Actual value and historical data chart for Australia Population Density People Per Sq Km

Australia Population Density: Inhabitants per sq km data was reported at 3.380 Person in 2022. This records an increase from the previous number of 3.340 Person for 2021. Australia Population Density: Inhabitants per sq km data is updated yearly, averaging 2.660 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 3.380 Person in 2022 and a record low of 2.220 Person in 1990. Australia Population Density: Inhabitants per sq km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Australia – Table AU.OECD.GGI: Social: Demography: OECD Member: Annual.

Historical dataset showing Australia population density by year from 1961 to 2022.

Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

View yearly updates and historical trends for Australia Population Density. Source: World Bank. Track economic data with YCharts analytics.

The Australian Population Grid 2022 was created using estimated residential population (ERP) data for Statistical Areas Level 1 (SA1). The SA1 level ERP data was then modelled down to a 1km x 1km grid across geographic Australia using various point layers that represent population. The value of each grid cell represents the population density (number of people per square kilometre) in that 1km x 1km cell. This is modelled data and caution must be used in its interpretation, as the population has NOT been measured at the 1km cell level. SA1s are defined by the Australian Statistical Geography Standard (ASGS) Edition 3 (2021) and the grid used is based on the National Nested Grid Standard.Data and geography notes: Source data publication: Regional population, 2022Geographic boundary information: Statistical Areas Level 1 (SA1) - Australian Statistical Geography Standard (ASGS) Edition 3, National Nested Grid StandardAdditional data inputs: ABS Address Register, Indigenous Community Points (ICP)Further information: Regional population methodologySource: Australian Bureau of Statistics (ABS) www.abs.gov.auProcessing step:1) A subset of the Address Register that represented residential addresses as closely as possible was made. ICP points were included where no AR point existed.SA1 centroid points were included where no AR or ICP point existed within an SA1. All these layers were combined into a single point layer (Allpoints). 2) The Allpoints layer was overlaid with the ASGS 2021 SA1 boundaries to give every point an SA1 code. Points without an SA1 code (outside all SA1 regions) were dropped. 3) Estimated Resident Population by SA1 (ERP) was averaged across all points within each SA1. 4) Points were converted to raster, using the National Nested grid as template. Point population values falling within each raster cell were summed.

This data set contains the Australian Bureau of Statistics population data for Australian states and territories. Population data was collected as part of national census’ in 1991, 1996, 2001, 2006 and 2011. Data presented is the total population for all collection districts by place of enumeration. District Boundaries differed for each census and therefore were re-projected onto the 2011 population mesh blocks to standardise the spatial extent of the reporting areas. Given the focus of this project, population data was clipped by a 50km coastal buffer.

Note: population data for census’ 1991 – 1996 - 2001 was purchased by NESP and is made publically available through by NESP

Note: population data for 2006 and 2011 was downloaded through the ABS webportal. http://www.abs.gov.au/websitedbs/censushome.nsf/home/tablebuilder?opendocument&navpos=240

Note. 2006 Census district boundaries were downloaded from the ABS website http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/2919.0.55.001Main+Features1Aug%202006?OpenDocument and 2011 population mesh blocks http://www.abs.gov.au/ausstats/abs@.nsf/mf/1270.0.55.001

This data contains geographical information in shape files that represent the population density in Australia, from 1991 to 2011. The data contains the summary polygon, state_code, cd_code19, 91_pop_dat (population count), area and density (in persons per km^2). For other data sets the count will be 96_pop_dat, 2001_pop_dat, 2006_pop_dat and 2011_pop_dat.

The ABS Australian population grid 2023 was created using 2023 Estimated Residential Population (ERP) data at the SA1 level. The SA1 level ERP data was then modelled down to a 1km x 1km grid across geographic Australia using various point layers that represent population. The value of each grid cell represents the population density (number of people per square kilometre) in that 1km x 1km cell. This is modelled data and caution must be used in its interpretation, as the population has NOT been measured at the 1km cell level. SA1s are defined by the Australian Statistical Geography Standard (ASGS) Edition 3 (2021) and the grid used is based on the National Nested Grid Standard.Data and geography notes:Source data publication: Regional population, 2022-23Geographic boundary information: Statistical Areas Level 1 (SA1)(2021) - Australian Statistical Geography Standard (ASGS) Edition 3, National Nested Grid StandardAdditional data inputs: ABS Address Register, Indigenous Community Points (ICP)Further information: Regional population methodologySource: Australian Bureau of Statistics (ABS) www.abs.gov.auProcessing steps:A subset of the Address Register was created to represent residential addresses as closely as possible. Indigenous Community Points were included where no AR point existed. SA1 centroid points were included where no AR or ICP point existed within an SA1. All these layers were combined into a single point layer (Allpoints).The Allpoints layer was overlaid with the ASGS 2021 SA1 boundaries to give every point an SA1 code. Points without an SA1 code (outside all SA1 regions) were dropped.Estimated Resident Population by SA1 (ERP) was averaged across all points within each SA1.Points were converted to raster using the National Nested grid as template. Point population values falling within each raster cell were summed.

