These files provide more detailed outputs from BITRE's 'Freight vehicle congestion in Australia’s five major cities - 2019' publication (see: https://www.bitre.gov.au/publications/2021/freight-vehicle-congestion-australias-five-major-cities-2019), which reported freight vehicle telematics based measures of traffic congestion for freight vehicles on 53 selected routes across Australia’s five mainland state capital cities—Sydney, Melbourne, Brisbane, Adelaide and Perth. The selected routes comprise the major motorways, highways and arterial roads within each city that service both passenger and freight vehicles.

Disclaimers: https://www.infrastructure.gov.au/disclaimers.

The Government Towns layer is a data set that reflects the official boundaries of Government Towns in South Australia as defined by the Crown Land Management Act, 2009 or preceding Acts. The polygons are based on the existing cadastral data that defines the boundaries.

This dataset is derived from data stored in Landgate’s medium scale Topographic Geodatabase (TGDB). It provides a very broad view of the states population centres. License Information Use of Fundamental Land Information published to data.wa.gov.au is subject to the conditions of a Personal Use Agreement. © Western Australian Land Information Authority (Landgate). Use of Landgate data is subject to Personal Use License terms and conditions unless otherwise authorised under approved License terms and conditions.

Please note this dataset is the most recent version of the Administrative Boundaries (AB). For previous versions of the AB please go to this url: https://data.gov.au/dataset/ds-dga-b4ad5702-ea2b-4f04-833c-d0229bfd689e/details?q=previous

Geoscape Administrative Boundaries is Australia’s most comprehensive national collection of boundaries, including government, statistical and electoral boundaries. It is built and maintained by Geoscape Australia using authoritative government data. Further information about contributors to Administrative Boundaries is available here.

This dataset comprises seven Geoscape products:

• Localities
• Local Government Areas (LGAs)
• Wards
• Australian Bureau of Statistics (ABS) Boundaries
• Electoral Boundaries
• State Boundaries and
• Town Points

Updated versions of Administrative Boundaries are published on a quarterly basis.

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Notable changes in the May 2025 release

• Victorian Wards have seen almost half of the dataset change now reflecting the boundaries from the 2024 subdivision review. https://www.vec.vic.gov.au/electoral-boundaries/council-reviews/ subdivision-reviews.

  • There have been spatial changes (area) greater than 1 km2 to 66 wards in Victoria.

• One new locality ‘Kenwick Island’ has been added to the local Government area ‘Mackay Regional’ in Queensland.

  • There have been spatial changes(area) greater than 1 km2 to the local government areas 'Burke Shire' and 'Mount Isa City' in Queensland.

• There have been spatial changes(area) greater than 1 km2 to the localities ‘Nicholson’, ‘Lawn Hill’ and ‘Coral Sea’ in Queensland and ‘Calguna’, ‘Israelite Bay’ and ‘Balladonia’ in Western Australia.

• An update to the NT Commonwealth Electoral Boundaries has been applied to reflect the redistribution of the boundaries gazetted on 4 March 2025.

• Geoscape has become aware that the DATE_CREATED and DATE_RETIRED attributes in the commonwealth_electoral_polygon MapInfo TAB tables were incorrectly ordered and did not match the product data model. These attributes have been re-ordered to match the data model for the May 2025 release.

IMPORTANT NOTE: correction of issues with the 22 November 2022 release

• On 28 November 2022, the Administrative Boundaries dataset originally released on 22 November 2022 was amended and re-uploaded after Geoscape identified some issues with the original data for 'Electoral Boundaries'.
• As a result of the error, some shapefiles were published in 3D rather than 2D, which may affect some users when importing data into GIS applications.
• The error affected the Electoral Boundaries dataset, specifically the Commonwealth boundary data for Victoria and Western Australia, including 'All States'.
• Only the ESRI Shapefile formats were affected (both GDA94 and GDA2020). The MapInfo TAB format was not affected.
• Because the datasets are zipped into a single file, once the error was fixed by Geoscape all of Administrative Boundaries shapefiles had to be re-uploaded, rather than only the affected files.
• If you downloaded either of the two Administrative Boundary ESRI Shapefiles between 22 November and 28 November 2022 and plan to use the Electoral Boundary component, you are advised to download the revised version dated 28 November 2022. Apologies for any inconvenience.

Further information on Administrative Boundaries, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on Administrative Boundaries, including software solutions, consultancy and support.

Note: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

The Australian Government has negotiated the release of Administrative Boundaries to the whole economy under an open CCBY 4.0 licence.

