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Toronto Parks Atlas
R.V. Burgess Park, site photograph
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Neighbourhood ParkType:Walkable Mid-Rise Neighbourhood Park (enclosure-leaning)Thorncliffe Park

R.V. Burgess Park

Neighbourhood Park, middle of the pack overall (score 34, rank ~47th percentile). Strongest: amenity diversity; weakest: edge activation.

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Aerial, City of Toronto orthophoto, ~8 cm/px source · cached 5/9/2026

Data updated

R.V. Burgess Park scores 33.8 / 100. Strongest dimensions: enclosure / eyes on park and connectivity. Weakest: edge activation (0). Border-vacuum risk is elevated (96). This score is a transparent reading of Jane Jacobs-style vitality factors, not a definitive judgment.

Best fordaily urban lifefamilies

Area · 1.13 ha

What's here

Recreation
PlaygroundGarden
Facilities
Drinking waterPicnic areaBenches

Getting around

Paths

507 m of mapped path. Too little surface tagging to say how much is paved.

No steps mapped on the path network.

Seating

Typically 13 m to the nearest bench, and 33 m at the far end.

Arrival

Nearest parking 3 m away. None of the 29 nearby lots records whether it has accessible spaces.

Path, seating and parking data comes from OpenStreetMap and reflects what volunteers have mapped, not a survey. Absence here means nobody has recorded it. This section does not assess wheelchair access: the relevant OpenStreetMap tag is present on well under 1% of Toronto paths.

Vitality Score
34/100

Weighted across six dimensions · confidence 68%

Data Confidence
33.8 / 100

Data confidence: moderate

Citywide
47th
of all 3,753 parks
Among Neighbourhood Park
20th
same primary typology
Expected for similar parks
40
median in medium Neighbourhood Park (n=357)
Performance gap
-7
raw − expected · context confidence high
modest underperformer

Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.

Loading map…

The parks map is loading.
Street context. Park polygon highlighted on the citywide map.

Boundary: OpenStreetMap contributors (ODbL).

Explain this score

Where did the 34 come from? Each weighted contribution against a neutral 50 baseline. Green = pushed up; red = pulled down.

Download JSON
What pushed this score up or down vs a neutral 50weight × score
Edge Activation0 · p28
-12.5
Border Vacuum Risk96 (risk)
-4.6
Enclosure / Eyes on Park83 · p88
+3.3
Amenity Diversity39 · p90
-2.3
Natural Comfort43 · p41
-1.1
Connectivity55 · p68
+1.0

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

R.V. Burgess Park works because its amenity diversity score (39) is in the top tier and its enclosure (83) is also top quartile.

What limits this park

R.V. Burgess Park is held back by edge activation (0, below-average): the surrounding streets carry too few active uses to spill into the park; border-vacuum risk is also elevated (96).

Most distinctive characteristic

Most distinctive feature: exceptionally high amenity diversity (39, top decile).

Jacobs reading

R.V. Burgess Park sits between an urban social park and an ecological retreat: moderately useful for both, exceptionally suited to neither.

Tradeoffs

  • The park is enclosed by buildings (83) but the surrounding streets are quiet (edge activation 0): frame without animation.

Performance in context

  • Reads as a modest underperformer relative to comparable parks (gap -7; cohort: medium Neighbourhood Park).
  • Citywide rank is high (47th) but typology rank is more modest (20th): the strength likely comes from the dataset average pulling lower than this typology’s baseline.

Typology classification

confidence 70%
Neighbourhood Park

Classified as Neighbourhood Park: 1.1 ha, framed by 12 mid-rise vs 0 towers

Edge Activation

25% weightpartial 60%
0.0 / 100

Within 100 m of the park edge: 3 active uses (community, transit_stop) and 17 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: OpenStreetMap: cafes, restaurants, shops, schools, community centres, transit, parking, highways, rail. All data sources.

Connectivity

20% weightmeasured 85%
54.8 / 100

Connectivity blends paths, intersections, transit, entrances, and edge density. This park has 20 mapped paths/walkways and 17 sidewalk segments within 50 m; 1 street intersections within 100 m; 10 bus stops within a 400 m walk; 10 estimated access points across ~445 m of perimeter. low edge density, significant superblock penalty applied. Source coverage: centreline, pedestrian_network, transit_osm.

Streets within 25 m0
Intersections within 100 m1
Paths/walkways (50 m)20
Sidewalk segments (50 m)17
Transit stops (400 m)10 (0 subway/GO, 0 streetcar/LRT, 10 bus)
Estimated entrances10
Edge connections / 100 m perimeter0.00
Park perimeter445 m

Source: Toronto Centreline V2 + Pedestrian Network + OSM transit stops. All data sources.

Amenity Diversity

20% weightmeasured 75%
38.6 / 100

5 distinct amenity types in the park (playground, bench, drinking_water, garden, picnic). Diversity 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. All data sources.

Natural Comfort

15% weightpartial 45%
42.7 / 100

Natural-comfort components for this park: ~7.4% effective canopy (0.0% from contiguous tree polygons + scattered tree density); nearest waterbody ~445 m; 12 city-mapped trees inside the polygon (10.6/ha). Reading: exposed. Source coverage: waterbodies, street_trees. Impervious surface is approximated (Toronto's authoritative layer ships only as a raster GeoTIFF).

