Live Scorecard · refreshed weekly from open data City Cycling Index · Methodology v19

City of Sydney

A live, open-data readiness scorecard for cycling in your city — built from OpenStreetMap and WorldPop, assessed using a consistent global methodology, and refreshed as the map changes.

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Overview

Map of the exact area scored, drawn over the street network Scored on: Municipality.
Live · Scorecard · refreshed weekly from open data Leading infrastructure

City of Sydney

A live, open-data readiness scorecard for cycling in your city — built from OpenStreetMap and WorldPop, assessed using a consistent global methodology, and refreshed as the map changes.

geoBoundaries administrative footprint
Enclosed area 27 km²
8446 residents/km²

Study area


The exact area scored

geoBoundaries administrative footprint
Enclosed area 27 km²
8446 residents/km²

Dimensions


How City of Sydney scores

Coverage
83
Connectivity
77
Access
95
Amenities
100
Activation layer pending.

Lever to improve


Priority actions.

Strongest asset: Amenities
Primary constraint: Heat resilience
Top screening candidate (local validation required): Pine Street
Heat resilience (77)
Connectivity (77)
Connectivity — Close the highest-severity missing links

Eight dimensions, four of them scored

How City of Sydney scores

The Infrastructure Provision score rests on open data alone. What our riders experience — ridership, safety and time lost at intersections — is measured separately, so the benchmark can never be flattered by who happens to use our app.

Infrastructure — open data
Measured from OpenStreetMap and WorldPop. These make up the Infrastructure Provision score.
Coverage
83
Connectivity
77
Access
95
Amenities
100
Riding experience — our riders' trips
Measured from Party Onbici rides. Never part of the Infrastructure Provision score.
Ridership
—
Safety
—
Intersection wait
—
Context — not scored
Shown beside the score as evidence, never inside it.
Heat resilience
77
Riding experience pending. These switch on as enough Party Onbici riders cover the city — intersection wait needs 10 signalised junctions, each ridden by at least 3 different riders. They join the full composite; the Infrastructure Provision score is unaffected either way. Heat resilience is shown as evidence and is never scored either: canopy and building shade are measured per 25 m of network, but a city is never ranked up or down for having trees. It sits beside the score, not inside it.
Calm streets beyond the mapped network — descriptive, not scored. 52% of this city's ordinary streets carry no posted speed limit in OpenStreetMap, and a street is never assumed calm — so the figures below are a floor, not a total. Of the streets that could be judged, 167.6 km assess as calm enough for everyday cycling (traffic stress LTS 1–2), beyond the mapped cycle network the score measures. 130.7 km of that rests on a posted speed limit; 36.9 km is calm by structure — car-free and living streets. Whether these streets connect into usable routes is not assessed, and nothing here enters any score.
Infrastructure Provision — weekly trend

How confident is each part?

BoundaryHigh

Municipality — The scored polygon IS one published administrative feature, cited by its own geoBoundaries shapeID, so its identity rests on that citation rather than on a measurement against a municipal-tier feature.

Infrastructure classificationMedium

76% of network length carries an explicit separation tag · 24% was inferred from route and access attributes · 0% is unclassified.

Population accessMedium

Residents within 300 m of traffic-free infrastructure — an off-street path or a physically protected lane (ITDP's definition) — from WorldPop gridded population. Composition: the traffic-free network behind it is 22 km separated cycleway and 78 km path shared with pedestrians (78% shared). Capped at the confidence of its weakest essential input (Infrastructure classification).

AmenitiesMedium

Counts reliably represent amenities mapped in OpenStreetMap, but mapping completeness has not been independently validated for this city.

Corridor topologyLow

Largest-connected-component analysis of the low-stress network. 9 of 17 prioritised corridors are stored as multi-part geometries (up to 5 separate pieces), so they are not continuous on the ground and the corridor geometry on this page cannot be treated as validated.

Economic benefitScenario estimate

A modelled scenario (conservative to ambitious uptake), not a measured outcome — see ROI assumptions.

Where City of Sydney sits

Every city is scored the same way. Rankings follow.

#23 of 385

City of Sydney's rank among the 385 comparably scored study areas in this assessment set

Scored on: Municipality.

The index is computed identically for every scored city, so your position against peers is a consistent comparative baseline. Compare against neighbours, cities your size, or the other study areas assessed alongside yours.

Scores for other cities update weekly as their maps change; a city needs a comparable dimension set to appear in a cohort.

Nearby cities · Infrastructure Provisionof 100
  • 23 City of Sydney This city
    85
  • 122 North Sydney (NSW)
    50
  • 143 Inner West (NSW)
    45
  • 170 Waverley (NSW)
    40
  • 182 Woollahra (NSW)
    38
Similar population · Infrastructure Provisionof 100
  • 23 City of Sydney This city
    85
  • 197 Pickering (GHSL 3167)
    37
  • 199 Penrith (NSW)
    36
  • 258 Abu Dhabi
    27
  • 282 Cinco Ranch (GHSL 6114)
    22
Rolling, dense municipal cores · Infrastructure Provisionof 100
  • 23 City of Sydney This city
    85
  • 26 Freiburg im Breisgau (GHSL 2756)
    85
  • 130 Neuquén (GHSL 2410)
    49
  • 184 Bern
    38
  • 276 Sarajevo (GHSL 426)
    24

#2 of 21 rolling, dense municipal cores with 150,000–300,000 residents

Comparable study areas — 384 eligible assessments · Infrastructure Provisionof 100
  • 1 Lund (GHSL 699)
    99
  • 2 Oulu (GHSL 269)
    99
  • 21 Aarhus
    86
  • 22 Odense (GHSL 410)
    86
  • 23 City of Sydney This city
    85
  • 24 Aalborg (GHSL 72)
    85
  • 25 Paris
    85

14 points behind Lund (GHSL 699) — the priority corridors below identify potential opportunities to strengthen the network.

