Contains latest available estimates by age and sex of the resident populations of areas of Australia as at 30 June. These estimates are provided for Statistical Areas Level 2 - 4 (SA2s - SA4s), Greater Capital City Statistical Areas (GCCSAs), and states and territories of Australia according to the current edition of the Australian Statistical Geography Standard (ASGS). Estimates are also provided for Local Government Areas (LGAs).

Contains latest available estimates of the resident populations of areas of Australia as at 30 June in each year . These estimates are provided for Statistical Areas Level 2 - 4 (SA2s - SA4s), Greater Capital City Statistical Areas (GCCSAs), and states and territories of Australia according to the current edition of the Australian Statistical Geography Standard (ASGS). Estimates are also provided for Local Government Areas (LGAs), Significant Urban Areas, Remoteness Areas, and Commonwealth and State Electoral Divisions.

Comprehensive socio-economic dataset for Australia including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

These population projections were prepared by the Australian Bureau of Statistics (ABS) for Geoscience Australia. The projections are not official ABS data and are owned by Geoscience Australia. These projections are for Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), and are projected out from a base population as at 30 June 2022, by age and sex. Projections are for 30 June 2023 to 2032, with results disaggregated by age and sex.

Method The cohort-component method was used for these projections. In this method, the base population is projected forward annually by calculating the effect of births, deaths and migration (the components) within each age-sex cohort according to the specified fertility, mortality and overseas and internal migration assumptions. The projected usual resident population by single year of age and sex was produced in four successive stages – national, state/territory, capital city/rest of state, and finally SA2s. Assumptions were made for each level and the resulting projected components and population are constrained to the geographic level above for each year.
These projections were derived from a combination of assumptions published in Population Projections, Australia, 2022 (base) to 2071 on 23 November 2023, and historical patterns observed within each state/territory.

Projections – capital city/rest of state regions The base population is 30 June 2022 Estimated Resident Population (ERP) as published in National, state and territory population, June 2022. For fertility, the total fertility rate (at the national level) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, of 1.6 babies per woman being phased in from 2022 levels over five years to 2027, before remaining steady for the remainder of the projection span. Observed state/territory, and greater capital city level fertility differentials were applied to the national data so that established trends in the state and capital city/rest of state relativities were preserved. Mortality rates are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that mortality rates will continue to decline across Australia with state/territory differentials persisting. State/territory and capital city/rest of state differentials were used to ensure projected deaths are consistent with the historical trend. Annual net overseas migration (NOM) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, with an assumed gain (at the national level) of 400,000 in 2022-23, increasing to 315,000 in 2023-24, then declining to 225,000 in 2026-27, after which NOM is assumed to remain constant. State and capital city/rest of state shares are based on a weighted average of NOM data from 2010 to 2019 at the state and territory level to account for the impact of COVID-19. For internal migration, net gains and losses from states and territories and capital city/rest of state regions are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that net interstate migration will trend towards long-term historic average flows.

Projections – Statistical Areas Level 2 The base population for each SA2 is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. The SA2-level fertility and mortality assumptions were derived by combining the medium scenario state/territory assumptions from Population Projections, Australia, 2022 (base) to 2071, with recent fertility and mortality trends in each SA2 based on annual births (by sex) and deaths (by age and sex) published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. Assumed overseas and internal migration for each SA2 is based on SA2-specific annual overseas and internal arrivals and departures estimates published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. The internal migration data was strengthened with SA2-specific data from the 2021 Census, based on the usual residence one year before Census night question. Assumptions were applied by SA2, age and sex. Assumptions were adjusted for some SA2s, to provide more plausible future population levels, and age and sex distribution changes, including areas where populations may not age over time, for example due to significant resident student and defence force populations. Most assumption adjustments were made via the internal migration component. For some SA2s with zero or a very small population base, but where significant population growth is expected, replacement migration age/sex profiles were applied. All SA2-level components and projected projections are constrained to the medium series of capital city/rest of state data in Population Projections, Australia, 2022 (base) to 2071.

Projections – Local Government Areas The base population for each LGA is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. Projections for 30 June 2023 to 2032 were created by converting from the SA2-level population projections to LGAs by age and sex. This was done using an age-specific population correspondence, where the data for each year of the projection span were converted based on 2021 population shares across SA2s. The LGA and SA2 projections are congruous in aggregation as well as in isolation. Unlike the projections prepared at SA2 level, no LGA-specific projection assumptions were used.