Canopy coverage0.0%
Canopy area0.00 ha
Inside ravine system0.0%
Water surface inside park0.0%
Nearest water (if outside park)445 m
Estimated green100.0%
City-mapped trees inside polygon12
Tree density10.6 / ha
Cover diversity (Shannon, 0 to 100)0.0
Sample points used78

Source: Toronto Treed Area + Ravine + Waterbodies + Street Tree Inventory. All data sources.

Enclosure / Eyes on Park

10% weightmeasured 80%
82.8 / 100

22 buildings within 25 m of the park edge (12 mid-rise, 10 low-rise, 0 tower); avg edge height 10.6 m (~4 floors); 4.9 buildings per 100 m of 445 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 12 mid-rise edge buildings.

Buildings within 25 m22
Buildings within 50 m22
Avg edge height10.6 m (~4 floors)
Tallest edge building15.8 m
Mid-rise (3 to 7 floors)12
Low-rise (< 3 floors)10
Towers (≥ 13 floors)0
Frontage density4.95 per 100 m perimeter
Mid-rise share of edge55%
Tower share of edge0%
Blank-edge share (proxy)0%
Park perimeter445 m

Source: Toronto 3D Massing (building footprints + heights). All data sources.

Border Vacuum Risk

10% weightpartial 60%
96.0 risk

Border-vacuum factors within 50 m of the park: parking_lot, parking_lot, parking_lot, parking_lot, parking_lot, parking_lot, 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: OpenStreetMap: highways, rail, parking. All data sources.

Equity Context

contextinferred 15%
50.0 / 100

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: Not loaded yet: Toronto Neighbourhood Profiles. All data sources.

Amenities (5 types · 23 records)

  • playground
  • bench
  • drinking water
  • garden
  • picnic

Nearby active-edge features (41)

  • parking lot3 m
  • parking lot9 m
  • parking lot9 m
  • parking lot10 m
  • parking lot12 m
  • parking lot16 m
  • parking lot28 m
  • community: Jenner Jean-Marie Community Recreation Centre32 m
  • parking lot33 m
  • parking lot56 m
  • parking lot58 m
  • parking lot62 m
  • parking lot64 m
  • parking lot67 m
  • parking lot68 m
  • parking lot71 m
  • community: Toronto Public Library - Thorncliffe73 m
  • parking lot75 m
  • parking lot94 m
  • transit stop: 56 Thorncliffe Park Drive97 m
  • parking lot102 m
  • transit stop: 44 Thorncliffe Park Drive107 m
  • parking lot108 m
  • parking lot111 m
  • school: Fraser Mustard Early Learning Academy116 m
  • transit stop: 49 Thorncliffe Park Drive122 m
  • transit stop: 75 Thorncliffe Park Drive123 m
  • school: Fraser Mustard Early Learning Academy125 m
  • parking lot135 m
  • transit stop: 38 Thorncliffe Park Drive137 m
  • parking lot144 m
  • parking lot147 m
  • transit stop: Grandstand Place152 m
  • transit stop: 35 Thorncliffe Park Drive156 m
  • parking lot173 m
  • parking lot173 m
  • parking lot173 m
  • parking lot176 m
  • parking lot182 m
  • parking lot195 m
  • transit stop: Milepost Place196 m

Park profile

Five-axis radar across the structural dimensions.

Edge ActivationConnectivityAmenity DiversityNatural ComfortEnclosureR.V. Burgess Park
Edge activation, connectivity, amenity diversity, natural comfort, and enclosure, each 0 to 100.

Citywide percentile ranks

Across all Toronto parks in the dataset.

  • Overall vitality
    47th
  • Edge activation
    28th
  • Connectivity
    68th
  • Amenity diversity
    90th
  • Natural comfort
    41th
  • Enclosure
    88th

Most similar parks

Closest in metric space across the five structural dimensions.

Most opposite parks

Furthest in metric space. Useful for recognising what kind of park this isn’t.

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 R.V. Burgess Park matters. 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.

Rate this park on as many dimensions as you have an opinion about. 1 = not at all, 5 = strongly. Skip the ones you don't feel sure about. Aggregated only, no comments stored at the row level.

feels socially active
feels comfortable
feels safe
feels connected
feels welcoming
feels ecological / natural
feels good for lingering
feels family-friendly
feels culturally important
70%

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

real Toronto data
  • City of Toronto Open Data: Green Spaces
    Polygon boundaries, official names, land classes. Boundaries are reconciled against OpenStreetMap (ODbL) for new and updated parks.
  • Parks & Recreation Facilities
    Inventory of in-park amenities (washrooms, fields, rinks…).
  • Toronto Pedestrian Network
    Sidewalk segments around and through parks; estimated park entrances.
  • Toronto Centreline V2
    Street segments + intersection nodes near park edges; trails and walkways.
  • Toronto 3D Massing
    Building footprints + heights for edge-building counts, frontage density, and tower-in-the-park risk.
  • Toronto Treed Area
    Tree canopy share inside park polygons via stratified-grid sampling.
  • Toronto Waterbodies & Rivers
    Water surface inside parks + nearest-water distance for cooling.
  • Ravine & Natural Feature Protection
    Ravine overlap as a cooling / natural-comfort signal.
  • Toronto Street Tree Inventory
    Tree count + density inside park polygons.
  • OpenStreetMap (Overpass API)
    Cafés, restaurants, retail, transit stops, parking, highways, rail.