Benchmark lenses

City of Sydney seen through the world's cycling frameworks

Unofficial estimates computed from open data, inspired by ITDP, PeopleForBikes, CROW, Can-BICS and BikeDNA. Each lens abstains where the data can't support a reliable number — abstentions never lower the score.

BNA-inspired low-stress connectivity Data confidence: High
77%
near any route
near largest

101 separate low-stress islands; largest 97 km of 126 km. 99% of residents live near any low-stress route, 84% near the largest network.

Bike Score-style partial estimate Data confidence: Medium
infrastructure 100 · destinations 100
infrastructure
destinations

2 of 4 components computable (infrastructure, destinations), shown as separate figures; hills and commute mode share excluded, and no composite is printed — a partial mean is not comparable to an official Bike Score

CROW-style quality profile Data confidence: High
partial diagnostic — 3 of 5 axes
Cohesion: goodDirectness: poorSafety: not assessedComfort: goodAttractiveness: OSM tags too sparse
Can-BICS-style comfort split Data confidence: High
22 km high-comfort

22 km high (separated) · 89 km medium (shared) · 13 km low (painted)

Dedicated infrastructure (protected only) Data confidence: Medium
22 km · 18% of network

Physically protected infrastructure only — the strictest definition, the one a council's own inventory counts. A disclosure, never a scoring input: cycling on calm streets, or legal sidewalk riding in some countries, sits outside this model. 69% of residents live within 300 m of it.

Data quality (BikeDNA-inspired) Data confidence: Medium
87% surface-tagged

2,307 mapped ways · 100% classified · OSM data 0 days old

Broad catchment (any cycleway) Data confidence: High
100% within 800 m of any cycle infrastructure

Residents within 800 m of any cycle infrastructure — a generous upper bound

Benchmark lenses are unofficial estimates computed by Party Onbici from open data, inspired by the named frameworks. They are not official ITDP, PeopleForBikes, Bike Score, CROW or Can-BICS results.

Grey tiles and "not assessed" chips are deliberate abstentions, not errors: each lens declines to estimate where open data cannot support a reliable number. Abstentions never lower a city's scores.

One dataset, read through several framings — every result our own estimate A single source node on the left holds this city's open data. Arrows fan out from it to one row per benchmark lens, each of which re-reads that same data through another framework's framing and produces an unofficial Party Onbici estimate. Every arrow points away from the data; nothing points back into it, because no third-party score is imported. ONE DATASET This city's open data OpenStreetMap WorldPop measured once, on our own boundary An unofficial estimate computed by Party Onbici from open data. It is not ITDP People Near Bikelanes's published score, and it is not endorsed by them. Party Access (traffic-free) Our estimate, framed after ITDP People Near Bikelanes An unofficial estimate computed by Party Onbici from open data. It is not PeopleForBikes Bicycle Network Analysis's published score, and it is not endorsed by them. BNA-inspired low-stress connectivity Our estimate, framed after PeopleForBikes Bicycle Network Analysis An unofficial estimate computed by Party Onbici from open data. It is not Walk Score Bike Score's published score, and it is not endorsed by them. Bike Score-style estimate Our estimate, framed after Walk Score Bike Score An unofficial estimate computed by Party Onbici from open data. It is not CROW Design Manual for Bicycle Traffic's published score, and it is not endorsed by them. CROW-style quality profile Our estimate, framed after CROW Design Manual for Bicycle Traffic An unofficial estimate computed by Party Onbici from open data. It is not Canadian Bikeway Comfort and Safety (Can-BICS)'s published score, and it is not endorsed by them. Can-BICS-style comfort split Our estimate, framed after Canadian Bikeway Comfort and Safety (Can-BICS) Party Onbici's own diagnostic, computed from open data. Dedicated infrastructure (protected only) Our own diagnostic, computed from open data An unofficial estimate computed by Party Onbici from open data. It is not BikeDNA's published score, and it is not endorsed by them. BikeDNA-inspired data quality Our estimate, framed after BikeDNA Party Onbici's own diagnostic, computed from open data. Broad catchment Our own diagnostic, computed from open data No published third-party score is imported Every figure above is computed by Party Onbici, from the data on the left
A lens re-reads our own open data through another framework's framing, so a city can be seen under several methodologies at once instead of trusting one number. Each result is an unofficial estimate computed by Party Onbici, labelled "-style" or "-inspired" where it names the framework it borrows from; none of them reproduces, replaces or is endorsed by anybody's published score.
How each lens is computed, and why it is an estimate

Candidate areas requiring local validation

Automated screening shortlist for City of Sydney

Drawn from OpenStreetMap and WorldPop via our ROI model, then put through an automated screen. Each shortlisted corridor closes a real gap in today's network and leads with its modelled annual benefit potential — indicative health benefit and running-cost savings; new-cyclist and CO₂ figures span a conservative to an ambitious uptake scenario. Passing the screen is not a recommendation to build.

7 of the 20 corridor candidates in this report pass the automated screening gate. Their combined overlap-adjusted modelled health-benefit range is AUD 828,287 – AUD 4,978,329/year (WHO HEAT). 10 of them carry a modelled health figure.

1,470 candidate network discontinuities detected before screening · 203 consolidated corridor candidates created from them · 12 consolidated candidates cleared the automated screening gate city-wide · 20 are carried into this report, 7 of them passing

Missing linkBike lane Existing network

Estimates from OpenStreetMap & WorldPop via the Party Onbici ROI model — indicative figures for prioritisation, not a substitute for detailed design. Resident catchments are estimated from the population and network analysis; uptake, health, cost and carbon results are scenario estimates.

