Data Notes:

• 'SA4 grouping’ and ‘remoteness’ describe areas within NSW. Both are ABS standard categories. SA4 group relates to a predefined geographical area, based on population and labour markets, whereas remoteness is based on density of population.

• From 2016 onwards, geographical data is reported by the ABS remoteness structure. The ABS remoteness structure uses 5 categories: Major Cities, Inner Regional, Outer Regional, Remote and Very Remote. Prior to 2016, MCEECDYA categories were used, which divided schools into four categories.

• Since 2014, the department has used a geographical structure based on the new ABS Australian Statistical Geography Standard (ASGS). Groups of ASGS Statistical Area 4 (SA4) boundaries in NSW have been combined into 11 groups for reporting and publication of department data. Previous publications compared enrolments in DEC regions. Further information on SA4 groups is available in the Statistical Bulletin Explanatory Notes.

Data Source:

• Schools and Students: Statistical Bulletin. Centre for Education Statistics and Evaluation.

NSW government schools by Rural Fire Service bushfire category. Includes school codes which can be used to link to other datasets. Data provided for the NSW GovHack, 2017.

Data Notes:

• Category 1 = heavy bush or forest
• Category 2 = light bush or scrub
• Category 3 = no bush, grass-covered land
• Buffer = no bush, but within 50 meters of category 1 or 2 bush

References:

• https://www.rfs.nsw.gov.au/plan-and-prepare/building-in-a-bush-fire-area/additional-information (see: What do the colours mean on the map?)
• https://datasets.seed.nsw.gov.au/dataset/d6f2d89f-3cdc-4da0-add2-f2da74bc0bfc/metaexport/html (see: abstract)

Data Source:

• Asset Management System (AMS), School Infrastructure NSW.

Data Notes:

• From 2016 onwards, instead of MCEEDYA remoteness categories, remoteness geographical data will be reported by the ABS remoteness structure. This is in line with national reporting. The MCEECDYA remoteness indicator divides schools into four categories: metropolitan, provincial, remote and very remote.

• Previous publications of the Statistical Bulletin compared enrolments in DoE regions. From 2014 these geographies have been discontinued and replaced with a geographical structure based on the new ABS Australian Statistical Geography Standard (ASGS). Groups of ASGS Statistical Area 4 (SA4) boundaries in NSW have been combined into 11 groups for reporting and publication of Department data.

Data Source:

• Schools and Students: 2016 Statistical Bulletin. Centre for Education Statistics and Evaluation.

The NSW Rest Areas dataset provides information on rest area sites managed by Transport for NSW (TfNSW) and other authorities, including local councils and the National Parks and Wildlife Service (NPWS). The dataset includes details such as the rest area name, vehicle category, access direction, and different facilities, e.g. toilets, picnic tables, playground etc., that are available at each site.

The dataset does not include TfNSW managed inspection bays.

In February 2025, 33 additional rest areas were added to the dataset and 11 rest areas were removed. A new attribute called has_disabled_toilet has been added to the dataset. This field provides up-to-date data regarding wheelchair accessible toilet facilities at rest area sites.

There have been data changes to the following attributes: access_direction, access_direction_cardinal, accessible, baby_change_facilities, bbq, boat_ramp, caravan_disposal, carriageway_configuration, category, distance_from, driver_reviver, emergency_phones, latitude, lga, lighting, litter_bins, longitude, lookout, pets_allowed, picnic_tables, playground, power_outlets, power_supply, region, responsible_authority, rest_area_name, road_number, shade, shelter, side_of_road, site_status, sports_ground, suburb, toilets, tourist_information, tree_shading, vehicle_type and water_supply_type.

The NSW Rest Areas dataset can be queried by API for use by the public and industry.

API will only provide extracts in JSON and GeoJSON format. For other spatial formats please download below.

The NSW Post-School Destinations and Experiences Survey (PSDES) collects information about the main destinations of recent school leavers in the 6 to 12 months after leaving school.

Data Notes

• The survey collected data on school leavers in the 6-12 months after leaving school in 2023, School leavers comprise students who completed Year 12 and students who left school while they were in Year 10, 11 or 12 (early school leavers).

• There are some caveats and limitations in the generalisability of survey findings to the total population of recent school leavers in NSW. For example, students who completed Year 12 via an alternative pathway other than the HSC, such as the International Baccalaureate, are not counted as Year 12 completers and are not covered in the survey.

