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Geographic Investigation

Funding Deserts

Where disadvantage is highest and investment is lowest — 584 Local Government Areas scored by SEIFA disadvantage, remoteness, entity coverage, and funding flows. 363 LGAs score above 100, indicating severe geographic underinvestment relative to need.

Data updated 31 March 2026
LGAs Analysed
584
scored by desert index
Severe Deserts
363
desert score > 100
Avg Desert Score
112.1
across all LGAs
Funding Gap
$44.9B
most vs least funded

Source: SEIFA 2021 (ABS) × Remoteness Areas (ABS) × CivicGraph Entity Graph × Justice Funding × AusTender Procurement.

Worst Funding Deserts

The 30 LGAs with the highest desert scores: most disadvantaged, most remote, fewest service providers, and least funded. Many have zero indexed entities and zero tracked funding — invisible to the systems designed to help them.

#LGAEntitiesDesert Score
1
Barkly
Unknown
0190
2
Laverton
Unknown
0190
3
Mount Isa
Unknown
0190
4
Palmerston
Unknown
0190
5
Roper Gulf
Unknown
0190
6
Unincorporated NSW
Unknown
0190
7
Mount Magnet
WA
3185
8
Coolgardie
WA
18182
9
Balonne
Unknown
0180
10
Brewarrina
Unknown
0180
11
Central Highlands (Qld)
Unknown
0180
12
Coonamble
Unknown
0180
13
Moree Plains
Unknown
0180
14
Unincorporated NT
Unknown
0180
15
Victoria Daly
Unknown
0180
16
Woorabinda
Unknown
0180
17
Coomalie
Unknown
0175
18
Flinders (Tas.)
Unknown
0175
19
Blackall Tambo
Unknown
0170
20
Carpentaria
Unknown
0170
21
Croydon
Unknown
0170
22
Fraser Coast
Unknown
0170
23
Inverell
Unknown
0170
24
MacDonnell
Unknown
0170
25
Mid Murray
Unknown
0170
26
Murchison
WA
8170
27
Murray River
Unknown
0170
28
Northern Areas
Unknown
0170
29
Orroroo Carrieton
Unknown
0170
30
Snowy Valleys
Unknown
0170
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The Urban-Remote Divide

The data is unambiguous: remoteness drives desert scores. Very Remote LGAs average 148 on the desert index versus 70 for Major Cities — a 2.1x disparity.

Average Desert Score by Remoteness

Very Remote
148
69 LGAs
Remote
139
75 LGAs
Outer Regional
126
191 LGAs
Inner Regional
98
106 LGAs
Major Cities
70
128 LGAs
RemotenessLGAsAvg Desert Score
Very Remote69147.5
Remote75138.6
Outer Regional191126.3
Inner Regional10698.0
Major Cities12869.9

Desert Scores by State

State-level aggregates reveal structural differences in how funding reaches communities. States with large remote footprints carry higher average desert scores.

StateLGAsAvg Desert Score
QLD16117.3
WA96114.0
TAS13105.7
SA38101.6
NT1699.5
NSW9599.0
VIC8180.1
ACT265.5

Best Funded vs Worst Funded

Side-by-side comparison of the 10 most underserved and 10 best-served LGAs. The contrast reveals the structural geography of Australian social investment.

Most Underserved (Worst Deserts)

#LGAScore
1
Barkly
· Very Remote
190
2
Laverton
· Very Remote
190
3
Mount Isa
· Very Remote
190
4
Palmerston
· Very Remote
190
5
Roper Gulf
· Very Remote
190
6
Unincorporated NSW
· Very Remote
190
7
Mount Magnet
WA · Very Remote
185
8
Coolgardie
WA · Very Remote
182
9
Balonne
· Very Remote
180
10
Brewarrina
· Remote
180

Best Served (Lowest Desert Scores)

#LGAScore
1
Blacktown
NSW · Major Cities
20.0
2
Cambridge
WA · Major Cities
20.0
3
Cottesloe
WA · Major Cities
20.0
4
Hunters Hill
NSW · Major Cities
20.0
5
Nedlands
WA · Major Cities
20.0
6
Northern Beaches
NSW · Major Cities
20.0
7
Boroondara
VIC · Major Cities
21.9
8
Hornsby
NSW · Major Cities
22.5
9
Mitcham
SA · Major Cities
22.9
10
Mosman Park
WA · Major Cities
23.3

Methodology

SEIFA IRSD (Socio-Economic Indexes for Areas): The Index of Relative Socio-Economic Disadvantage from the Australian Bureau of Statistics (2021 Census). Each postcode is assigned a decile from 1 (most disadvantaged) to 10 (least disadvantaged). LGA-level scores are averaged across constituent postcodes. A low SEIFA decile means the area has higher proportions of people with low incomes, lower educational attainment, and higher unemployment.

Remoteness classification: Based on the ABS Remoteness Areas framework (ARIA+ 2021), which classifies geography into five categories: Major Cities, Inner Regional, Outer Regional, Remote, and Very Remote. Each category reflects distance from service centres and population density.

Entity coverage: The count of CivicGraph-indexed entities (charities, service providers, community organisations) operating within each LGA. A low entity count signals sparse service infrastructure — fewer organisations competing for or delivering services.

Desert score formula: A composite index combining four dimensions:

  • SEIFA IRSD decile (inverted, scaled 0–100) — lower decile = higher disadvantage = higher score
  • Remoteness category (0–40) — Very Remote = 40, Remote = 30, Outer Regional = 20, Inner Regional = 10, Major Cities = 0
  • Entity coverage gap (0–30) — fewer entities per LGA = higher score
  • Funding gap (0–20) — less tracked funding = higher score

Maximum theoretical score: 190. A score above 100 indicates a severely underserved area where disadvantage, remoteness, and lack of service infrastructure compound.

Data sources: AusTender procurement contracts, state justice funding programs, political donation records (AEC), ACNC charity registry, philanthropic foundation giving, and ATO tax transparency data. All cross-referenced by ABN and mapped to postcodes and LGAs via the CivicGraph entity graph.

Limitations: The desert score measures tracked funding and entity presence within CivicGraph's indexed datasets. It does not capture all government programs (e.g., direct state service delivery, Medicare, Centrelink payments). LGAs with zero entities may have organisations not yet indexed. The score is most useful as a relative comparison between LGAs, not as an absolute measure of service access.

Explore the Data

Dive deeper into funding deserts, explore place-level data, or see how power concentrates across the system.

Full Report

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