Figures are in AUD (2026 prices). Cross-city monetary comparisons are indicative only — each city is valued with its own jurisdiction-specific parameters, not converted to a common currency.

Economic parameters: AUS — National appraisal guidance.

What the automated screen checks
  • Every constituent gap it states resolves to a real row
  • One continuous piece of geometry on the ground
  • A plausible set of distinct network edges behind it
  • Calculated, member and drawn lengths reconcile
  • Structural network-gain proxy passed
  1. Locator map for Pine Street
    1 Missing link · 278 m

    Pine Street

    Locality: Pine Street

    Location -33.88619, 151.19645

    Corridor ID 282449e6-2939-46aa-9cc3-fb2415a1983f

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 36 school features, 7 transport features, 61 workplace features, 100 shop & service features, 113 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 278 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Residents in catchment14,339
    Health benefit / yearAUD 155,911 – AUD 937,646conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 6,371 – AUD 38,316conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake143 – 860conservative–ambitious uptake
    Destinations mapped in catchment317
    CO₂ saved / year7.0 t – 42.1 tconservative–ambitious uptake
  2. Locator map for Liverpool Street
    2 Bike lane

    Liverpool Street

    Locality: Liverpool Street

    Location -33.87644, 151.21064

    Corridor ID ed18c7cf-8aee-416a-882b-ff497bd3cea1

    This area ranks highly because 74 school features, 51 transport features, 548 workplace features, 425 shop & service features are already mapped within a 2 km cycling catchment of it, and it addresses a 2.5 km gap in the existing network.

    Residents in catchment13,121
    Health benefit / yearAUD 142,827 – AUD 858,055conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 5,837 – AUD 35,064conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake131 – 787conservative–ambitious uptake
    Destinations mapped in catchment1,415
    CO₂ saved / year6.4 t – 38.6 tconservative–ambitious uptake
  3. Locator map for Kepos Street
    3 Missing link · 276 m

    Kepos Street

    Locality: Kepos Street

    Location -33.89628, 151.21247

    Corridor ID c7052733-2b98-4ca3-8707-4b224c54b88d

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 12 school features, 20 workplace features, 56 shop & service features, 86 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 276 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Its most exposed stretch would need about 9 more percentage points of tree canopy to stay usable in extreme heat.

    Residents in catchment11,753
    Health benefit / yearAUD 128,654 – AUD 768,651conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 5,257 – AUD 31,410conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake118 – 705conservative–ambitious uptake
    Destinations mapped in catchment174
    CO₂ saved / year5.8 t – 34.6 tconservative–ambitious uptake
  4. Locator map for Chalmers Street
    4 Missing link · 249 m

    Chalmers Street

    Locality: Chalmers Street

    Location -33.89475, 151.20509

    Corridor ID d7ae0d8a-888c-4ac8-994b-9a4b347a8d26

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 65 school features, 9 transport features, 243 workplace features, 255 shop & service features, 278 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 249 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Overlap-adjusted: 8,234 residents counted for this corridor. 23% of its catchment is already served by a higher-ranked candidate on this shortlist and is not counted twice.

    Residents in catchment8,234
    Health benefit / yearAUD 89,540 – AUD 538,913conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 3,659 – AUD 22,022conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake82 – 494conservative–ambitious uptake
    Destinations mapped in catchment850
    CO₂ saved / year4.0 t – 24.2 tconservative–ambitious uptake

    Before overlap adjustment

    Residents in catchment10,728
    Health benefit / yearAUD 116,661 – AUD 702,144
    Fuel & running-cost saving / yearAUD 4,767 – AUD 28,693
    Modelled additional cyclists at sustained uptake107 – 644
    Destinations mapped in catchment850
    CO₂ saved / year5.2 t – 31.6 t
  5. Locator map for Pitt Street
    5 Missing link · 258 m

    Pitt Street

    Locality: Pitt Street

    Location -33.89458, 151.20357

    Corridor ID f951e8e1-f389-49e1-b9ee-914485564356

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 67 school features, 11 transport features, 248 workplace features, 258 shop & service features, 274 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 258 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Overlap-adjusted: 1,476 residents counted for this corridor. 86% of its catchment is already served by a higher-ranked candidate on this shortlist and is not counted twice.

    Residents in catchment1,476
    Health benefit / yearAUD 16,074 – AUD 96,598conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 657 – AUD 3,947conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake15 – 89conservative–ambitious uptake
    Destinations mapped in catchment858
    CO₂ saved / year723 kg – 4.3 tconservative–ambitious uptake

    Before overlap adjustment

    Residents in catchment10,612
    Health benefit / yearAUD 115,570 – AUD 694,512
    Fuel & running-cost saving / yearAUD 4,723 – AUD 28,381
    Modelled additional cyclists at sustained uptake106 – 637
    Destinations mapped in catchment858
    CO₂ saved / year5.2 t – 31.2 t
  6. Locator map for Marriott Street
    6 Missing link · 89 m

    Marriott Street

    Locality: Marriott Street

    Location -33.89286, 151.21186

    Corridor ID b216d944-9290-483a-b7c2-1c6786d97791

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 10 school features, 19 workplace features, 51 shop & service features, 71 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 89 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Overlap-adjusted: 3,369 residents counted for this corridor. 66% of its catchment is already served by a higher-ranked candidate on this shortlist and is not counted twice.