• Prior to 2021 a stratified sampling approach was used for the mainstream Year 12 completer survey (excluding Aboriginal and/or Torres Strait Islander and non-Connected Community school leavers). The sampling strategy for this group changed to a census for the first time in 2021 and resulted in a marked increase in the overall proportion of responses collected from the target population.

• Time series data of destinations by student type from 2014 to 2018 should be used with caution as some counts of school leavers are estimated from lower cell counts than in later years. Estimates in the data are based on base weights which are adjusted to matched population distributions for school leaver characteristics to minimise non-response bias.

• Each table shows population estimates (as column totals) for each grouping variable and leaver type combination as well as weighted percentages for each of the 10 main destination categories included in the survey. Population estimates and destination percentage breakdowns are also included for all leavers (across leaver type). Findings are reported at a system level (across leavers from government and non-government schools).

• For a full description of notes and caveats, see the 2023 Post-School Destinations and Experiences Survey Technical Report

• See the 2023 Post-School Destinations and Experiences Survey, Annual Report and fact sheets

Data Source

NSW Post-School Destinations and Experiences Survey

Available tables in this dataset:

• Table 1 provides a breakdown of main destination by leaver type and survey year (2014 to 2023).
• Table 2 provides a breakdown of main destination by leaver type and gender (as self-identified) for 2023 only.
• Table 3 provides a breakdown of main destination by leaver type and Aboriginal status (as self-identified) for 2023 only.

The master dataset contains comprehensive information for all government schools in NSW as of 24 January 2019. Data items include school locations, latitude and longitude coordinates, school type, student enrolment numbers, electorate information, contact details and more. For more information visit the NSW Education Data Hub. Please Note: AURIN has spatially enabled the original data.

The NSW Administrative Boundaries Web Service is a dynamic map of administrative and property boundaries. Administrative Areas Boundaries depict a polygon feature class within the NSW Digital Cadastral Database maintained by LPI. The administrative boundaries provided through this web service includes: Counties, Suburbs, Parishes, Local Government Areas, State Forests, National Parks, State Electoral Districts. For detailed information, for each individual dataset contained in this web services, please see the Digital Cadastre Database Dictionary published at http://www.lpi.nsw.gov.au/mapping_and_imagery/spatial_data.

This web service allows users to easily integrate NSW Administrative Boundaries into OGC compliant spatial platforms and applications. Administrative Boundaries can be used to aggregate information for analytical purposes and analyse time series trends. Administrative boundary data in combination with geo-coded address data, demographic information and agency specific business information underpins the ability to perform high quality spatial analysis.

The NSW Administrative Boundaries Web Service is a dynamic map of administrative and property boundaries. Administrative Areas Boundaries depict a polygon feature class within the NSW Digital Cadastral Database maintained by Spatial Services (DCS). The administrative boundaries provided through this web service includes: Counties, Suburbs, Parishes, Local Government Areas, State Forests, National Parks, State Electoral Districts.

NOTE: Please contact the Customer HUB https://customerhub.spatial.nsw.gov.au/ for advice on datasets access.

Multi-age classes are made up of students drawn from different year levels. They may be established because of the uneven pattern of enrolment in the school, because of the small size of the school or where it’s considered that mixing students of different ages is academically and socially advantageous.\r \r Data Notes:\r \r * Multi-age or composite class data for individual schools was not published for 2020. The collection took place in March 2020 when school operations were severely impacted by COVID-19, so the department did not follow up potential errors in class size or class structure with numerous schools.\r \r * The 2024 class size factsheet with state level aggregate data has been published and is available here: https://data.nsw.gov.au/data/dataset/nsw-education-average-government-primary-school-class-sizes-by-school-size\r \r * Multi-age classes are often designed to match the organisation of the syllabus, which is based on ‘stages’ running over two years.\r \r * From 2017, school size is based on primary enrolment rather than school classification.\r \r * Historical data displays the data that was correct in that year.\r \r Research suggests that:\r \r * Class organisation "...will not determine either educational advantage or disadvantage..." (NSW DET 1997).\r \r * The most important factors in determining student success are the quality of the teacher and his or her teaching. (Hattie, 2003)\r \r Multi-age classes may benefit students both socially and emotionally. NSW consistently performs above the national average in NAPLAN testing. \r \r Data source:\r Centre for Education Statistics and Evaluation. NSW Department of Education.\r