The Census 2021 Usual Residents Population Density for SA2 data.sourced from: https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/latest-release

NEXIS (National Exposure Information System) Residential Population Density web service is a set of five raster layers, representing the density of people across Australia at different scales and resolution.

this graph was created in R:

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driven primarily by high birth rates in developing countries and advancements in healthcare. According to the United Nations, the global population surpassed 8 billion in 2023, marking a critical milestone in human history. This growth, however, is unevenly distributed across continents and countries, leading to varied population densities and urban pressures.

Surface area and population density play vital roles in shaping the demographic and economic landscape of each country. For instance, countries with large land masses such as Russia, Canada, and Australia have low population densities despite their significant populations, as vast portions of their land are sparsely populated or uninhabitable. Conversely, nations like Bangladesh and South Korea exhibit extremely high population densities due to smaller land areas combined with large populations.

Population density, measured as the number of people per square kilometer, affects resource availability, environmental sustainability, and quality of life. High-density areas face greater challenges in housing, infrastructure, and environmental management, often experiencing increased pollution and resource strain. In contrast, low-density areas may struggle with underdeveloped infrastructure and limited access to services due to the dispersed population.

Urbanization trends are another important aspect of these dynamics. As people migrate to cities seeking better economic opportunities, urban areas grow more densely populated, amplifying the need for efficient land use and sustainable urban planning. The UN reports that over half of the world’s population currently resides in urban areas, with this figure expected to rise to nearly 70% by 2050. This shift requires nations to balance population growth and density with sustainable development strategies to ensure a higher quality of life and environmental stewardship for future generations.

Through an understanding of population size, surface area, and density, policymakers can better address challenges related to urban development, rural depopulation, and resource allocation, supporting a balanced approach to population management and economic development.

It should be noted that this data is now somwhat dated!

Human population density is a surrogate indicator of the extent of human pressures on the surrounding landscapes.

Areas with high population density are associated with higher levels of stream pollution and water diversion through sewers and drains. City and urban environments are substantially changed from their pre-European condition but a changed condition is not of itself necessarily poor by societal standards. It is the impacts such as polluted run-off to waterways, air pollution, sewage disposal, household water use and predation of wildlife by pets that confer impacts on catchment condition. Human population centres have an impact well beyond the built environment.

The impact of major population centres is well expressed in the AWRC map, but is best displayed in the 500 map. The main areas of impact are the major coastal and capital cities and suburbs, including popular beachside tourist destinations. Elsewhere, the impact of population density appears to be confined to the Murray and other major river valleys.

The Australian Bureau of Statistics compiles population statistics by sampling statistical local areas (SLAas) through the national census. These data can be converted to a per catchment basis.

Interpretation of the indicator is largely unequivocal, although there are land-uses/activities (e.g. mining) where population density is not a good indicator of the degree of habitat decline. This indicator has not been validated relative to habitat decline. This indicator is easy to understand.

Data are available as:

• continental maps at 5km (0.05 deg) cell resolution for the ILZ;
• spatial averages over CRES defined catchments (CRES, 2000) in the ILZ;
• spatial averages over the AWRC river basins in the ILZ.

See further metadata for more detail.

Population data extracted from the 2005-06 Population and Housing Census data and attributed to the statistical local area polygon and then rasterised. The population density for a region is calculated by dividing the Estimated Resident Population by the land area to obtain the number of persons per square kilometre. Capital cities have been masked out of this analysis.

This data is associated with the paper 'Hohnen, Rosemary, Karleah Berris, Pat Hodgens, Josh Mulvaney, Brenton Florence, Brett P. Murphy, Sarah M. Legge, Chris R. Dickman, and John CZ Woinarski. 2020 "Pre-eradication assessment of feral cat density and population size across Kangaroo Island, South Australia." Wildlife Research 47, no. 8 (2020): 669-676.'This paper assesses feral cat density at nine sites (remote infra-red camera arrays) on Kangaroo Island, South Australia. This dataset only includes data for six of those nine camera arrays as these were the arrays collected by the first author. These arrays are referred to in the paper as Border1, Border 2, Border3, Forest 1, Forest 2, and Farmland 1. In the dataset, there are two spreadsheets of each array 1.) the locations that cameras were deployed (referred to as xx_detector_input), and 2.) a spreadsheet describing the night each individual cat was detected at each camera site (referred to as xx_detections_input). For each array, both the respective spreadsheets are in the format that can be input into the 'secr' package in the program R to calculate density. Further information on the methods used to collect this dataset can be found in the methods section of the respective manuscript.

13.7 (number per thousand population) in 2021.