Nature of projections and considerations for usage The nature of the projection method and inherent fluctuations in population dynamics mean that care should be taken when using and interpreting the projection results. The projections are not forecasts, but rather illustrate future changes which would occur if the stated assumptions were to apply over the projection period. These projections do not attempt to allow for non-demographic factors such as major government policy decisions, economic factors, catastrophes, wars and pandemics, which may affect future demographic behaviour. To illustrate a range of possible outcomes, alternative projection series for national, state/territory and capital city/rest of state areas, using different combinations of fertility, mortality, overseas and internal migration assumptions, are prepared. Alternative series are published in Population Projections, Australia, 2022 (base) to 2071. Only one series of SA2-level projections was prepared for this product. Population projections can take account of planning and other decisions by governments known at the time the projections were derived, including sub-state projections published by each state and territory government. The ABS generally does not have access to the policies or decisions of commonwealth, state and local governments and businesses that assist in accurately forecasting small area populations. Migration, especially internal migration, accounts for the majority of projected population change for most SA2s. Volatile and unpredictable small area migration trends, especially in the short-term, can have a significant effect on longer-term projection results. Care therefore should be taken with SA2s with small total populations and very small age-sex cells, especially at older ages. While these projections are calculated at the single year of age level, small numbers, and fluctuations across individual ages in the base population and projection assumptions limit the reliability of SA2-level projections at single year of age level. These fluctuations reduce and reliability improves when the projection results are aggregated to broader age groups such as the five-year age bands in this product. For areas with small elderly populations, results aggregated to 65 and over are more reliable than for the individual age groups above 65. With the exception of areas with high planned population growth, SA2s with a base total population of less than 500 have generally been held constant for the projection period in this product as their populations are too small to be reliably projected at all, however their (small) age/sex distributions may change slightly. These SA2s are listed in the appendix. The base (2022) SA2 population estimates and post-2022 projections by age and sex include small artificial cells, including 1s and 2s. These are the result of a confidentialisation process and forced additivity, to control SA2 and capital city/rest of state age/sex totals, being applied to their original values. SA2s and LGAs in this product are based on the Australian Statistical Geography Standard (ASGS) boundaries as at the 2021 Census (ASGS Edition 3). For further information, see Australian Statistical Geography Standard (ASGS) Edition 3.

Made possible by the Digital Atlas of Australia The 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 Statistics If you have questions or feedback about this web service, please email geography@abs.gov.au. To subscribe to updates about ABS web services and geospatial products, please complete this form. For information about how the ABS manages any personal information you provide view the ABS privacy policy.

Data and geography references Source data publication: Population Projections, Australia, 2022 (base)

This dataset presents the preliminary estimates of the resident population by age and sex as at 30 June 2017. The data is aggregated to Greater Capital City Statistical Areas (GCCSA), according to the 2016 edition of the Australian Statistical Geography Standard (ASGS). Estimated resident population (ERP) is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence within Australia refers to that address at which the person has lived or intends to live for six months or more in a given reference year. For the 30 June reference date, this refers to the calendar year around it. Estimates of the resident population are based on Census counts by place of usual residence (excluding short-term overseas visitors in Australia), with an allowance for Census net undercount, to which are added the estimated number of Australian residents temporarily overseas at the time of the Census. A person is regarded as a usual resident if they have been (or expected to be) residing in Australia for a period of 12 months or more over a 16-month period. This data is ABS data (catalogue number: 3235.0) available from the Australian Bureau of Statistics. For more information please visit the Explanatory Notes.

This dataset presents data on population and people available from the ABS Data by Region statistics. This release of Data by Region presents various data for 2011-2019 and Census of Population and Housing data for 2011 and 2016 and is based on the Greater Capital City Statistical Area (GCCSA) 2016 boundaries. The dataset includes information in the following specified areas of population and people: Estimated Resident Population, Working Age Population, Median Age, Births and Deaths, Population Density, Internal and Overseas Migration, Aboriginal and Torres Strait Islander people, Overseas Born Proportion, Religious Affiliation and Speaks language other than English. Data by Region contains a standard set of data for each region type, depending on the availability of statistics for particular geographies. Data are sourced from a wide variety of collections, both ABS and non-ABS. When analysing these statistics, care needs to be taken as time periods, definitions, methodologies, scope and coverage can differ across collections. Where available, data have been presented as a time series - to enable users to assess changes over time. However, when looked at on a period to period basis, some series may sometimes appear volatile. When analysing the data, users are encouraged to consider the longer term behaviour of the series, where this extra information is available. For more information please visit the Explanatory Notes.