Current Extent The State Vegetation Type Map (SVTM) is a regional-scale map of NSW Plant Community Types. This map represents the current extent of each Plant Community Type, Vegetation Class and …Show full descriptionCurrent Extent The State Vegetation Type Map (SVTM) is a regional-scale map of NSW Plant Community Types. This map represents the current extent of each Plant Community Type, Vegetation Class and Vegetation Formation, across all tenures in NSW. This map is updated periodically as part of the Integrated BioNet Vegetation Data program to improve quality and alignment to the NSW vegetation classification hierarchy. An SVTM pre-clearing PCT map is available here. Further information about the mapping methods is available from the State Vegetation Type Mapping Program Page Current Release C2.0.M2.1 (November2024) This release includes revisions, using the most recent NSW PCT Classification Master list (represented by “C2.0” in the version release number). PCT spatial distributions were manually edited based on user and community feedback since the previous C2.0.M2.0 release. In addition, changes were made to the Native Vegetation Extent mask which is used to create the Native Extent map. Detailed technical information is available here. Data Access Map data may be downloaded, viewed within the SEED Map Viewer, or accessed via the underlying ArcGIS REST Services or WMS for integration in GIS or business applications. The Trees Near Me NSW app provides quick access to view the map using a mobile device or desktop. Download the app from Google Play or the App Store, or access the web site at https://treesnearme.app. Map Data Type The map is supplied as ESRI Feature Class (Quickview) and 5m GeoTiff Raster, and can be viewed and analysed in most commercial and open-source spatial software packages. If you prefer to use the download package, we supply an ArcGIS v10.4 mxd and/or a layer file for suggested symbology. The raster attributes contain PCT, Vegetation Class and Vegetation Formation. Feedback and Support We welcome your feedback to assist us in continuously improving our products. To help us track and process your feedback, please use the SEED Data Feedback tool available via the SEED map viewer. For further support, contact the BioNet Team at bionet@environment.nsw.gov.au. Useful Related Data NSW BioNet Flora Survey Plots – PCT Reference Sites: full floristic plots used in the development of the quantitative Plant Community Type (PCT) classification. Currently available for eastern NSW PCTs version C2.0. NSW State Vegetation Type Map - technical notes Eastern NSW - percentage cleared calculation technical notes.

Data Notes

• Class size audits are conducted by CESE (Centre for Education Statistics and Evaluation) in March each year. Audits were not conducted in 1998, 1999, 2000 and 2001.

• Data for 2020 should be treated with caution. The collection took place in March when schools were impacted by COVID-19, so fewer data checks were carried out.

• Students attending schools for specific purposes (SSPs), students in support classes in regular schools and distance education students are excluded from average class size calculations.

• The average class size for each grade is calculated by taking the number of students in all classes that a student from that grade is in (including composite/multi age classes) divided by the total number of classes that includes a student from that grade. This can result in a lower Kindergarten to Year 6 average class size than any individual year level.

• From 2017, school size is based on primary enrolment rather than school classification.

• Schools change size, so data in Table 2 is not necessarily comparable to previous iterations in earlier fact sheets.

Data Source

Education Statistics and Measurement, Centre for Education Statistics and Evaluation.

Data quality statement

The Class Size Audit Data Quality Statement addresses the quality of the Class Size Audit dataset using the dimensions outlined in the NSW Department of Education's data quality management framework: institutional environment, relevance, timeliness, accuracy, coherence, interpretability and accessibility. It provides an overview of the dataset's quality and highlights any known data quality issues.

