Product, EquiMap

Core features

Live analysis, Greater Sydney fire coverage

Avg km to nearest fire station, by SEIFA decile · real ABS + FRNSW data

Decile 1 (most disadv.)

1.64

Decile 3

1.95

Decile 5

2.08

Decile 7

3.28

Decile 8

2.97

Decile 10 (premium)

2.54

✓ Real finding

Across 361 Greater Sydney communities, the most modest areas are better covered (1.64 km) than mid-premium ones (3.28 km). The real gaps are on the semi-rural fringe, not where intuition predicts.

01

Equity-weighted gap scoring

Every SA2 area receives a gap score from 0-10 per service type. Unlike simple proximity measures, EquiMap's scores are weighted by SEIFA decile, age cohort, and remoteness, measuring need, not just distance.

Scores statistical areas nationwide (~2,400 SA2s across Australia)

Weights by SEIFA disadvantage, 65+ population, and First Nations communities

Surfaces compounding gaps across multiple service types simultaneously

Exportable ranked list for business cases, board papers and funding submissions

02

Travel-time modelling, beyond straight-line distance

Coverage radius circles can mislead. A hospital might be 5 km away, but separated by a river with no bridge, making it 25 minutes by road. The current analyses use a transparent straight-line baseline; EquiMap is built to layer in real 5, 10, and 15-minute drive-time catchments from open road-network data, or vehicle telemetry when agencies supply it.

Straight-line distance today, a clear, defensible starting point

Drive-time via OpenStreetMap road network as the next layer

Integrates real ambulance, fire, and police travel times when supplied

Designed as a single swap in the pipeline, no re-engineering

Isochrone view · illustrative concept

Illustrative concept. Drive-time catchments are an enhancement to the current straight-line baseline, available when road-network or telemetry data is added.

What-if scenario builder · concept preview

Scenario: +1 station near Bilpin-Colo

ILLUSTRATIVE

Before (real)

36.7km

to nearest station

After (modelled)

~12km

to nearest station

Real gap identified (Bilpin-Colo) 36.7 km

Scenario modelling (illustrative) Phase 3 feature

Gap detection (live now) ✓ Real data

03

What-if scenario modelling

Don't just identify gaps, model solutions. Place proposed new service facilities on the map and instantly see the projected impact: coverage improvement, equity score delta, reduction in average response time, and population newly served.

Drag-and-drop interface for non-GIS users

Instant recalculation of gap scores and equity metrics

Save and compare multiple scenarios side-by-side

Export scenario results directly into report briefing templates

Equity case studies

See the method in action.

Four real analyses on open government data, fire coverage, GP access, affordability, each showing how EquiMap helps a different client understand equity with evidence. The recurring lesson: the gaps are rarely where intuition points.

Fire · Metro

Greater Sydney

The most modest areas turned out better served than the premium fringe.

Health · National

GP access Australia-wide

Bulk-billing and physical access pull in opposite directions, distance is the real gap.

Health · State

Victoria, zoomed in

The same engine, focused on one state: regional access is Victoria's real equity issue.

Explore all four case studies →

Data architecture

Open by default.
Proprietary when available.

EquiMap delivers significant analytical value from freely available open data. When agencies supply their own operational data, precision increases further, but the baseline is always strong.

Open data (default · no cost · no approval required)

ABS Census & SEIFA 2021

Population, income & SEIFA profile by SA2/LGA via ABS Data API

data.gov.au (30,000+ datasets)

National service locations, facility registers, CC BY 4.0

State open data portals

Fire, ambulance, police, hospital locations, all states

Geoscience Australia / Digital Atlas

GNAF address fabric, SA2 boundaries, road network

ABS Population Projections

Demand forecasting to 2036 and 2056

Proprietary data (optional · agency-supplied · improves precision)

Vehicle telemetry & CAD data

Real ambulance, fire & police travel times vs theoretical road network

Dispatch & response records

Historical response time datasets for calibration and trend analysis

Hospital patient origin data

Where patients travel from, reveals true catchment areas vs assumed

CCTV & incident data

Demand hotspots for police & fire resource optimisation models

Real estate & development approvals

Growth pipeline driving 2036/2056 demand projections

🧮 Methodology

How the gap score is calculated

EquiMap is built to be transparent. Here is the method behind every analysis on this site, including the assumptions, so results can be understood and challenged. This reflects the current prototype; the approach is being refined as the platform matures.

📍

1. Measure access

For each community (ABS SA2 or LGA), we measure the distance from its population-weighted centroid to the nearest relevant service. The current baseline uses straight-line (as-the-crow-flies) distance: a transparent, reproducible starting point. Drive-time isochrones from the open road network are planned as the next layer, and matter most where rivers, terrain or limited roads make straight-line distance optimistic.

⚖️

2. Weight by need

Raw distance treats every community equally. EquiMap weights it by relative need, using the ABS SEIFA Index of Relative Socio-economic Disadvantage (IRSD) decile, with scope to factor in age profile (such as the 65+ share), remoteness, and First Nations community presence. A given distance counts for more in a community with higher assessed need.

🔢

3. Score the gap

Access and need-weighting combine into a single gap score from 0 to 10 per service, per community. Low scores mean well served relative to need; high scores flag where coverage is thin and need is high. Scores are normalised within each analysis so communities can be ranked and the clearest opportunities surfaced as a shortlist.

Assumptions & limitations, stated plainly

Straight-line distance is a deliberate simplification and can understate real travel time. Nearest-service distance does not yet account for service capacity, opening hours, or quality. SEIFA is an area-level index, so it describes communities, not individuals. These analyses are prototype demonstrations on open data, intended to show the method and prompt better questions, not to replace an agency's operational modelling. Each limitation is a planned enhancement as agency data and validation are added.

Competitive landscape

Purpose-built for the equity layer

Existing tools are either powerful but general-purpose (Esri, Palantir) or AU-native mapping platforms (CSIRO Terria, NationalMap). EquiMap is purpose-built for the equity layer that sits alongside them.

Feature	Esri ArcGIS	CSIRO Terria	NationalMap	Palantir	EquiMap ✦
AU open data native	Partial	✓	✓	✗	✓
SEIFA equity weighting	Partial	✗	✗	✗	✓
Multi-service gap scoring	✗	✗	✗	Partial	✓
Travel-time / isochrone modelling	✓	✗	✗	Partial	Roadmap
What-if scenario builder	✓	✗	✗	✓	Roadmap
Proprietary data integration	✓	✗	✗	✓	✓
Non-GIS user friendly	✗	Partial	Partial	✗	✓
AU-sovereign hosting	✗	✓	✓	✗	✓
Report briefing export	Partial	✗	✗	Partial	✓

Engagement models

Flexible models for
every planning stage

ENTRY

Pilot Study

Rapid 3-month assessment for a specific state, service type, or corridor.

POA

Project-based · typically 3 months

Single service type analysis

One state or metro region

Interactive EquiMap dashboard

Report-ready briefing report

Open data baseline (proprietary optional)

Discuss a pilot →

Ready to see EquiMap in action for your city?

The live preview runs real OpenStreetMap tiles with service markers plotted at real coordinates for Sydney, Melbourne, Brisbane, and Perth. No sign-up required.

Launch the live preview →

Location intelligence builtto ensure equity