These population projections were prepared by the Australian Bureau of Statistics (ABS) for Geoscience Australia. The projections are not official ABS data and are owned by Geoscience Australia. These projections are for Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), and are projected out from a base population as at 30 June 2022, by age and sex. Projections are for 30 June 2023 to 2032, with results disaggregated by age and sex.

Method The cohort-component method was used for these projections. In this method, the base population is projected forward annually by calculating the effect of births, deaths and migration (the components) within each age-sex cohort according to the specified fertility, mortality and overseas and internal migration assumptions. The projected usual resident population by single year of age and sex was produced in four successive stages – national, state/territory, capital city/rest of state, and finally SA2s. Assumptions were made for each level and the resulting projected components and population are constrained to the geographic level above for each year.
These projections were derived from a combination of assumptions published in Population Projections, Australia, 2022 (base) to 2071 on 23 November 2023, and historical patterns observed within each state/territory.

Projections – capital city/rest of state regions The base population is 30 June 2022 Estimated Resident Population (ERP) as published in National, state and territory population, June 2022. For fertility, the total fertility rate (at the national level) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, of 1.6 babies per woman being phased in from 2022 levels over five years to 2027, before remaining steady for the remainder of the projection span. Observed state/territory, and greater capital city level fertility differentials were applied to the national data so that established trends in the state and capital city/rest of state relativities were preserved. Mortality rates are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that mortality rates will continue to decline across Australia with state/territory differentials persisting. State/territory and capital city/rest of state differentials were used to ensure projected deaths are consistent with the historical trend. Annual net overseas migration (NOM) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, with an assumed gain (at the national level) of 400,000 in 2022-23, increasing to 315,000 in 2023-24, then declining to 225,000 in 2026-27, after which NOM is assumed to remain constant. State and capital city/rest of state shares are based on a weighted average of NOM data from 2010 to 2019 at the state and territory level to account for the impact of COVID-19. For internal migration, net gains and losses from states and territories and capital city/rest of state regions are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that net interstate migration will trend towards long-term historic average flows.

Projections – Statistical Areas Level 2 The base population for each SA2 is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. The SA2-level fertility and mortality assumptions were derived by combining the medium scenario state/territory assumptions from Population Projections, Australia, 2022 (base) to 2071, with recent fertility and mortality trends in each SA2 based on annual births (by sex) and deaths (by age and sex) published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. Assumed overseas and internal migration for each SA2 is based on SA2-specific annual overseas and internal arrivals and departures estimates published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. The internal migration data was strengthened with SA2-specific data from the 2021 Census, based on the usual residence one year before Census night question. Assumptions were applied by SA2, age and sex. Assumptions were adjusted for some SA2s, to provide more plausible future population levels, and age and sex distribution changes, including areas where populations may not age over time, for example due to significant resident student and defence force populations. Most assumption adjustments were made via the internal migration component. For some SA2s with zero or a very small population base, but where significant population growth is expected, replacement migration age/sex profiles were applied. All SA2-level components and projected projections are constrained to the medium series of capital city/rest of state data in Population Projections, Australia, 2022 (base) to 2071.

Projections – Local Government Areas The base population for each LGA is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. Projections for 30 June 2023 to 2032 were created by converting from the SA2-level population projections to LGAs by age and sex. This was done using an age-specific population correspondence, where the data for each year of the projection span were converted based on 2021 population shares across SA2s. The LGA and SA2 projections are congruous in aggregation as well as in isolation. Unlike the projections prepared at SA2 level, no LGA-specific projection assumptions were used.