The NSW Koala Strategy identifies 50 koala populations in New South Wales based on the Areas of Regional Koala Significance (ARKS) identified by the NSW Government (DPIE 2020), noting that koalas are also found outside these areas.\r \r These 50 koala populations have been prioritised in 2 intervention categories:\r \r * populations for immediate investment\r * populations with key knowledge gaps.\r \r The nineteen populations for immediate investment are relatively large koala populations supported by good levels of knowledge but subject to significant threats.\r \r These populations have been prioritised for investment because we have a good understanding of their size and distribution, habitat values and the nature and intensity of threats.\r \r Through targeted investment and management, we can reduce the threats to these koala populations. Expert assessment of a range of criteria determined whether a population area would be prioritised for investment over the next five years.\r \r Many of the nineteen populations are likely to support a minimum of 1000 koalas, and in some cases, they likely support many more.\r \r Populations for immediate investment in most cases exactly match existing ARKS. In a few cases, the name of the ARKS has been amended for clarity, and the boundary of several ARKS has also been amended (see Table 1 in MS Word document).\r \r For the remaining 31 koala populations, we will address knowledge gaps through a baseline survey program to assess their population status, genetics, and health.\r \r Some information is known about these koala populations already, however, in many places there are gaps in our knowledge. Interventions to reduce threats, improve habitat and support population viability will be carried out once the status of koalas is known and key threats identified.\r \r It is likely that all koala populations will benefit from local, community- based actions, improved local planning processes and targeted research on the status of koalas and the distribution of habitat.\r \r In addition to the initial surveys, for some populations we will use ongoing monitoring to track population trends and measure the effectiveness of interventions.\r \r The intervention category of koala populations may change over time. Populations can move between categories as knowledge is improved, or populations are made more secure through strategic interventions.\r \r _Reference: DPIE 2020, Framework for the spatial prioritisation of koala conservation actions in NSW: Saving our Species Iconic Koala Project _

Enrolments of students in support classes and in schools for specific purposes by category.

Data Notes:

• Schools for Specific Purposes (SSPs) are for students with specific needs. Students in SSPs are reported according to the type of specific need rather than by their year of schooling. Students with multiple disabilities are reported according to their main disability.

• Most SSPs have permanent enrolments and include schools for students with intellectual (mild, moderate and severe) and physical disabilities, visual or hearing impairment, behaviour disorders or emotional disturbance, and students in juvenile justice centres.

• Some SSPs have no permanent enrolments because the children temporarily attending them are enrolled and counted in their own schools. These are mainly hospital schools. Some students with specific needs are enrolled in support classes in primary, secondary and central schools. Students enrolled in support classes are reported according to the type of specific need rather than by their year of schooling. Support classes for students of mixed abilities are classified according to the predominant type of specific need present in the class.

• Students in SSPs, except those in juvenile justice schools, are reported by the type of support class they are enrolled in, not by the type of SSP.

• From 2020, students in mainstream support classes are reported by their underlying grade of enrolment.

• Data has been confidentialised where necessary to suppress enrolments of 5 or fewer students, indicated by an asterisk (*).

Data Source:

• Schools and Students: Statistical Bulletin. Centre for Education Statistics and Evaluation.

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.

ABS 2011 census data presented spatially in an ESRI files geodatabase. Derived from Tabular ABS 2011 Census data for NSW joined with Meshblocks for NSW downloaded from the ABS website.

As well as published "Persons" and "Dwellings" data an additional field "Persons_km2" was derived from the persons count and spatial area of the associated Mesh Block (see Lineage).

Dataset History

2011 base level Census data for NSW was downloaded from the ABS website along with the spatial boundaries pertaining to the tabular data (NSW Mesh block shpaefiles).

Census data was joined to the Mesh block polygons based on the Mesh block ID and the combined attributes exported to a file geodatabase feature class. A field was added "Persons_km2) and a popultaion density for each mesh block polygon area was derived by dividing the "persons" in that mesh block by the polygon area (based on Aust Albers projection) factored to calculate persons per square km.

Dataset Citation

Australian Bureau of Statistics (2014) NSW 2011 Census Population Counts and Density (Spatial). Bioregional Assessment Source Dataset. Viewed 14 June 2018, http://data.bioregionalassessments.gov.au/dataset/90662127-a559-493b-9d65-df44270aeb0a.

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. ABS 2011 census data presented …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. ABS 2011 census data presented spatially in an ESRI files geodatabase. Derived from Tabular ABS 2011 Census data for NSW joined with Meshblocks for NSW downloaded from the ABS website. As well as published "Persons" and "Dwellings" data an additional field "Persons_km2" was derived from the persons count and spatial area of the associated Mesh Block (see Lineage). Dataset History 2011 base level Census data for NSW was downloaded from the ABS website along with the spatial boundaries pertaining to the tabular data (NSW Mesh block shpaefiles). Census data was joined to the Mesh block polygons based on the Mesh block ID and the combined attributes exported to a file geodatabase feature class. A field was added "Persons_km2) and a popultaion density for each mesh block polygon area was derived by dividing the "persons" in that mesh block by the polygon area (based on Aust Albers projection) factored to calculate persons per square km. Dataset Citation Australian Bureau of Statistics (2014) NSW 2011 Census Population Counts and Density (Spatial). Bioregional Assessment Source Dataset. Viewed 14 June 2018, http://data.bioregionalassessments.gov.au/dataset/90662127-a559-493b-9d65-df44270aeb0a.