    Residents in catchment3,369
    Health benefit / yearAUD 36,643 – AUD 220,228conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 1,497 – AUD 8,999conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake34 – 202conservative–ambitious uptake
    Destinations mapped in catchment151
    CO₂ saved / year1.6 t – 9.9 tconservative–ambitious uptake

    Before overlap adjustment

    Residents in catchment9,924
    Health benefit / yearAUD 107,938 – AUD 648,720
    Fuel & running-cost saving / yearAUD 4,411 – AUD 26,509
    Modelled additional cyclists at sustained uptake99 – 595
    Destinations mapped in catchment151
    CO₂ saved / year4.9 t – 29.2 t
  7. Locator map for Pitt Street
    7 Missing link · 280 m

    Pitt Street

    Locality: Pitt Street

    Location -33.89621, 151.20259

    Corridor ID d5ea05e5-e2c1-4129-be4a-e273f41e6f2d

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 64 school features, 9 transport features, 245 workplace features, 247 shop & service features, 276 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 280 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Overlap-adjusted: 1,120 residents counted for this corridor. 88% of its catchment is already served by a higher-ranked candidate on this shortlist and is not counted twice.

    Residents in catchment1,120
    Health benefit / yearAUD 12,233 – AUD 73,270conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 500 – AUD 2,994conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake11 – 67conservative–ambitious uptake
    Destinations mapped in catchment841
    CO₂ saved / year550 kg – 3.3 tconservative–ambitious uptake

    Before overlap adjustment

    Residents in catchment9,383
    Health benefit / yearAUD 102,487 – AUD 613,831
    Fuel & running-cost saving / yearAUD 4,188 – AUD 25,084
    Modelled additional cyclists at sustained uptake94 – 563
    Destinations mapped in catchment841
    CO₂ saved / year4.6 t – 27.6 t
  8. Locator map for Southern Cross Drive
    8 Missing link · 172 m

    Southern Cross Drive

    Locality: Southern Cross Drive

    Location -33.91147, 151.21292

    Corridor ID 24ec58ce-f7eb-4caa-85b7-dddfaa1e2cce

    ✓ Automated screening: passed 5 of 5 checks.

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 18 school features, 32 workplace features, 74 shop & service features, 114 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 172 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

    Its most exposed stretch would need about 51 more percentage points of tree canopy to stay usable in extreme heat.

    Residents in catchment8,648
    Health benefit / yearAUD 93,765 – AUD 565,858conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 3,832 – AUD 23,123conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake86 – 519conservative–ambitious uptake
    Destinations mapped in catchment238
    CO₂ saved / year4.2 t – 25.4 tconservative–ambitious uptake
  9. Locator map for Coulson Street
    9 Bike lane

    Coulson Street

    Locality: Coulson Street

    Location -33.90553, 151.18424

    Corridor ID ded59519-e953-4280-a3eb-533837ecb317

    This area ranks highly because 25 school features, 6 transport features, 173 workplace features, 102 shop & service features are already mapped within a 2 km cycling catchment of it, and it addresses a 2.9 km gap in the existing network.

    Residents in catchment7,306
    Health benefit / yearAUD 79,591 – AUD 477,545conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 3,252 – AUD 19,514conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake73 – 438conservative–ambitious uptake
    Destinations mapped in catchment444
    CO₂ saved / year3.6 t – 21.5 tconservative–ambitious uptake
  10. Locator map for Wilson Street
    10 Bike lane

    Wilson Street

    Locality: Wilson Street

    Location -33.89715, 151.17997

    Corridor ID 332a7150-0eaf-49c9-90d2-8e4b0f58ed75

    This area ranks highly because 45 school features, 5 transport features, 127 workplace features, 130 shop & service features are already mapped within a 2 km cycling catchment of it, and it addresses a 2.9 km gap in the existing network.

    Residents in catchment6,748
    Health benefit / yearAUD 73,049 – AUD 441,566conservative–ambitious uptake
    Fuel & running-cost saving / yearAUD 2,985 – AUD 18,044conservative–ambitious uptake
    Modelled additional cyclists at sustained uptake67 – 405conservative–ambitious uptake
    Destinations mapped in catchment474
    CO₂ saved / year3.3 t – 19.8 tconservative–ambitious uptake
10 candidate clusters did not pass the automated screen

These clusters did not pass the automated screening checks, so they are not on the shortlist above, carry no modelled benefit and were excluded from its overlap adjustment. They are published here — and in full in the downloadable corridor GeoJSON — so the finding can be checked locally.

  1. 1. Multi-street corridor — 5 linked gaps (requires validation)

    Location -33.88059, 151.20161

    Corridor ID 5c8ecd91-b5a6-4987-b7a8-860470cd2c95

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 77 school features, 40 transport features, 535 workplace features, 411 shop & service features, 357 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 425 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  2. 2. Multi-street corridor — 7 linked gaps (requires validation)

    Location -33.90133, 151.21069

    Corridor ID 909190e1-602a-41e4-9e78-08bbeca47ca3

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 50 school features, 1 transport feature, 226 workplace features, 188 shop & service features, 251 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 499 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  3. 3. Multi-street corridor — 5 linked gaps (requires validation)

    Location -33.87739, 151.20106

    Corridor ID 27fc5ae1-c2b4-4330-8e93-1324cc9be543

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it; calculated, member and drawn lengths do not reconcile

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 78 school features, 53 transport features, 554 workplace features, 414 shop & service features, 343 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 926 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  4. 4. Multi-street corridor — 11 linked gaps (requires validation)

    Location -33.88061, 151.19842

    Corridor ID 2ef523b5-a4db-41cf-8b2a-f8d36d16523b

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 77 school features, 42 transport features, 517 workplace features, 403 shop & service features, 389 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 275 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  5. 5. Multi-street corridor — 7 linked gaps (requires validation)

    Location -33.87943, 151.20178

    Corridor ID 6c10dd01-68ea-4262-a48f-da118555380a

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it; calculated, member and drawn lengths do not reconcile