Nature of projections and considerations for usage The nature of the projection method and inherent fluctuations in population dynamics mean that care should be taken when using and interpreting the projection results. The projections are not forecasts, but rather illustrate future changes which would occur if the stated assumptions were to apply over the projection period. These projections do not attempt to allow for non-demographic factors such as major government policy decisions, economic factors, catastrophes, wars and pandemics, which may affect future demographic behaviour. To illustrate a range of possible outcomes, alternative projection series for national, state/territory and capital city/rest of state areas, using different combinations of fertility, mortality, overseas and internal migration assumptions, are prepared. Alternative series are published in Population Projections, Australia, 2022 (base) to 2071. Only one series of SA2-level projections was prepared for this product. Population projections can take account of planning and other decisions by governments known at the time the projections were derived, including sub-state projections published by each state and territory government. The ABS generally does not have access to the policies or decisions of commonwealth, state and local governments and businesses that assist in accurately forecasting small area populations. Migration, especially internal migration, accounts for the majority of projected population change for most SA2s. Volatile and unpredictable small area migration trends, especially in the short-term, can have a significant effect on longer-term projection results. Care therefore should be taken with SA2s with small total populations and very small age-sex cells, especially at older ages. While these projections are calculated at the single year of age level, small numbers, and fluctuations across individual ages in the base population and projection assumptions limit the reliability of SA2-level projections at single year of age level. These fluctuations reduce and reliability improves when the projection results are aggregated to broader age groups such as the five-year age bands in this product. For areas with small elderly populations, results aggregated to 65 and over are more reliable than for the individual age groups above 65. With the exception of areas with high planned population growth, SA2s with a base total population of less than 500 have generally been held constant for the projection period in this product as their populations are too small to be reliably projected at all, however their (small) age/sex distributions may change slightly. These SA2s are listed in the appendix. The base (2022) SA2 population estimates and post-2022 projections by age and sex include small artificial cells, including 1s and 2s. These are the result of a confidentialisation process and forced additivity, to control SA2 and capital city/rest of state age/sex totals, being applied to their original values. SA2s and LGAs in this product are based on the Australian Statistical Geography Standard (ASGS) boundaries as at the 2021 Census (ASGS Edition 3). For further information, see Australian Statistical Geography Standard (ASGS) Edition 3.

Data and geography references

Source data publication: Population Projections, Australia, 2022 (base) to 2071 Geographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3 Further information: Population Projections, Australia methodology Source: Australian Bureau of Statistics (ABS)

Made possible by the Digital Atlas of Australia

The 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 Statistics

Email geography@abs.gov.au if you have any questions or feedback about this

The Population Health Area (PHA) data include totals for the Greater Capital City Statistical Areas/ Rest of States/NT, States/ Territories and Australia; and for the Statistical Areas Level 3 and Level 4. Attribution: Torrens University Australia

The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:

• Year
• Month
• GCCSA (Greater Capital City Statistical Area, which is used to define capital cities)
• Date (using the first day of the month)
• fulltime: Fulltime workers
• parttime: Parttime workers
• n. Overall workers
• outorin. Estimated indoor or outdoor status

This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.

Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers.

The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."

ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).

To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).

ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Australian Bureau of Statistics (ABS) Catalogue Number: 3218.0 Population Estimates by Local Government Area, 2011 to 2012.

Dataset History

ABS Catalogue Number 3218.0 Population Estimates by Local Government Area, 2011 to 2012.

This dataset was downloaded as a single spreadsheet file (.xls) on 29 May, 2014 from the following website: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3218.02011-12?OpenDocument

(Metadata taken from the Explanatory Notes section of the ABS website http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/3218.0Explanatory%20Notes12011-12?OpenDocument)

INTRODUCTION

1 This product contains estimates of the resident population of Statistical Areas Level 2 to 4 (SA2s - SA4s) and Greater Capital City Statistical Areas (GCCSAs) of Australia. These estimates plus those for Local Government Areas, Significant Urban Areas, Remoteness Areas and Electoral Divisions are also provided in the Downloads tab of this issue.

2 To meet the conflicting demands for accuracy and timeliness there are several versions of sub-state/territory population estimates. Preliminary estimates as at 30 June are normally available by April of the following year, revised estimates twelve months later and rebased and final estimates after the following Census. The estimates in this issue are preliminary rebased for 2011, based on the results of the 2011 Census, and preliminary for 2012.

For an ABS Glossary of Terms visit:

http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/2901.0Main%20Features12011

Dataset Citation

Australian Bureau of Statistics (2013) ABS Regional Population Growth Australia 2011-2012. Bioregional Assessment Source Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/c27fc127-3743-4805-b4b6-f50712cd655f.

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;

The Metropolitan Accessibility/Remoteness Index of Australia (Metro ARIA), developed by the Hugo Centre for Migration and Population Research (previously APMRC) and sponsored by the Australian Urban Research Infrastructure Network (AURIN), provides a nationally consistent and comparable dataset that quantifies geographic accessibility within the metropolitan area. SA1 Metro ARIA is for the year 2015. Spatial coverage is the 2011 ABS Urban Centre boundaries for each of the eight Australian Capital Cities.

