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 world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Australia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

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.

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 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.

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 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.

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 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.

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

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.

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.

Urban Centres and Localities (UCLs) represent areas of concentrated urban development. They are identified using dwelling and population density criteria and data from the 2021 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 3Geographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3 - Urban Centres and LocalitiesFurther information: Australian Statistical Geography Standard (ASGS) Edition 3 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.

Additional file 3: Supplementary Table 1. Predicted 2020 population, number of existing Australian 5 km parkrun events (at July 2021), and number of proposed parkrun events, in greater capital city and regional areas for each state. Supplementary Figure 1a. Map of current and proposed events for the greater capital city (Sydney) region of New South Wales. For this and all subsequent figures, numbered locations correspond to the order of selection by the location-allocation algorithm listed in Supplementary Table 2; the same population density scale has been used for all figures. Supplementary Figure 1b. Map of current and proposed events for regional New South Wales (NSW). Note for this and subsequent regional maps, event locations in the greater capital city are suppressed because of heavy clustering. Note also that the locations selected by the algorithm represent only the centroid of the SA2 area; sometimes this coincides with a regional town, but often the nearest town is visible as a darker purple area indicating higher population density. See the online interactive map for further details. Supplementary Figure 2. Map of current and proposed events for the Northern Territory (NT). Supplementary Figure 3. Map of current and proposed events for Queensland (QLD). Supplementary Figure 4. Map of current and proposed events for South Australia (SA). Supplementary Figure 5. Map of current and proposed events for Tasmania (TAS). Supplementary Figure 6a. Map of current and proposed events for the greater capital city (Melbourne) region of Victoria. Supplementary Figure 6b. Map of current and proposed events for regional Victoria (VIC). Supplementary Figure 7a. Map of current and proposed events for the greater capital city (Perth) region of Western Australia. Supplementary Figure 7b. Map of current and proposed events for regional Western Australia (WA). Supplementary Figure 8. Map of current events for the Australian Capital Territory (ACT). Note that no new events were proposed. Supplementary Table 2. Locations of new events selected by the location-allocation algorithm.

Key Attributes:

Population (2021): Total number of residents in each SA1, sourced from the ABS 2021 Census.

Population Density: Persons per square kilometre, based on land area.

Normalized Density Score: A 0–1 scale indicating relative density within Wodonga (0 = lowest density, 1 = highest density).

Usage: This layer is ideal for spatial analysis, urban planning, and infrastructure prioritization, allowing users to assess demographic concentration, compare development intensity across neighborhoods, and correlate population pressure with environmental or urban heat indicators.

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.

These datasets represent a Human Industrial Footprint (HIF) index map and an Ecological Intactness Index (EII) map for Australia circa 2020-2024. The datasets are distributed in raster format (.tif) and have a spatial resolution of 100 m, mapped on an Australian Albers Equal Area projection (EPSG:3577).

The HIF was created by incorporating 16 nationally relevant pressure layers, also part of the dataset. The pressures used to compute the HIF were 1) intensive land uses, 2) buildings, 3) mining and quarrying, 4) human population density, 5) croplands, 6) pasturelands, 7) forestry plantations, 8) reservoirs and large dams, 9) farm dams, 10) roads, 11) railways, 12) energy transmission lines, 13) oil pipelines, 14) gas pipelines, 15) hiking trails, and 16) navigable waterways. Each pressure layer was assigned a relative score between 0 and 10 to make them comparable. The scored (scaled) pressure layers were then summed to obtain the final HIF map.

The HIF was used to derive the Ecological Intactness Index (EII). The EII is calculated using the HIF, with the intactness index value for each cell parameterised to: a) be proportional to habitat area when there is no habitat fragmentation; b) decline mono-tonically as fragmentation increases, and be sensitive to both the number of nearby patches and the separation between patches, and (c) to be proportional to habitat quality for a given total area of habitat and degree of fragmentation.

In the pressure layer folder, native and modified pasturelands are merged in the "pastures" pressure layer and paved and unpaved roads are in the "roads" layer.

The code to create these maps is also available through this repository. The code is an end‑to‑end GRASS GIS pipeline to rebuild the Human Industrial Footprint Index for continental Australia on a 100 m grid in Albers Australia Equal Area (EPSG:3577). It generates 16 pressure layers, applies hierarchical priority (Urban > Mining > Crops >Pasture), scales each 0–10, and exports individual layers plus the summed index as Cloud‑Optimised GeoTIFFs (COGs).

Acknowledgements

This research was funded by The Wilderness Society.

Contact

Further queries regarding these datasets can be directed to Ruben Venegas (r.venegas@uq.edu.au) and James Watson (james.watson@uq.edu.au).

This record provides an overview of the scope and research output of NESP Marine Biodiversity Hub Project C5 - "Quantification of risk from shipping to large marine fauna across Australia". For specific data outputs from this project, please see child records associated with this metadata. Given the substantial increases in coastal/port development along the Australian coastline, and associated increase in recreational and commercial shipping, there is an increasing potential for adverse interactions with marine species. Two risks associated with these activities for large marine fauna are ship collisions and the impact of chronic ocean noise. Research is urgently needed to quantify these risks in both a spatial and temporal context to help develop and implement appropriate management strategies. This project aims to provide directed science (species- and area-specific) to inform decision-making by the Department of Environment in its application of the EPBC Act. Planned Outputs • Initial scoping report of ship strike risk summarising what is currently known about species that were tentatively nominated as being at-risk for ship strike, the data available, shipping size/type data needed and recommendations on what species to investigate further with a qualitative ranking from easiest to most difficult. • AIS data base for the Australian EZ and initial processing protocols. • Full Australia-wide fine-scale shipping density and average speed maps for 2012 – present including information such as vessel length, beam and draft. This data will directly feed into future noise mapping. • A national map of approximate density of small vessel distribution based on available proxies such as population density, boat registration data and boat ramp locations. • A suite of distribution and density surfaces for the various species nominated during Phase 1; • Spatial and temporal risk profiles for selected species. The risk maps will range from full fine-scale maps when data is present, to coarse-scale ‘regions of concern’ for species where distribution data is limited to approximate extent. • An updated version of a database of ship strikes (historical and recent) within the Australian EEZ Report on national ship strike risk to the limits of current data and knowledge. • Report on our ship strike risk methodological developments • Report on initial shipping noise mapping • Report on the recommendations and findings of the 2017 workshop on chronic noise in the marine environment.