Please note, we recommend using the new Map Viewer in ArcGIS Online. There is an issue in Map Viewer Classic with the display of grid cell values. The clickable area of each cell is shifted to the northwest. This can result in neighbouring pixel values being displayed. The underlying data is correct, and the values display correctly in the new Map Viewer and in ArcGIS Pro. The Australian population grid 2022 is a modelled 1 km x 1 km grid representation of the estimated resident population (ERP) of Australia from 30 June 2022. The population grid is created by reaggregating estimated resident population data from Statistical Areas Level 1 (SA1) to a 1 km x 1 km grid across Australia based on point data representing residential address points. The value of each grid cell represents the estimated population density (number of people per square kilometre) within each 1 km x 1 km grid cell.

SA1 boundaries are defined by the Australian Statistical Geography Standard (ASGS) Edition 3 (2021) and the 1 km x 1 km grid is based on the National Nested Grid.

Data considerations Caution must be taken when using the population grid as it presents modelled data only; it is not an exact measure of population across Australia. Contact the Australian Bureau of Statistics (ABS) If you have questions, feedback or would like to receive updates about this web service, please email geography@abs.gov.au. For information about how the ABS manages any personal information you provide view the ABS privacy policy.

Data and geography references Source data publication: Regional population, 2022 Additional data input: ABS Address Register Geographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3, National Nested Grid Further information: Regional population methodology Source: Australian Bureau of Statistics (ABS)

The Australian population grid 2024 was created using 2024 Estimated Resident Population (ERP) by Statistical Area Level 1 2021 (SA1) data. This data was modelled to 1 kilometre square grid cells to represent the population density of Australia (people per square kilometre). This is modelled data and should be used and interpreted with caution.SA1s are defined by the Australian Statistical Geography Standard (ASGS) Edition 3 2021. The grid was constructed using the National Nested Grid Standard.Processing steps:A subset of the ABS Address Register (AR) was created to represent residential addresses as closely as possible. Indigenous Community Points (ICP) 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 SA1 boundaries to give every point an SA1 code. Points without an SA1 code (outside all SA1 regions) were dropped.ERP by SA1 was averaged across all points within each SA1. Points were converted to raster using the National Nested Grid as template. Point population values which fell within each raster cell were summed.Data and geography referencesMain source data publication: Regional population, 2023–24 financial yearGeographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3Further information: Regional population methodologySource: Australian Bureau of Statistics (ABS)Contact the Australian Bureau of StatisticsEmail geography@abs.gov.au if you have any questions or feedback about this web service.Subscribe to get updates on ABS web services and geospatial products.Privacy at the Australian Bureau of StatisticsRead how the ABS manages personal information - ABS privacy policy.

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 population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery.

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.

This map is based on information from the 1966 census, and shows distribution and numbers of population in N.S.W. and the A.C.T. The map was printed by the Commonwealth Government Printer.

The scale is approx. 30 miles = 1 inch.


(SR Map No.52714). 1 map.

Note:
This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

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.

Population density metrics for 2011 Statistical Area Level 2 (SA2) within 2011 Greater Capital City Statistical Areas (GCCSA), including SA2 Population-weighted density (PWD) for 2011 and 2014, PWD change 2011-2014, and ERP population counts by density classes. Selected Density Classes were based on the Australian Population Density Grid published by the ABS, December 2014 (cat. no. 1270.0.55.007). Corresponding population metrics for 2011 GCCSAs. PWD using standardised 1km grid cells provides a more comparable measure of the density in larger regions. It does this by weighting the density using the proportion of population living at that density. In this way the density measure reflects the density at which people actually live. This removes the effect of large unpopulated areas that may be within the regions being compared. In this way comparisons between regions are more valid.

The map service can be viewed at http://soe.terria.io/#share=s-AgXEN0N0Q95icRW7M9JIC9IYBdE

Downloadable spatial data also available below.

