Coffee112 m
- parking lot116 m
- restaurant — Domino's119 m
- restaurant — Bob's Bulgogi121 m
- retail — Friends Convenience & Grocery125 m
- restaurant — Lighthouse Shisha Lounge129 m
- restaurant — Booster Juice137 m
- retail — Rabba140 m
- cafe — Starbucks140 m
- restaurant — La Bettola Di Terroni145 m
- restaurant — Subway151 m
- retail — International News154 m
- retail — Gateway Newsstands154 m
- retail155 m
- retail — Urban Philosophy158 m
- retail — Sweetgrass160 m
- transit stop — Entrance by 2 Queen Street East164 m
- parking lot165 m
- restaurant — Batch166 m
- cafe — Starbucks167 m
- restaurant — Subway168 m
- restaurant — Portico169 m
- retail — Parsian Fine Foods171 m
- retail — Zeglio Custom Clothiers171 m
- restaurant — Fran's Restaurant175 m
- parking lot177 m
- retail — A & E Optical179 m
- retail — Addition Elle180 m
- restaurant — Salus181 m
- retail — Panemor181 m
- community — Toronto Met Catholics182 m
- cafe — Timothy's183 m
- restaurant — Martini Bar185 m
- restaurant — Yeti Kitchen187 m
- retail — Butterfield and Robinson Travel188 m
- restaurant — Booster Juice189 m
- transit stop — Entrance from One Queen Street East (via PATH)190 m
- retail — My Legacy Cannabis190 m
- retail — Ben McNally192 m
- retail — TireSource193 m
- transit stop — Yonge / Queen Northeast Corner194 m
- retail — Elapra Shoes195 m
- parking lot195 m
- parking lot196 m
- restaurant — Gyu-Kaku197 m
- retail — Queen & Jarivs Vape Shop197 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality96th
- Edge activation99th
- Connectivity77th
- Amenity diversity44th
- Natural comfort38th
- Enclosure76th
Most similar parks
Closest in metric space across the five structural dimensions.
- Toronto Sculpture GardenUrban Plaza52
- Trinity SquareCivic Square55
- OLD CITY HALL - Building GroundsCivic Square53
- Prescott ParketteUrban Plaza48
- City Wide Open SpaceRavine / Naturalized Park51
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
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.
p69 citywide · p74 within Parkette
Source: Google Places API · match medium (0.75 composite confidence) · last refreshed 5/9/2026. Privacy contract. Measures public attention, not occupancy.
Human activity signals
Programming, social attention, temporal rhythm, and nearby pedestrian / cycling flow. An experimental aggregate layer that complements the spatial scores — partial coverage, partial confidence.
Activity reading: no inputs available. The strongest signal is public attention / mentions. Source coverage: google-places.
Does this score feel accurate?
Your read of METROPOLITAN UNITED CHURCH GROUNDS - 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.
- 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.