Users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

Administrative Boundaries © Geoscape Australia licensed by the Commonwealth of Australia under Creative Commons Attribution 4.0 International license (CC BY 4.0).

Preferred attribution for Adapted Material:

Incorporates or developed using Administrative Boundaries © Geoscape Australia licensed by the Commonwealth of Australia under Creative Commons Attribution 4.0 International licence (CC BY 4.0).

What to Expect When You Download Administrative Boundaries

Administrative Boundaries is large dataset (around 1.5GB unpacked), made up of seven themes each containing multiple layers.

Users are advised to read the technical documentation including the product change notices and the individual product descriptions before downloading and using the product.

Please note this dataset is the most recent version of the Administrative Boundaries (AB). For previous versions of the AB please go to this url: https://data.gov.au/dataset/ds-dga-b4ad5702-ea2b-4f04-833c-d0229bfd689e/details?q=previous

License Information

The monthly Building Approvals (BAPS) collection collects data relating to residential and non-residential building work above certain value limits that have been approved within the reference month. Data from this collection provides timely estimates of future building activity and is an important leading economic indicator. It also provides the sampling framework for the quarterly Building Activity Survey, which is a major contributor to the quarterly National Accounts estimates.

Python scripts, generated figures, and CDP open dataset on cities' mitigation actions in 2019 ( accessed on 6th Oct-2020) for a paper that runs multiple pre-processing, feature engineering steps to undertake two clustering approaches based on cities' nature of actions and finance.

The average commuting distance in kilometres by place of residence by major cities 2011. This information provided by the Bureau of Infrastructure, Transport and Regional Economics (BITRE). Further information can be found at www.bitre.gov.au. Australia’s commuting distance:cities and regions.\r \r Figure BLT30 in Built environment. See; https://soe.environment.gov.au/theme/built-environment/topic/2016/livability-transport#built-environment-figure-BLT30

Data hosted on data.gov.au Data hosted on data.gov.au

Supplementary Information Files for Socio-economic groups moving apart: An analysis of recent trends in residential segregation in Australia's main capital citiesWe study changes in the spatial distribution and segregation of socio-economic groups in Australia using a new data set with harmonised census data for 1991 and 2011. We find a general increase in residential segregation by education and occupation groups across the major capital cities in Australia. Importantly, these trends cannot be explained in general by changes in the demographic structure of groups and areas but rather by the rise in the over and underrepresentation of groups across areas. In particular, our analysis reveals clear diverging trends in the spatial configuration of high and low socio-economic groups as measured by their occupation and education. Whereas high-skilled groups became more concentrated in the inner parts of cities, the low-educated and those working in low-status occupations became increasingly overrepresented in outer areas. This pattern is observed in all five major capital cities, but it is especially marked in Sydney, Melbourne and Brisbane.

Data for the ACT is (C) Access canberra and licenced for reuse under the CC By 4.0 International, https://creativecommons.org/licenses/by/4.0/

Data for NSW was provided by the Office of Environment and Heritage, NSW Government.

Data for the Northern Territory was sourced from the Northern Territory Environment Protection Authority.

Data for Queensland was provided by the State of Queensland, Department of Science, Information Technology and Innovation.

Data for South Australia was created and supplied by the Environment Protection Authority, SA.

Data for Tasmania was provided by EPA Tasmania, DPIPWE.

Data for Victoria was provided by the Environment Protection Authority Victoria.

Data for Western Australia was provided by the Western Australian Department of Environment Regulation.

Data used to produce figure ATM36 of the Atmosphere theme of SoE2016 available at https://soe.environment.gov.au/theme/ambient-air-quality/topic/2016/ozone#ambient-air-quality-figure-ATM36

About this dataset

Context

The dataset tabulates the Au Gres household income by gender. The dataset can be utilized to understand the gender-based income distribution of Au Gres income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Au Gres, MI annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Au Gres, MI annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Au Gres income distribution by gender. You can refer the same here

Species occurrence data from the Atlas of Living Australia (ALA), between 1900 and 2023, were used to create data summaries of native species in terrestrial bioregions (IBRA7). This data collection comprises two datasets: counts of native species in each terrestrial bioregion, and lists of native species with taxonomic information and EPBC status in each terrestrial bioregion.