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 76 school features, 41 transport features, 547 workplace features, 412 shop & service features, 333 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 451 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  6. 6. Multi-street corridor — 3 linked gaps (requires validation)

    Location -33.87818, 151.19578

    Corridor ID 28e870a5-a0a7-4eab-8254-61f8570b07e5

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 30 school features, 14 transport features, 66 workplace features, 89 shop & service features, 99 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 823 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  7. 7. Multi-street corridor — 5 linked gaps (requires validation)

    Location -33.87443, 151.20051

    Corridor ID e6c809cc-a958-42eb-a205-b41787c3e831

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 75 school features, 56 transport features, 551 workplace features, 380 shop & service features, 330 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 247 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  8. 8. Multi-street corridor — 5 linked gaps (requires validation)

    Location -33.87856, 151.21631

    Corridor ID 4a0bb336-f3e2-4707-8590-dbd6af2852b0

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 69 school features, 29 transport features, 489 workplace features, 413 shop & service features, 317 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 194 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  9. 9. Multi-street corridor — 4 linked gaps (requires validation)

    Location -33.87430, 151.20387

    Corridor ID 3ef685e4-4c89-4d6c-967c-ed034345f096

    Locator map for Multi-street corridor

    Did not pass: not continuous on the ground — the geometry is in several pieces; no plausible set of distinct network edges behind it

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 73 school features, 55 transport features, 556 workplace features, 408 shop & service features, 332 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 350 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

  10. 10. Multi-street corridor — 2 linked gaps (requires validation)

    Location -33.87575, 151.20390

    Corridor ID fdba7a3b-0453-412b-8b46-c1aaab28b9f2

    Locator map for Multi-street corridor

    Did not pass: no plausible set of distinct network edges behind it; the structural network-gain proxy is not met

    Structural network-gain proxy: the distinct existing ways the build would join, the destinations ALREADY MAPPED inside its catchment (not destinations this build would newly connect), and a minimum build length. Routed before/after connectivity gain: not assessed. No routed connectivity model exists in this pipeline, so connectivity before, connectivity after and the residents who would newly gain access are reported as unavailable rather than estimated from the catchment.

    This area ranks highly because approximately 75 school features, 53 transport features, 558 workplace features, 424 shop & service features, 315 other mapped features are already mapped within a 2 km cycling catchment of it, and it addresses a 95 m gap in the existing network. Estimated mapped destinations in the 2 km catchment: this corridor's category breakdown is reconciled across overlapping catchments, so the figures are approximate counts of mapped features rather than exact ones.

Estimated residents in catchment — population × network analysis Potential new cyclists — modelled Health benefit — modelled scenario Transport-cost & carbon — modelled scenario
Modelling assumptions
Uptake — conservative
1%
Uptake — ambitious
6%
Trips per new cyclist
3 / week
Average trip distance
4 km
Car trips replaced
40%
Benefit basis
Annual, steady-state (per year once uptake is sustained; no multi-year ramp modelled)
Modelled additional cyclists
A steady-state stock at sustained uptake, not an annual intake; mode-shift of catchment residents, with existing cyclists not separately excluded. Each corridor publishes the population its riders were modelled on, its corridor adjustment factor and the final effective uptake rate that implies
Catchment & overlap
Residents within the corridor buffer (WorldPop); portfolio counts each resident once (a corridor's buffer minus the union of higher-ranked corridors' buffers)
Crashes & air pollution
Not separately assessed
Currency & valuation year
AUD, 2026 prices — local currency, not converted; cross-city monetary comparisons are indicative only
Value of statistical life
AUD 5,300,000
All-cause mortality rate
400 per 100,000/yr
HEAT reference dose
100 min/week (~1213 km/yr)
Mortality reduction at reference dose
10%
Serious injury cost
AUD 260,000
Discount rate
5%
Appraisal horizon
10 years
Casualty reduction from facility
30%
Protected-lane build cost
AUD 250,000/km
Social cost of carbon
AUD 75/tonne
Value of time
AUD 40/hr × 50%
Time saved per trip
2 min
Fuel levy
AUD 0.50/L
Consumption tax (VAT/GST)
10%
From baseline to validated

Local data that would validate this 0 / 7

This scorecard is built entirely from open data, scored the same way worldwide. A handful of local datasets would turn it into a validated, city-specific diagnostic — and then a measured pilot.

1

Open-data baseline

this scorecard, today.
2

Locally-validated diagnostic

your datasets below, reconciled against ours.
3

Measured pilot

counts and outcomes tracked on the ground.
  • Official cycling-network GIS Needed

    Your authoritative lane/path layer, to reconcile against the OSM-derived network.

    Validates: Coverage & comfort classification

  • Census cycling mode share Needed

    Journey-to-work (or all-trip) cycling share, as an external outcome to compare the index against.

    Validates: External outcome comparison

  • Cycling counts Needed

    Automatic or manual count-site volumes, to switch on a measured ridership layer.

    Validates: Ridership (activation layer)

  • Crash / casualty records Needed

    Geocoded cycling crashes, to switch on a measured safety layer and target corridors.

    Validates: Safety (activation layer)

  • Traffic speeds & volumes Needed

    Road speeds/volumes, to refine which streets count as low-stress for the network graph.

    Validates: Comfort / traffic-stress classification

  • Planned / funded projects Needed

    Your committed pipeline, so proposed corridors are de-duplicated against what's already funded.

    Validates: Priority corridors

  • Local demographic / equity data Needed

    Local equity indicators, to weight access by who is currently underserved.