The Building Feature Class sits within the National Parks and Wildlife Service (NPWS) Assets Geodatabase. The Building point layer includes Accommodation, Amenities, Commercial/Retail premises and Sheds. It also includes private buildings adjacent to Parks tagged as "Threatened Property" for emergency services.

The Assets Geodatabase is directly related to the Assets Maintenance System (AMS) which runs under SAP and contains similar fields, values and business rules. The Assets Geodatabase is the vehicle in which spatial assets are initially captured, edited and stored so that the features have coordinates and can be viewed spatially. The data is collected across the entire NSW National Parks Estate and includes some off-park features for fire management, access and mapping purposes. The spatial feature data is manually synchronised with the AMS. The two systems run side by side and are linked by an ID field. AMS is also set up to be used by other Department Planning, Industry & Environment groups eg. Botanic Gardens and Parklands and previously Marine Parks.

The database includes the following asset Feature Class types - Barrier, Bridge or Elevated Walkway, Building, Communication Equipment, Crossing, Drainage Point, Environmental Monitoring Station, Extractive industry, Facility, Fence Handrail, Fire Management Zone, Gate, Hazards, Hydraulic Point, Hydraulic Storage Point, Hydraulic Valve, Irrigation System, Landing, Landing Strip, Lookout, Natural Feature, Other Structure, Parking Area, Pipe Channel Section, Power or Communication line, Power or Communication point, Sign, Step point, Stormwater Drainage Line, Surface, Survey Mark, Tower, Track Section, Treatment Disposal System, Visitor Area, Visitor Monitoring Point. Detailed documentation is available including: - Data Dictionary (internal location - P:\Corporate\Tools\Information\Assets) - Data Model - Business Rules - Functional Location and Naming Convention

Note that for external supply the dataset is simplified with certain attribute fields being removed. Those fields that have a name prefixed with "d_" contain descriptions extracted from the original geodatabase domains.

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.

This Land and Soil Capability (LSC) dataset uses the best available soils natural resource mapping across New South Wales. It provides a broad-scale, regional view as to the dominant LSC class present for over 3000 individual mapping units through the assessment of eight key soil and landscape limitations (water erosion, wind erosion, salinity, topsoil acidification, shallow soils/rockiness, soil structure decline, waterlogging and mass movement).

The assessment of LSC is based on the mapping method and rule set developed by OEH (2012). It builds on the rural land capability classification and mapping undertaken for the central and eastern divisions of the state by the former Soil Conservation Service of NSW (Emery 1986) but with more emphasis on a broader range of soil and landscape properties.

The mapping is based on an eight class system with values ranging between 1 and 8 which represent a decreasing capability of the land to sustain landuse. Class 1 represents land capable of sustaining most landuses including those that have a high impact on the soil (e.g., regular cultivation), whilst class 8 represents land that can only sustain very low impact landuses (e.g., nature conservation).

Dataset History

The best available soils datasets were sourced to provide a single (seamless where possible) layer across NSW. Datasets collated to derive this map included:

published and draft 1:100,000 soil landscape mapping [1:100,000 scale]

published and draft 1:250,000 soil landscape mapping [1:250,000 scale]

Soil and Land Resources of the Hawkesbury Nepean Catchment [1:100,000 scale]

Soil and Land Resources of the Liverpool Plains Catchment [1:100,000 scale]

Reconnaissance Soil and Land Resources of the Murray CMA Catchment [1:100,000 & 1:250,000 scale]

Soil Landscapes of the SCA Hydrological Catchments [1:100,000 scale]

Soils landscapes of the Comprehensive Coastal Assessment (Bare Point, Jervis Bay, Batemans Bay and Ulladulla) [1:100,000 scale]

Southern Comprehensive Regional Assessment [1:100,000 scale]

Northern Comprehensive Regional Assessment [1:100,000 scale]

Reconnaissance soil landscapes of the Namoi CMA [1:100,000 scale]

Reconnaissance soil landscapes of the Upper Riverina (HSHL) [1:100,000 scale]

Reconnaissance soil landscapes of the Border Rivers/Gwydir CMA [1:100,000 scale]

Brigalow Belt South Western Regional Assessment [1:100,000 scale]