The counts of native species by bioregion informed an analysis of change in the proportion of species likely to persist over the very long term (S), using the species-area relationship (SAR) with a z-value of 0.25 (S = A^z), and average condition (A) within each bioregion over a time series from the Habitat Condition Assessment System (HCAS) version 3.0. A national-level indicator can then be derived as a species richness weighted average of the bioregional analysis. The counts of EPBC Act threatened species by bioregions is used to inform an interpretation of the condition status of each bioregion. The lists of native species by bioregion provide a basis for an updated analysis that takes into account the fact that species are shared between bioregions and this has an impact on the proportion of species likely to persist over the very long term, when summarised at a national level. These outputs support interpretation of the HCAS and National Connectivity Index (NCI) for the Australian Government’s environment corporate performance measure EN01 (2023-24 Annual Report of the Department of Climate Change, Energy, the Environment and Water). This data collection may also be relevant for other types of analysis at the bioregional level or with different data inputs for the SAR analysis.

The ALA aggregates data from hundreds of different data providers, using different methods, into a single database. Consequently, observations in the ALA display spatial, temporal, and taxonomic bias that ensure care must be taken in their interpretation in downstream analysis. When summarising to the bioregional scale, survey effort is broadly correlated with accessibility, meaning that bioregions near major cities may appear disproportionately biodiverse relative to more remote regions. Lineage: All species occurrence data aggregated by the ALA as of 25 June 2024 were downloaded and filtered using the galah R package to include only records:

• passing the ALA general data quality profile (https://support.ala.org.au/support/solutions/articles/6000240256-getting-started-with-the-data-quality-filters) • occurring in the years 1900-2023 • where the taxon was identified to at least species level • identified within an IBRA terrestrial bioregion

A secondary download without the ALA data quality profile was additionally carried out to retrieve records that would have been initially excluded on the grounds of coordinate uncertainty. Records with a high degree of coordinate uncertainty (e.g. in the case of some highly threatened species) were included if their location had been indexed against an IBRA7 bioregion.

Species were considered native if they were not listed on the Global Register of Introduced and Invasive Species - Australia (version 1.10). Species on the GRIIS were mapped to ALA names, and this was then used as the basis for excluding introduced and invasive species from the downloaded records.

Two summary datasets were created based on these filtered records.

Counts of native species: This dataset comprises aggregated counts of records of native species within each terrestrial bioregion, and the total number of native species recorded in the dataset across bioregions. The summary dataset is published as native_spp_counts_bioregion.csv and contains the following elements:

1. IBRA7 terrestrial bioregion
2. Count of native species in the given bioregion
3. Total number of native species across all bioregions

List of taxa in bioregions: This dataset comprises taxonomic information and EPBC status for native species in each bioregion, and is published as native_taxon_list_bioregions.csv. EPBC status of taxa was inferred by mapping names of taxa on the EPBC list to ALA names, and joining these to the downloaded records. The dataset contains the following elements:

1. Kingdom
2. Phylum
3. Class
4. Order
5. Family
6. Genus
7. Species
8. Scientific name
9. Taxon rank
10. IBRA7 terrestrial bioregion
11. EPBC status

The data_sources.csv file includes information on the source datasets within the Atlas of Living Australia that contributed to this collection.

Abstract This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. This is a virtual dataset as the original is too large to upload to the registry. It may be accessed via the State of Victoria www.data.vic.gov.au Part of the Vicmap Features of Interest dataset series. This layer is derived from the Register of Geographic Names. Named locations described in this layer include town names, buildings/structures and place names …Show full descriptionAbstract This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. This is a virtual dataset as the original is too large to upload to the registry. It may be accessed via the State of Victoria www.data.vic.gov.au Part of the Vicmap Features of Interest dataset series. This layer is derived from the Register of Geographic Names. Named locations described in this layer include town names, buildings/structures and place names in general.These locations are stored as named points. The layers primary function is to support production of map annotation and as a general reference for localities. The Register is the primary reference for official names and their applications. The Register holds the status of names (e.g. official; official alternative; official historical; etc). To provide the official legal name of a place or feature or asset as in section 18 of the Geographic Place Names Act 1998. Purpose To provide accurate locations to named features of interest in Victoria Dataset History This data was derived from the Register of Geographic Names. Description: 1:25 000 maps (approx. 100m accuracy); 1:100 000 maps (approx. 1000m accuracy) Determination: Comparison to independent source Vertical Accuracy (m): N/A (no height data maintained) Dataset Citation Victorian Department of Environment, Land, Water and Planning (2016) Vicmap towns, virtual dataset.. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/bc953598-7bb2-4667-8ff2-e2849234b82d.