Map prepared by the ABS and presented as Figure BLT3 in Built environment theme of the 2016 State of the Environment Report, available at http://www.soe.environment.gov.au.

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

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 …Show full descriptionIt 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.

Changelog Version 1.0.0 (2025-07-05)

ArcGIS Instant App (Atlas) created with the following:

Population distribution by Statistical Area Level 2 webmapBasemap widget showcasing the Basemap Gallery

 Configured to open on the Topographic Basemap

Map layer widget, configured to open on the initial App load

 Show title 
 Toggle on/off
 Zoom to layer
 Show legend
 Adjust transparency 
 Swipe layer on/off
 Open data table
 Layer information
 Remove layer

Legend widget

 Will showcase the legend of visible layers 

Measurement widget

 Linear measurement 
 Area measurement 
 Find coordinates
 Elevation profiles 

Sketch widget used to add the drawing as an operational layer of the map

 Points 
 Lines 
 Polygons 
 Shapes 
 Symbols 
 Text
 Colours 

Save widget

 Export to PDF 
 Screenshot

Darker shades indicate areas with higher population density, while lighter shades represent more sparsely populated zones. This combination of labeling and color coding provides an intuitive and informative view of how Wodonga's population is distributed geographically.

Key FeaturesArcGIS Instant App (Atlas) created using the Population distribution by local government area webmap and the following widgets:BasemapMap LayerLegendMeasurementSketchSaveModification As needed, please refer to map for currency of data layers. Contact Digital Atlas of Australia

Chart and table of population level and growth rate for the Melbourne, Australia metro area from 1950 to 2025.

The Meeberrie earthquake is the largest known onshore Australian earthquake. Its magnitude was ML 7.2 and it was felt over a wide area of Western Australia as shown on the isoseismal map below, from Port Hedland in the north to Albany and Norseman in the south. Damage from the earthquake was small because of the low population density in the epicentral region, but the shaking at Meeberrie homestead was very severe; all the walls of the homestead were cracked, several rainwater tanks burst, and widespread cracking of the ground occurred. Minor non-structural damage was reported in Perth more than 500km away from the epicentre.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Urban Centres and Localities (UCLs) represent areas of concentrated urban development. They are identified using dwelling and population density criteria and data from the 2016 Census of Population and Housing. Urban Centres and Localities are designed to facilitate the visualisation and analysis of statistical data, in particular data from the Census of Population and Housing. The criteria for inclusion (such as minimum population sizes) enable users to access cross classified Census data (such as population counts by various age ranges), without limiting the usability of the associated data.Data and geography referencesSource data publication: Australian Statistical Geography Standard (ASGS) Edition 2 - Urban Centres and LocalitiesFurther information: Australian Statistical Geography Standard (ASGS) Edition 2 Significant Urban Areas, Urban Centres and Localities, Section of StateSource: Australian Bureau of Statistics (ABS)Made possible by the Digital Atlas of AustraliaThe Digital Atlas of Australia is a key Australian Government initiative being led by Geoscience Australia, highlighted in the Data and Digital Government Strategy. It brings together trusted datasets from across government in an interactive, secure, and easy-to-use geospatial platform. The Australian Bureau of Statistics (ABS) is working in partnership with Geoscience Australia to establish a set of web services to make ABS data available in the Digital Atlas of Australia.Contact the Australian Bureau of StatisticsEmail geography@abs.gov.au if you have any questions or feedback about this web service.Subscribe to get updates on ABS web services and geospatial products.Privacy at the Australian Bureau of StatisticsRead how the ABS manages personal information - ABS privacy policy.