    Validates: Access equity overlay

Map of the exact area scored, drawn over the street network
The exact area scored

What “City of Sydney” means on this scorecard

Every calculation is clipped to the exact study extent shown here — no cherry-picked study areas. Where that extent came from is named below.

Boundary source
geoBoundaries administrative footprint
Administrative level
City / Council
Boundary type
Municipality
Study boundary ID
25037944B98854570895907
Enclosed area
27 km²
Built-up area (density denominator)
27 km²
Population density
8446 residents/km²

The scored polygon IS one published administrative feature, cited by its own geoBoundaries shapeID, so its identity rests on that citation rather than on a measurement against a municipal-tier feature.

Terrain

How hilly is the network?

Average network grade 2.0%, with 8.5% of the network on slopes above 5%. Contextual — terrain does not change the index score. © Commonwealth of Australia (Geoscience Australia) (CC BY 4.0) © Commonwealth of Australia (Geoscience Australia) (CC BY 4.0) © Commonwealth of Australia (Geoscience Australia) (CC BY 4.0) © Commonwealth of Australia (Geoscience Australia) (CC BY 4.0)

19.7%over 3%
8.5%over 5%
3.7%over 8%
Nighttime illumination

What do we know about this network after dark?

34.1% of the cycling network has confirmed or inferred nighttime illumination. For 57.7% the evidence is inconclusive, and for 8.2% there is none either way. Contextual — nighttime illumination is shown as evidence and does not change the index score. It becomes a scored dimension when a city supplies its street-lighting asset register.

Nighttime satellite radiance indicates artificial illumination in the surrounding area. It does not necessarily mean that dedicated street lighting is present on the road itself.

Satellite evidence was gathered but is not yet calibrated for this city, so it is recorded without drawing a conclusion. Confirmed shares come from OpenStreetMap lighting tags and mapped lamp posts.

34.1%confirmed or inferred
57.7%inconclusive
8.2%no evidence
Heat resilience

Can this network be used in extreme heat?

76.9% of the residents who can reach a bike route today can still reach one that stays usable in the heat. Measured across 92.1% of the qualifying network. Contextual — heat resilience does not change the index score.

Tree canopy here is checked against New South Wales's 2022 Greater Sydney canopy survey. Along streets — the blocks with scattered trees rather than parkland — the two agree to within about 2 percentage points.

76.9%access retained

What sits behind the number

Sub-scores & evidence

Every dimension shows exactly how it's measured and the single lever that would move it. Nothing hidden. Want the thresholds themselves? Read the full scoring methodology — what each score means, how every dimension is measured, and what the index does not claim.

How a mapped way becomes a facility class, a quality weight and an Access decision A single OpenStreetMap way and its tags enter a classifier on the left. On the right, one row per facility class: each row carries the quality weight a kilometre of that class contributes to Coverage, and states whether the class counts toward the Access measure. A filled marker means it counts; a hollow marker means it does not. ONE MAPPED WAY Its tags highway=* cycleway=* bicycle=* segregated=*, foot=* The best facility on the way wins Counts toward the Access measure Protected track Counts toward Access ×1.0 per kilometre Counts toward the Access measure Shared path, off the carriageway Counts toward Access ×0.8 per kilometre Not counted toward the Access measure Mixed traffic, signed Not counted toward Access ×0.8 per kilometre Not counted toward the Access measure Painted lane Not counted toward Access ×0.5 per kilometre Not counted toward the Access measure Unevidenced Not counted toward Access ×0.5 per kilometre Not counted toward the Access measure Crossing Not counted toward Access ×0.0 per kilometre
A kilometre is not a kilometre. Each class carries a quality weight, and Coverage counts weighted kilometres rather than raw ones. Access is a separate decision from the weight: it counts only the classes that keep a rider away from motor traffic, so a class can carry real length toward Coverage and still be excluded from Access.
Coverage 83

22 km physically protected · 78 km shared path · 13 km painted · 11 km mixed traffic — 123 km modelled → 75 effective km ≈ 2.82 km/km² built-up (quality-weighted)

Lever to improve

Build protected lanes / paths

Connectivity 77

77% of the low-stress network is one connected piece · 1,470 candidate network discontinuities detected before screening

Lever to improve

Close the highest-severity missing links

Access 95

94% of residents within 300 m of traffic-free cycling infrastructure — an off-street path or a physically protected lane, ITDP's People Near Protected Bikelanes definition · the traffic-free network behind it is 22 km separated cycleway and 78 km path shared with pedestrians (78% shared)

Lever to improve

Fill accessibility-lane gaps where people live

Amenities 100

1,107 parking · 8 repair · 364 water · 246 toilets ≈ 16.52 capped weighted units per km² of built-up area · 90.0 parking per 10 km of network

Lever to improve

Add parking / repair / water at hubs


Network composition

What the modelled total contains
Physically protected cycling infrastructure 22 km
Other low-stress / cycling-suitable network — off-road shared paths, painted lanes, mixed traffic 101 km
Total cycling-accessible network modelled 123 km

Network comfort mix

Classified by separation
High — separated 22 km Medium — shared 89 km Low — painted 13 km

Comparable on-street lane network: 34 km of separated + painted lanes — the like-for-like figure to set beside your city's own lane count. The full 123 km above additionally counts shared and off-road paths, so it reads higher.

Corridor kilometres. Network length is measured in CORRIDOR kilometres: each physical corridor counts once. A street with a cycle track on each side is two usable facilities but one corridor, and OpenStreetMap records that either as one carriageway or as two parallel ways — counting rows would make the figure depend on local mapping habit. Ways running parallel within 4–25 m of each other are treated as one corridor. That removed 13.8% of this city's as-mapped length.

Data & assumptions

Nothing hidden

Every source, version and economic assumption behind this scorecard — and the raw figures to download and check yourself.