This dataset presents the footprint of economic activity for Australia's capital cities. The data is aggregated to Statistical Area Level 2 (SA2) from the 2011 Australian Statistical Geography Standard (ASGS) and spans the year of 2014. This data has been created by the Grattan Institute for the Mapping Australia's Economy: Cities as Engines of Prosperity Report, Kelly, J-F., Donegan, P., Chisholm, C., & Oberklaid, M. published 20 July 2014. The report maps the Australian economy by the location of economic activity, defined as the dollar value of goods and services produced by workers within a particular area. It finds that economic activity is concentrated most heavily in the central business districts (CBDs) and inner areas of large cities. For more information including the data creation methodology, please refer to the Mapping Australia's Economy: Cities as Engines of Prosperity Report. Please note: AURIN has spatially enabled the original data using the ASGS 2011 SA2 Digital Boundaries.

About this dataset

Context

The dataset tabulates the Au Sable charter township median household income by race. The dataset can be utilized to understand the racial distribution of Au Sable charter township income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Au Sable charter Township, Michigan median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Au Sable charter Township, Michigan (2021, in 2022 inflation-adjusted dollars)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Au Sable charter township median household income by race. You can refer the same here

This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for Local Government Areas in Australia.The ASGS Local Government Areas are an ABS approximation of gazetted local government boundaries as defined by each State and Territory Local Government Department. Local Government Areas cover incorporated areas of Australia. Incorporated areas are legally designated parts of a State or Territory over which incorporated local governing bodies have responsibility. The major areas of Australia not administered by incorporated bodies are the northern parts of South Australia, and all of the Australian Capital Territory and the Other Territories. These regions are identified as ‘Unincorporated’ in the ASGS Local Government Areas structure.More information on local governments can be found at the Australian Local Government Association website: http://www.alga.asn.au The suffix on Long Official Name Local Government Area indicates the Local Government Area status: Cities (C), Areas (A), Rural Cities (RC), Boroughs (B), Shires (S), Towns (T), Regional Councils (R), Municipalities/Municipal Councils (M), District Councils (DC), Regional Councils (RegC), Aboriginal Councils (AC).Processors and tools are using this data.EnhancementsAdd ISO 3166-3 codes.Simplify geometries to provide better performance across the services.

Data Notes:

• 'SA4 grouping’ and ‘remoteness’ describe areas within NSW. Both are ABS standard categories. SA4 group relates to a predefined geographical area, based on population and labour markets, whereas remoteness is based on density of population.

• From 2016 onwards, geographical data is reported by the ABS remoteness structure. The ABS remoteness structure uses 5 categories: Major Cities, Inner Regional, Outer Regional, Remote and Very Remote. Prior to 2016, MCEECDYA categories were used, which divided schools into four categories.

• Since 2014, the department has used a geographical structure based on the new ABS Australian Statistical Geography Standard (ASGS). Groups of ASGS Statistical Area 4 (SA4) boundaries in NSW have been combined into 11 groups for reporting and publication of department data. Previous publications compared enrolments in DEC regions. Further information on SA4 groups is available in the Statistical Bulletin Explanatory Notes.

Data Source:

• Schools and Students: Statistical Bulletin. Centre for Education Statistics and Evaluation.

First home benefits received for top 20 NSW suburbs and towns - last 12 months.

With 8.7 Million Businesses in Australia , Techsalerator has access to the highest B2B count of Data/Business Data in the country.

Thanks to our unique tools and large data specialist team, we are able to select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

Whether you are looking for an entire fill install, access to our API's or if you are just looking for a one-time targeted purchase, get in touch with our company and we will fulfill your international data need.

At Techsalerator we cover all regions and cities in Australia. A few listed:

Regions : New South Wales (Sydney) Queensland (Brisbane) South Australia (Adelaide) Tasmania (Hobart) Victoria (Melbourne) Western Australia (Perth)