Travel Zones (TZs) are the spatial unit of geography defined by Transport Performance and Analytics (TPA), a business unit within Transport for NSW (TfNSW). The TZ spatial layer is applied to data sources used by TfNSW for transport modelling and analysis, including the Household Travel Survey and the Census 2016 Journey to Work data.\r \r \r The Australian Bureau of Statistics (ABS) Statistical Area boundaries form the foundation of the TZ. Generally, a TZ is larger than a Statistical Area Level 1 or Mesh Block, both ABS geography definitions. The ABS Statistical Areas are based on population counts whereas TZ boundaries are defined using population, employment, housing and transport infrastructure.\r \r \r TZs are designed to have standardised trip generation levels across all zones. This causes zones to be different sizes across the metropolitan area. As with many other spatial boundaries, TZs tend to be small in areas with high land-use densities and larger in areas of lower density.\r \r \r This dataset now includes a CSV file mapping the Transit Stop Number (TSN) to the Travel Zone (TZ16). It captures the stop name, suburb and coordinates.\r \r \r Travel Zone Explorer is an interactive map where you can search for Travel Zones (TZ) and find out the current and future population in occupied private dwellings by age and sex.\r \r \r

A global map of 5 land use types at 30s (approx. 1km) resolution for 2005. The data set was generated through the statistical downscaling of the Land-use Harmonisation data set (Hurt et al 2011) at http://luh.umd.edu/. Five land use types (primary, secondary, pasture, crop, urban) are provided as separate raster layers, with the value of each cell representing the proportion of the grid cell occupied by that land use type. An additional layer representing cells defined as permanent ice (value of 1) is also provided. Lineage: Statistical downscaling was based on the following global raster layers:

Coarse Scale Land -Use: 2005 data layer of five land-use classes from the world Harmonised Land Use database.

Input covariates:- ACC.flt : Global Accessibility Index. The travel time to the nearest population centre of 50,000 or more. EARS.flt : MOD16 data set gap filled with Annual Actual Evaporations calculated as the sum of monthly EA derived using the Budkyo framework based on WorldClim climatic data, using PAWHC calculated from 1km Soil Depth from www.soilgrids.org combined with AWC from the Harmonised World Soil Database. MAT.flt: Mean Annual Temperature with maximum and minimum temperature corrected for radiation differences due to variation in terrain based on Danielson and Dean (2011) following Wilson and Gallant (2000). PTA.flt: Annual precipitation. Sum of monthly precipitation from WorldClim. TWI.flt: Topographic Wetness Index. Calculated at 9 s and upscaled to 1 km. ICE.flt: Presence of permanent ice. SLP.flt: Slope calculated at 9 s and upscaled to 1 km. SOC.flt: Soil Organic Carbon content. Weighted average of all depth classes. WATER.flt: Presence of permanent water bodies. POP.flt: Population density. CLC.flt: Consensus land-cover. 1 km land-cover product made by harmonising multiple products.

This data represents the indicative known and predicted distributions of threatened ecological communities, population and species. These data are a snapshot of data held and maintained in the Bionet – Threatened Species Profiles. The data were extracted mid-November 2013.

The base geometry is derived from a GIS intersection of a NSW Catchment management Authority Layer and IBRA Subregions layer (Interim Bio-regionalisation of Australia). For each NSW (TSC Act) and Cwth (EPBC Act) listed entity the "known" or "predicted" occurrence of each entity is attributed against the base polygon layer based. "Prediction" of occurrence should be treated as having a low confidence.

Attribution of "Known" occurrence is based on the existence of at lease one valid observation record for that polygon (locality). Validation of TS records is completed by nominated Threatened Species experts within NSW OEH (Office of Environment and Heritage). The Assignment is based on expert knowledge and is generally not assisted by distribution modelling approaches.

These data are rendered live from BioNet database to the Office of Environment and Heritage Threatened Species Web site (http://www.environment.nsw.gov.au/threatenedSpeciesApp/). See the following link for an example of a profile with indicative distribution map: http://www.environment.nsw.gov.au/threatenedspeciesapp/profile.aspx?id=10616

These web pages provide a view of the most current indicative distribution data. Users are recommended to check the currency of this product be for use. The data are indicative only and should be used with care - please refer to the readme and Q&A file for further information.