Group living can select for increased immunity, given the heightened risk of parasite transmission. Yet, it also may select for increased male reproductive investment, given the elevated risk of female multiple mating. Trade-offs between immunity and reproduction are well documented. Phenotypically, population density mediates both reproductive investment and immune function in the Indian meal moth, Plodia interpunctella. However, the evolutionary response of populations to these traits is unknown. We created two replicated populations of P. interpunctella, reared and mated for 14 generations under high or low population densities. These population densities cause plastic responses in immunity and reproduction: at higher numbers, both sexes invest more in one index of immunity (phenoloxidase (PO) activity) and males invest more in sperm. Interestingly, our data revealed divergence in PO and reproduction in a different direction to previously reported phenotypic responses. Males evolving at low population densities transferred more sperm and both males and females displayed higher PO than individuals at high population densities. These positively correlated responses to selection suggest no apparent evolutionary trade-off between immunity and reproduction. We speculate that the reduced PO activity and sperm investment when evolving under high population density may be due to the reduced population fitness predicted under increased sexual conflict and/or to trade-offs between pre- and post-copulatory traits.

Retirement Notice: This item is in mature support as of November 2025 and will be retired in December 2026. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item. This map shows the purchasing power per capita in Australia in 2021, in a multiscale map (Country, State, Statistical Area Level 4, Statistical Area Level 3, Local Government Area, Statistical Area Level 2, and Statistical Area Level 1). Nationally, the purchasing power per capita is 46,706 Australian dollar. Purchasing Power describes the disposable income (income without taxes and social security contributions, including received transfer payments) of a certain area's population. The figures are in Australian dollar (AUD) per capita.The pop-up is configured to show the following information at each geography level:Purchasing power per capitaPurchasing power for various goods and servicesCounts of households by income quintilesThe source of this data is Michael Bauer Research. The vintage of the data is 2021. This item was last updated in November, 2022 and is updated every 12-18 months as new annual figures are offered.Additional Esri Resources:Esri DemographicsThis item is for visualization purposes only and cannot be exported or used in analysis.We would love to hear from you. If you have any feedback regarding this item or Esri Demographics, please let us know.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Russia is the largest country in the world by far, with a total area of just over 17 million square kilometers. After Antarctica, the next three countries are Canada, the U.S., and China; all between 9.5 and 10 million square kilometers. The figures given include internal water surface area (such as lakes or rivers) - if the figures were for land surface only then China would be the second largest country in the world, the U.S. third, and Canada (the country with more lakes than the rest of the world combined) fourth. Russia Russia has a population of around 145 million people, putting it in the top ten most populous countries in the world, and making it the most populous in Europe. However, it's vast size gives it a very low population density, ranked among the bottom 20 countries. Most of Russia's population is concentrated in the west, with around 75 percent of the population living in the European part, while around 75 percent of Russia's territory is in Asia; the Ural Mountains are considered the continental border. Elsewhere in the world Beyond Russia, the world's largest countries all have distinctive topographies and climates setting them apart. The United States, for example, has climates ranging from tundra in Alaska to tropical forests in Florida, with various mountain ranges, deserts, plains, and forests in between. Populations in these countries are often concentrated in urban areas, and are not evenly distributed across the country. For example, around 85 percent of Canada's population lives within 100 miles of the U.S. border; around 95 percent of China lives east of the Heihe–Tengchong Line that splits the country; and the majority of populations in large countries such as Australia or Brazil live near the coast.

A summary of the analysis by time-slice, including the number of data clusters; the size of the MBRs; absolute populations based on work by Williams 8; and average population density using Williams’ data divided by the continent size of 7.7 million km2.

Key information about Australia Household Expenditure per Capita

• Australia Annual Household Expenditure per Capita reached 27,595.458 USD in Jun 2016, compared with the last update number of 28,443.602 USD in Jun 2010.
• Australia Annual Household Expenditure per Capita data is updated yearly, available from Jun 2004 to Jun 2016, with an averaged value of 28,443.602 USD.
• The data reached an all-time high of 28,443.602 USD in Jun 2010 and a record low of 16,777.252 USD in Jun 2004.
• In the latest reports, Retail Sales of Australia grew 4.217 % YoY in May 2023.

*This indicator will be no longer available from March 2026, 4th onwards. CEIC has a plan to remove the non-standard frequency indicator after the standard frequency indicator has been added and be available on this table. CEIC calculates Annual Household Expenditure per Capita from annual Weekly Average Household Expenditure multiplied by 52, annual Number of Household and quarterly Total Population and converts it into USD. The Australian Bureau of Statistics provides Average Household Expenditure in local currency, Number of Household and Total Population. Federal Reserve Board average market exchange rate is used for currency conversions. Household Expenditure per Capita is in annual frequency, ending in June of each year. Household Expenditure per Capita prior to 2008 based on 2017-2018 price.