Figure BLT34 in Built environment. See; https://soe.environment.gov.au/theme/built-environment/topic/2016/livability-transport#built-environment-figure-BLT34

Comprehensive socio-economic dataset for Haiti including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

This dataset presents the estimates of the internal migration statistics of Australia by Greater Capital City Statistical Area (GCCSA) following the 2011 Australian Statistical Geography Standard (ASGS). The dataset spans from the 2006-07 financial year up to the 2015-16 financial year. Regional internal migration is the movement of people from one region to another within Australia (both interstate and intrastate). For example, it incorporates moves from a GCCSA to any other GCCSA within the country. Net regional internal migration is the net gain or loss of population through this movement. The ABS has developed a new series of annual regional internal migration estimates (RIME) based on the 2011 edition of the Australian Statistical Geography Standard (ASGS). The Medicare and Defence data used for estimating interstate migration is now also used to estimate internal migration below the state/territory level. A similar method was used to prepare RIME at the LGA level, based on 2011 boundaries. This data is Australian Bureau of Statistics (ABS) data (catalogue number: 3412.0) used with permission from the ABS. For more information please visit the ABS Explanatory Notes. Please note: RIME are not directly comparable with estimated resident populations (ERPs) because of the different methods and source data used to prepare each series. The combination of natural increase and net migration (internal and overseas) therefore may not correspond with change in ERP. AURIN has spatially enabled the original data.

This dataset contains statistics for deaths and mortality in Australia. It includes all deaths that occurred and were registered in Australia, including deaths of persons whose place of usual residence was overseas. Deaths of Australian residents that occurred outside Australia may be registered by individual Registrars, but are not included in Australian Bureau of Statistics (ABS) death statistics. Standardised death rates in this dataset differ from those in the ABS.Stat datasets and commentary. Standardised death rates in this dataset are averaged using data for the three years ending in the reference year. They are calculated for each calendar year and then averaged. Standardised death rates in the ABS.Stat datasets and commentary are based on death registration data for the reference year only. Null values represent data not available for publication This dataset uses deaths and estimated resident population (ERP) for Greater Capital City Statistical Area (GCCSA) of Australia for 30 June 2012 to 2020, according to the 2016 edition of the Australian Statistical Geography Standard (ASGS). ERP is final for 2012 to 2016, revised for 2017 to 2019 and preliminary for 2020, based on the 2016 Census of Population and Housing. Data has been sourced from the September 2021 release. For more information including which ERP was used in this dataset please visit the Australian Bureau of Statistics (ABS) Explanatory Notes. AURIN has spatially enabled the original data from the ABS with the 2016 GCCSA boundaries.

The Metropolitan Accessibility/Remoteness Index of Australia (Metro ARIA), developed by the Hugo Centre for Migration and Population Research (previously APMRC) and sponsored by the Australian Urban Research Infrastructure Network (AURIN), provides a nationally consistent and comparable dataset that quantifies geographic accessibility within the metropolitan area. SA1 Metro ARIA is for the year 2015. Spatial coverage is the 2011 ABS Urban Centre boundaries for each of the eight Australian Capital Cities. Figure BLT34 in Built environment. See; https://soe.environment.gov.au/theme/built-environment/topic/2016/livability-transport#built-environment-figure-BLT34

This dataset presents the estimates of the internal and overseas migration statistics of Australia by age by Greater Capital City Statistical Area (GCCSA) following the 2016 Australian Statistical Geography Standard (ASGS). The dataset spans from the 2016-17 financial year up to the 2019-20 financial year. Overseas migration is the movement of people from overseas to Australia's sub-state areas and vice-versa. It cannot be directly measured and is estimated by breaking down overseas migrant arrivals and departures at the state level to sub-state areas, using information from the most recent Census. The state-level overseas migration data is sourced from Department of Home Affairs processing systems, visa information, and incoming passenger cards, and is published in National, state and territory population. Internal migration is the movement of people across a specified boundary within Australia involving a change in place of usual residence. It cannot be directly measured and is instead estimated using administrative data. The movement of people between and within Australia's states and territories cannot be directly measured and is estimated using administrative data. Internal migration is estimated based on a combination of Census data (usual address one year ago), Medicare change of address data (provided by Services Australia), and Department of Defence records (for military personnel only). The Medicare source data is assigned to a state or territory and GCCSA for a person's departure and arrival locations, based on the postcodes of their residential addresses as registered with Medicare. Postcodes are assigned wholly to a state/territory and GCCSA based on best fit. Where a postcode is split across areas, it is assigned to the area that contains the majority of that postcode's population. For more information please visit the Regional population methodology. AURIN has spatially enabled the original data.