OpenStreetMap (infrastructure)
Extract
Not recorded on this snapshot
Extract published
Not recorded on this snapshot
Artifact built
Not recorded on this snapshot
Build run
Not recorded on this snapshot
Extract loaded
2026-11-06
Source
Not recorded on this snapshot
Query area
geoBoundaries administrative footprint
Facility classifier version
Not recorded on this snapshot
Methodology version
v19
Licence
ODbL — © OpenStreetMap contributors
Why fields are blank
Several loads of this dataset exist in this deployment and this city has no load of its own, so the specific one behind these figures cannot be identified. Re-provision the city to record it.
WorldPop (population)
Product
aus_pop_2024_CN_100m_R2025A_v1
Edition / year
2024
Release
R2025A
Modelling basis
Constrained (residents placed only on built-up settlements)
Adjustment
Unadjusted (the product's own modelled totals)
Source
https://data.worldpop.org/GIS/Population/Global_2015_2030/R2025A/2024/AUS/v1/100m/constrained/aus_pop_2024_CN_100m_R2025A_v1.tif
Layer identifier (internal)
worldpop_city-of-sydney @ 100 m
Layer selection
The load built for this city — the only one counted.
Layer synced
2026-08-02
Resolution
100 m
Licence
CC BY 4.0 — © WorldPop (worldpop.org)
Road lighting (nighttime illumination evidence)
Radiance product
VNL_npp_2025_global_vcmslcfg_v2_median_cog
Composite year
2025
Layer identifier (internal)
viirs_glen-eira
Layer loaded
2026-09-05
Nominal resolution
463 m per pixel — coarser than any single street
Street lamps (OpenStreetMap)
127 mapped lamp nodes in the study area
Satellite calibration
Not calibrated — radiance is recorded as evidence but states no direction. Confirmed shares rest on OpenStreetMap lighting tags and mapped lamp posts.
Used for
A contextual view of what is known about the network after dark. It is an activation-layer dimension: displayed, never scored, and it changes no part of the Infrastructure Provision result.
Lighting model version
v2
Licence
Radiance: CC BY 4.0 — © Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines · Lighting tags and lamp nodes: ODbL — © OpenStreetMap contributors
geoBoundaries (the scored boundary IS this published feature)
Boundary source
geoBoundaries administrative footprint
Administrative level
City / Council
Country (ISO3)
AUS
Release
geoBoundaries (synced 2026-07-07)
Licence
CC BY 4.0 — © geoBoundaries
Methodology
Version
v19
Infrastructure Provision
The four infrastructure dimensions, renormalised to 100. Ridership & Safety are reported separately (activation layer) and do not change the infrastructure result.
Dimension weights
access=0.27223 · safety=0.1 · coverage=0.19446 · amenities=0 · ridership=0.1 · connectivity=0.23331 · intersection_delay=0.1
Provision thresholds (basic / strong / leading)
Coverage 1 / 2.5 / 5 · Access 50 / 80 / 100 · Amenities 2 / 10 / 40. These are FIXED provision criteria, not positions among other cities: 50 means basic but incomplete provision, 80 strong citywide provision, and 100 near-complete performance, interpolated in between. They do not change as cities are added to the board, so a city's score moves only when its own infrastructure or data does. Connected network share — identity scale, no threshold set: the percentage IS the score, so 62% of the network in one connected component scores 62. No published source states a normative target for this measure, and borrowing one written for a different measure would claim more than the evidence supports.
Contextual reference (not scored)
gap density 0.59 gaps/network-km (a diagnostic shown when connectivity abstains) · safety failure threshold 20 events/100k km (activation layer)
Scoring
Higher-is-better dimensions (coverage, access, amenities) are interpolated along fixed provision thresholds: 0 at zero, 50 at basic provision, 80 at strong, 100 at leading, straight lines between, clamped at each end. Access and Connectivity are already percentages, so their score IS the percentage. Gap density is contextual, not scored (v13). Safety, if scored, is lower-is-better against a FAILURE THRESHOLD: 100 - min(100, rate / threshold x 100), so zero events scores 100 and a rate at or above the threshold scores zero. See the calculation trace below.
Where the scoring targets come from
Coverage target
Percentile-derived, computed by us: the 90th percentile of the 40 cities on Party Onbici's own board with a population of 100,000 or more that held a snapshot on 2026-07-06, using the read-only calibrate_index_targets command. It is not a policy target and no standards body set it.
Access target
Percentile-derived, computed by us: the 90th percentile of the same 40-city board on 2026-07-06. What is measured — residents within 300 m of traffic-free infrastructure, an off-street path or a physically protected lane — follows ITDP's People Near Protected Bikelanes definition, but the level at which it scores 100 is ours, not ITDP's: ITDP publishes no such threshold.
Amenities target
Percentile-derived, computed by us: the 90th percentile of the same 40-city board on 2026-07-06. The per-category weights that turn facilities into units (parking 1.0 · repair station 4.0 · drinking water 2.0 · public toilet 0.5) are internally selected reference values — our own judgement of what each is worth to a rider, not calibrated and not taken from a published source.
Gap-density reference
Percentile-derived, computed by us: the 10th percentile of the same 40-city board on 2026-07-06 — the opposite tail, because fewer gaps is better. Contextual only since methodology v13: it is shown when connectivity abstains and scores nothing.
Ridership and safety
Internally selected reference values, not calibrated against any cohort and not taken from a published source — they were chosen to give the activation layer a scale. That layer is not yet assessed for any city, so neither value affects any published score.
The cohort itself
The cohort is the set of cities this platform had already assessed — a convenience sample of our own coverage, not a probability sample, not an international register, and not endorsed by any standards body. Its membership was not recorded at the time; only its size (40 cities) and the population floor (100,000) are on record. A target derived this way says 'the highest level we have measured', not 'the level a city ought to reach'.
Where the economic parameters come from
Economics basis
AUS — National appraisal guidance
Economic parameters
The economic parameters behind this city's monetary figures come from its own country's official appraisal guidance.
Inputs we chose ourselves
These economic inputs trace to no published document — they are our own reference values, not citations: Fleet fuel consumption, Retail petrol price, Fuel excise, Adult all-cause mortality rate, Gross hourly wage, Protected-lane build cost per km, Carbon price per tonne.
How each score is calculated
Coverage
21.6·1.0 + 12.7·0.5 + 88.7·0.8 = 98.9 effective km ÷ 26.6 km² = 3.71/km² → against fixed thresholds 1 (basic) / 2.5 (strong) / 5 (leading) → 83
Access
94% of residents near traffic-free infra against fixed thresholds 0.5 (basic) / 0.8 (strong) / 1 (leading) → 95
Connected network share
77% of low-stress network in its largest component ×100 → 77
Amenities
capped weighted units 440.0 ÷ 26.6 km² = 16.52/km² → against fixed thresholds 2 (basic) / 10 (strong) / 40 (leading) → 100 (each category capped at 50% of target)
WHO HEAT scenario inputs
Value of statistical life
AUD 5,300,000
All-cause mortality rate
400 per 100,000/yr
HEAT reference dose
100 min/week (~1213 km/yr)
Mortality reduction at reference dose
10%
Party Onbici transport & cost assumptions
Uptake — conservative
1%
Uptake — ambitious
6%
Trips per new cyclist
3 / week
Average trip distance
4 km
Car trips replaced
40%
Benefit basis
Annual, steady-state (per year once uptake is sustained; no multi-year ramp modelled)
Modelled additional cyclists
A steady-state stock at sustained uptake, not an annual intake; mode-shift of catchment residents, with existing cyclists not separately excluded. Each corridor publishes the population its riders were modelled on, its corridor adjustment factor and the final effective uptake rate that implies
Catchment & overlap
Residents within the corridor buffer (WorldPop); portfolio counts each resident once (a corridor's buffer minus the union of higher-ranked corridors' buffers)
Crashes & air pollution
Not separately assessed
Currency & valuation year
AUD, 2026 prices — local currency, not converted; cross-city monetary comparisons are indicative only
Serious injury cost
AUD 260,000
Discount rate
5%
Appraisal horizon
10 years
Casualty reduction from facility
30%
Protected-lane build cost
AUD 250,000/km
Social cost of carbon
AUD 75/tonne
Value of time
AUD 40/hr × 50%
Time saved per trip
2 min
Fuel levy
AUD 0.50/L
Consumption tax (VAT/GST)
10%
This report
Generated
2026-11-06 20:20 UTC
Methodology version
v19
Analysis run
b6ac5d62-5c09-470a-b5b4-f1836d3fe69c
Code revision
b80b800a4512c029739bbd55352d626cb510adee
Scoring config digest
1949a2fcba81cfcc
Software
Party Onbici City Cycling Index

