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

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;

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

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

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.

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

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.

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.

In financial year 2023, there was an average of **** public hospital beds per one thousand people in the Northern Territory in Australia. Victoria had the lowest public hospital bed density, with only **** beds per one thousand people.

This is Version 2 of the Australian Soil Bulk Density - Whole Earth product of the Soil and Landscape Grid of Australia.

It supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546EE212B0048

The map gives a modelled estimate of the spatial distribution of Bulk Density in soils across Australia.

The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).

Detailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html

Attribute Definition: Bulk Density of the whole soil (including coarse fragments) in mass per unit volume by a method equivalent to the core method; Units: g/cm3; Period (temporal coverage; approximately): 1950-2021; Spatial resolution: 3 arc seconds (approx 90m); Total number of gridded maps for this attribute: 18; Number of pixels with coverage per layer: 2007M (49200 * 40800); Data license : Creative Commons Attribution 4.0 (CC BY); Target data standard: GlobalSoilMap specifications; Format: Cloud Optimised GeoTIFF; Lineage: An attempt was made to update digital soil mapping of whole soil bulk density for Australia. This was an update of first attempt by Viscarra Rossel et al. (2014). Based on model evaluations using a dataset not included in any modelling, the updated version (2nd Version) represents a demonstrable improvement on the 1st version.

Since the first version, more measured site data has been made available and retrievable via the Australian SoilDataFederator. In 2014 there were 3776 sites with measured whole soil bulk density. For the new update, 6116 sites had measured data. Because of usually strong empirical relationships between bulk density, soil texture and soil carbon, the use of pedotransfer functions (to predict bulk density from soil texture and soil carbon) was performed with the intention of increasing data density and spatial coverage of data that would ultimately improve digital soil mapping prediction skill. This added a further 15735 sites after building a spatial pedotransfer function using a dataset of 12308 cases (3939 sites with bulk density, soil carbon and soil texture data).

The basic steps of the work entailed.

Use soil data federator to get pertinent soils observation data

Develop spatial pedotransfer function prediction whole soil bulk density using soil carbon and texture data.

Compile measured and inferred whole soil bulk density data (86306 cases), then setting aside a dataset of 7500 cases for external model evaluation.

Predictive models using random forest algorithm with 78806 data cases fitted. To account for uncertainties in pedotransfer function inferred data, Monte Carlo simulations were performed from the pedotransfer function model. Simulation was repeated 100 times.

Predictive model uncertainties quantified using UNEEC approach (Uncertainty Estimation based on local errors and Clustering).

Quantification of model extension limits derived using hybrid method involving multivariate convex hull analysis and count of observations.

Digital soil maps with quantified uncertainties (5th and 95th prediction interval limits) and assessment of model extrapolation risk were produced at 90m resolution for the following depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm, 100-200cm.

All processing for the generation of these products was undertaken using the R programming language. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Code - https://github.com/AusSoilsDSM/SLGA Observation data - https://esoil.io/TERNLandscapes/Public/Pages/SoilDataFederator/SoilDataFederator.html Covariate rasters - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/GetData-COGSDataStore.html

The exploration and management of mineral resources heavily rely on the availability of geoscientific data. However, the spatial distribution of these data can vary significantly across South Australia, creating challenges for comprehensive... The exploration and management of mineral resources heavily rely on the availability of geoscientific data. However, the spatial distribution of these data can vary significantly across South Australia, creating challenges for comprehensive geological analysis. Inspired by the Brazilian Geoscientific Knowledge Index (GKI) maps, this project aimed to develop a Data Density Index Map for South Australia. By visualising the distribution of critical geoscientific data, the map serves as a tool for identifying areas with high data concentrations, as well as regions that may benefit from additional data acquisition or exploration activities, ultimately facilitating decision-making and resource information management.

In June 2022, it was estimated that around 7.3 percent of Australians were aged between 25 and 29, and the same applied to people aged between 30 and 34. All in all, about 55 percent of Australia’s population was aged 35 years or older as of June 2022. At the same time, the age distribution of the country also shows that the share of children under 14 years old was still higher than that of people over 65 years old. A breakdown of Australia’s population growth Australia is the sixth-largest country in the world, yet with a population of around 26 million inhabitants, it is only sparsely populated. Since the 1970s, the population growth of Australia has remained fairly constant. While there was a slight rise in the Australian death rate in 2022, the birth rate of the country decreased after a slight rise in the previous year. The fact that the birth rate is almost double the size of its death rate gives the country one of the highest natural population growth rates of any high-income country.
National distribution of the population Australia’s population is expected to surpass 28 million people by 2028. The majority of its inhabitants live in the major cities. The most populated states are New South Wales, Victoria, and Queensland. Together, they account for over 75 percent of the population in Australia.

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

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.

Actual value and historical data chart for Australia New Business Density New Registrations Per 1 000 People Ages 15 64

13.7 (number per thousand population) in 2021.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Western Australia, Australia. The time period coverage is from 31 to -58 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This is Version 1 of the Australian Soil Bulk Density - Whole Earth product of the Soil and Landscape Grid of Australia.

The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).

These maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia.

Attribute Definition: Bulk Density of the whole soil (including coarse fragments) in mass per unit volume by a method equivalent to the core method; Units: g/cm3; Period (temporal coverage; approximately): 1950-2013; Spatial resolution: 3 arc seconds (approx 90m); Total number of gridded maps for this attribute: 18; Number of pixels with coverage per layer: 2007M (49200 * 40800); Total size before compression: about 8GB; Total size after compression: about 4GB; Data license : Creative Commons Attribution 4.0 (CC BY); Variance explained (cross-validation): 0.4%; Target data standard: GlobalSoilMap specifications; Format: GeoTIFF. Lineage: The National Soil Attribute Maps are generated by combining the best available digital soil mapping to calculate a variance weighted mean for each pixel. Two DSM methods have been utilised across and in various parts of Australia, these being;

1) Decision trees with piecewise linear models with kriging of residuals developed from soil site data across Australia. (Viscarra Rossel et al., 2015a); 2) Disaggregation of existing polygon soil mapping using DSMART (Odgers et al. 2015a).

Version 1 of the Australian Soil Property Maps combines mapping from the:

1) Australia-wide three-dimensional Digital Soil Property Maps; 2) Western Australia Polygon Disaggregation Maps; 3) South Australian Agricultural Areas Polygon Disaggregation Maps; 4) Tasmanian State-wide DSM Maps.

These individual mapping products are also available in the Data Access Portal. Please refer to these individual products for more detail on the DSM methods used.

Forecast: Density of Dentist Graduates in Australia 2023 - 2027 Discover more data with ReportLinker!

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.