Cities : name Sydney Melbourne Brisbane Perth Adelaide Gold Coast Canberra Newcastle Wollongong Logan City Geelong Hobart Townsville Cairns Toowoomba Darwin Rockingham Launceston Bendigo Ballarat Mandurah Mackay Bundaberg Bunbury Maitland Armadale Rockhampton Adelaide Hills South Brisbane Hervey Bay Reservoir Tamworth Wagga Wagga Albury Berwick Port Macquarie Queanbeyan Orange Blacktown Shepparton Caloundra Hoppers Crossing Werribee Melton Castle Hill Saint Albans Nowra Frankston Frankston East Rowville Warrnambool Baulkham Hills Albany Mount Waverley St Albans Auburn Bathurst Pakenham South Point Cook Dubbo Epping Wodonga Kalgoorlie Bankstown Mill Park Gladstone Kwinana Lismore Mildura Preston Sunbury Hurstville Narre Warren South Noble Park Southport Kellyville Port Stephens Banora Point Doncaster East Croydon Geraldton Maroubra Coffs Harbour Mosman Richmond Narre Warren Randwick Strathfield Bundoora Alice Springs Quakers Hill Endeavour Hills Palmerston Coburg Dandenong Fremantle Ferntree Gully Campsie Kew Hampton Park Canning Vale Glen Iris Mount Gambier Marrickville Northcote Granville Mount Isa Keysborough Armidale Morphett Vale Dianella Forest Lake Mornington Thornlie Ashfield Traralgon Dandenong North Busselton Cabramatta Greystanes Tarneit Maryborough Caboolture Kirwan Langwarrin Carlingford Liverpool Caringbah Brighton Glenferrie Hawthorn Hawthorn South Goulburn Boronia Woodridge Booval Thomastown Cheltenham Punchbowl Prospect Greensborough Gawler Burnie Balwyn North Lalor Brunswick Hornsby St Clair Springvale Wheelers Hill Craigieburn Whyalla Glenroy Camberwell Malvern East Murray Bridge Echuca Devonport Roxburgh Park Glenmore Park Epping Ballajura Essendon Cherrybrook Altona Meadows Cranbourne Katoomba Surfers Paradise Parramatta Broken Hill Doncaster Eltham Fairfield Morayfield Engadine Eastwood Saint Kilda Highton Mulgrave Forster Wantirna South Dee Why Thornbury Wahroonga Frankston South Wyndham Vale Gosnells Mount Eliza Willetton Carrum Downs North Ryde Mount Martha Wangaratta Sunnybank Hills Cronulla Sunshine West Taree Earlwood Sunnybank South Grafton Cessnock Hillside Westmead Carnegie Nerang Narangba Deer Park Taylors Lakes Deception Bay Umina Seaford Burwood Yagoona West Pennant Hills Paralowie Lilydale Moe Clayton Lara Griffith Bracken Ridge Eight Mile Plains Parafield Gardens Prestons Buderim Brighton East Carindale Port Hedland Duncraig Pascoe Vale Rochedale South Coorparoo Meadow Heights Mitcham Casula Bossley Park Cranbourne North Caulfield North Lakemba Kingston Grovedale Horsham Bentleigh Ballina Kingsford Lidcombe Carlton Wantirna Manly Ingleburn Burleigh Waters Elwood Cleveland Victoria Point Yarraville Singleton Bongaree Raymond Terrace Mount Druitt Bacchus Marsh Newtown Moonee Ponds Palm Beach Ascot Vale Morwell Port Melbourne Yeppoon Keilor East Port Augusta Port Pirie Footscray Williamstown Sale Coogee Templestowe Lower Brunswick West Hawthorn East Surrey Hills Port Lincoln Doonside Concord Toongabbie Dulwich Hill Balwyn Miranda Toorak Beaumaris Port Kennedy Broome Fawkner Scarborough St Kilda East Inala Warwick Rosebud Hampton Como Ashwood Chadstone Marsfield Kiama Mayfield Leichhardt Springvale South Goonellabah Port Augusta West Geelong West Lavington Doreen Newport Greenvale Blackburn Burwood West Ryde Kingswood Park Penrith Varsity Lakes Donvale Muswellbrook Taylors Hill Bateau Bay North Melbourne Wynnum West Karratha Charlestown Wynnum Penshurst Mentone Paddington Caringbah South Clayton South Happy Valley Diamond Creek Redfern North Fitzroy Warnbro Vermont South Sandy Bay East Maitland South Perth Lithgow Bayswater Manly West Parkdale Caulfield South Gympie Bairnsdale Bowen Nunawading Samford Valley Wanneroo Mount Gravatt East Altona North Caroline Springs Bulleen Kensington Gladesville Menai Bondi Beach Well...

Australia Population Density: People per Square Km data was reported at 3.382 Person/sq km in 2022. This records an increase from the previous number of 3.339 Person/sq km for 2021. Australia Population Density: People per Square Km data is updated yearly, averaging 2.263 Person/sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 3.382 Person/sq km in 2022 and a record low of 1.365 Person/sq km in 1961. Australia Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;