Common questions

What transport teams ask us first

Something else on your mind? Bring it to the briefing — or email hello@partyonbici.com.

Will the methodology hold up if it's challenged?
Yes — that's the design goal. Every score traces to published open data, the methodology is versioned and public, targets and weights are documented, and each benchmark lens abstains rather than guesses when the data can't support a well-founded number. Your own analysts can trace and check the figures against the same public data.
Nothing. The scorecard is computed entirely from open data on the study extent named in the study-area panel. If you later share ride or count data, it activates the Ridership and Safety dimensions — but the Infrastructure Provision score never depends on it.
The underlying map refreshes weekly; each scorecard shows its exact computation timestamp and the age of its OSM extract. When your city builds a new protected lane and it lands on the map, your score moves.
No. The Infrastructure Provision score uses only open geographic data — no personal information. Population figures are WorldPop statistical grids. Any future ride telemetry is aggregate, held in-region, and kept strictly outside the open-data benchmark.
The briefing and this preview scorecard are free — no procurement needed. Ongoing plans (live scorecard, corridor planning tools, consultation mapping) are an annual subscription scaled to your city's size — in the range of standard municipal GIS and analytics tooling, not a capital project. The exact figure is scoped at the briefing, but it's a line item a team can plan around, not a tender.
For city & transport teams

Put your city's cycling readiness on the record

Book a 30-minute briefing and we'll walk your team through this scorecard, then stand up a live index for your own boundary — same method, same open data, comparable worldwide.

  • A live scorecard for your admin boundary, refreshed weekly
  • Impact-ranked corridors mapped to your network gaps
  • Versioned, documented methodology you can reproduce

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Prefer email? hello@partyonbici.com

Methodology v19 — versioned and documented targets and weights. Scores are 0–100 against targets Party Onbici sets and accounts for in "Where the scoring targets come from" under Data & assumptions; they are not policy standards set by anyone else. Each composite blends available sub-scores, renormalising weights so excluded dimensions don't distort the total. Area and network length are clipped to this city's study extent, named in the study-area panel. Network length is OSM-classified route-kilometres (separated + painted + shared paths) and may exceed a city's own lane-only total, which typically counts painted and separated lanes only.

Boundaries © geoBoundaries (CC BY 4.0) · infrastructure © OpenStreetMap contributors · population: WorldPop.  ·  This scorecard is a planning diagnostic, not a definitive city ranking.  ·  Party Onbici · shared scorecard

Heat evidence: © Meta and World Resources Institute (CC BY 4.0) · Building footprints © Microsoft, CDLA-Permissive-2.0