The final Australian National Liveability Study 2018 datasets comprise a suite of policy relevant spatial indicators of local neighbourhood liveability and amenity access estimated for residential address points across Australia's 21 largest cities, and summarised at range of larger area scales (Mesh Block, Statistical Areas 1-4, Suburb, LGA, and overall city summaries). The indicators and measures included encompass topics including community and health services, employment, food, housing, public open space, transportation, walkability and overall liveability. The datasets were produced through analysis of built environment and social data from multiple sources including OpenStreetMap the Australian Bureau of Statistics, and public transport agency GTFS feed data. These are provided in CSV format under an Open Data Commons Open Database licence. The 2018 Australian National Liveability data will be of interest to planners, population health and urban researchers with an interest in the spatial distribution of built environment exposures and outcomes for data linkage, modelling and mapping purposes. Area level summaries for the data were used to create the indicators for the Australian Urban Observatory at its launch in 2020. A detailed description of the datasets and the study has been published in Nature Scientific Data, and notes and code illustrating usage of the data are located on GitHub. The spatial data were developed by the Healthy Liveable Cities Lab, Centre for Urban Research with funding support provided from the Australian Prevention Partnership Centre #9100003, NESP Clean Air and Urban Landscapes Hub, NHMRC Centre of Research Excellence in Healthy, Liveable Communities #1061404 and an NHMRC Senior Principal Research Fellowship GNT1107672; with interactive spatial indicator maps accessible via the Australian Urban Observatory. Any publications utilising the data are not necessarily the view of or endorsed by RMIT University or the Centre of Urban Research. RMIT excludes all liability for any reliance on the data.

1. Percent of population with access (within 400m) to greenspace - PSMA Australia Urban Parks (2009) and National Parks (2011) datasets were merged and duplicate polygons dissolved to form greenspace dataset for analysis. This greenspace dataset was buffered by 400m to represent a straight line walking distance. In the process of creating the 2011 Australian Population Grid (Australian Bureau of Statistics cat. no. 1270.0.55.007), a point dataset was created to represent residential dwellings using a combination of Feb 2012 PSMA Geocoded National Address File (GNAF) , 2013 Australian Government Indigenous Locations (AGIL), 2011 PSMA Locality centroids, 2012 Gazeteer. For the purposes of the Greenspace topic for SoE, this point layer was overlaid with 2011 Mesh Blocks (MB) and 2011 MB Census population counts were apportioned across these residential population points (MB Census population count divided by the number of residential dwelling points within the MB), thereby giving each point a population count. These residential points with population counts were then overlaid with the greenspace dataset and 2011 Urban Centres and Localities (UCL). Summary statistics were run to calculate the population within 400m of greenspace in 2011 Urban Centres and Localities, then divided by the 2011 Census Usual Resident population for UCL to calculate the percentage of population within 400m of greenspace. 2. Greenspace per capita (m2) - PSMA 2015 Greenspace layer was refined to relevant greenspace types (ie. to exclude caravan parks, racecourses, airports etc.). PSMA Australia Urban Parks (2009), National Parks (2011) and Greenspace (2015) were merged to form greenspace dataset, duplicate polygons were dissolved and Albers Area m2 calculated. The greenspace dataset was merged with 2011 Urban Centres and Localities (UCLs) to create a subset of greenspace polygons within UCLs. The area of greenspace was summed within capital city UCLs, grouping by UCL name. The population within capital city UCLs from 2011 Census Usual resident population was then calculated , along with the area of greenspace per capita within the capital cities.

Data used to produce Figures BLT22 and 23 in Built environment, SoE 2016. See; https://soe.environment.gov.au/theme/built-environment/topic/2016/livability-urban-amenity#built-environment-figure-BLT22 and https://soe.environment.gov.au/theme/built-environment/topic/2016/livability-urban-amenity#built-environment-figure-BLT23

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 …Show full descriptionPopulation 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.