Reconnaissance Soil Landscapes of the Upper Macleay Catchment [1:100,000 scale]

Upper Murrumbidgee Soil Benchmarking project [1:100,000 scale]

Glen Innes Data Gap Reconnaissance Soils Mapping [1:100,000 scale]

Soil Information for the Nyngan 1:250,000 sheet [1:250,000 scale]

Soil Information for the Walgett 1:250,000 sheet [1:250,000 scale]

Soil Information for the Gilgandra 1:250,000 sheet [1:250,000 scale]

Reconnaissance soil landscapes of the Riverine Plains [1:500,000 scale]

Land Systems of the Western Division [1:250,000-1:500,000 scale]

Land Systems of the Cobar Peniplain Bioregion [1:250,000-1:500,000 scale]

All map units were assigned a unique master landscape code and then assessed for eight soil or landscape limitations: topsoil acidification, salinity, water erosion, wind erosion, mass movement, shallow soils/rock outcrop, soil structure decline and waterlogging. This information was stored and interpreted using a rule set (http://www.environment.nsw.gov.au/soils/20120394lsc2spubslandingpage.htm) in the Access Based Data Utility for Land and soil capability (ABDUL) expert system. The system allows for a manual override to modify LSC values when required. The most limiting LSC of the 8 hazards represents the overall LSC result for each map unit The overall LSC was linked to the geodatabase to produce the final map.

Dataset Citation

NSW Office of Environment and Heritage (2013) Land and Soil Capability mapping of NSW. Bioregional Assessment Source Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/08cacd00-81e9-4fec-8a68-c9f047bb13c8.

Export Data Access API

The master dataset contains comprehensive information for all government schools in NSW. Data items include school locations, latitude and longitude coordinates, school type, student enrolment numbers, electorate information, contact details and more.

This dataset is publicly available through the Data NSW website, and is used to support the School Finder tool.

Data Notes:

• Data relating to healthy canteen is no longer up to date as it is no longer updated by the Department, this data can be sourced through NSW health.

• Student enrolment numbers are based on the census of government school students undertaken on the first Friday of August; and LBOTE numbers are based on data collected in March.

• School information, such as addresses and contact details, are updated regularly as required, and are the most current source of information.

• Data is suppressed for indigenous and LBOTE percentages where student numbers are equal to, or less than five indicated by "np".

• NSSC out of scope schools will not have an enrolment figure.

• NSSC and LBOTE figures are updated annually in December.

• ICSEA values are updated every February with the previous year's ICSEA values. Small schools, SSPs and Senior Secondary schools do not have their ICSEA values published by ACARA.

• Family Occupation and Educational Index (FOEI) is a school-level index of educational disadvantage. Data is extracted in May and values are updated annually in December.

• Following the introduction of part-time study in secondary schools in 1993, student enrolments are generally reported in full-time equivalent units (FTE). The FTE for students studying less than 10 units, the minimum workload, is determined by the formula: 0.1 x the number of units studied and represented as a proportion of the full-time enrolment of 1.0 FTE.

Data Source:

• Education Statistics and Measurement. Centre for Education Statistics and Evaluation.

Transport for NSW provides projections of population and dwellings at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2024 (TZP24), released in January 2025.\r \r TZP24 replaces the previously published TZP22.\r \r The projections are developed to support a strategic view of NSW and are aligned with the NSW Government Common Planning Assumptions .\r \r The TZP24 Population & Dwellings Projections dataset covers the following variables:\r \r * Estimated Resident Population\r \r * Structural Private Dwellings (Regional NSW only)\r \r * Population in Occupied Private Dwellings, by 5-year Age categories & by Sex\r \r * Population in Non-Private Dwellings\r \r The projections in this release, TZP24, are presented annually from 2021 to 2031 and 5-yearly from 2031 to 2066, and are in TZ21 geography.\r \r Please note, TZP24 is based on best available data as at early 2024, and the projections incorporate results of the National Census conducted by the ABS in August 2021.\r \r Key Data Inputs used in TZP24:\r \r * 2024 NSW Population Projections – NSW Department of Planning, Housing & Infrastructure\r \r * 2021 Census data - Australian Bureau of Statistics (including dwellings by occupancy, total dwellings by Mesh Block, household sizes, private dwellings by occupancy, population age and gender, persons by place of usual residence)\r \r For a summary of the TZP24 projection method please refer to the TZP24 Factsheet .\r \r For more detail on the projection process please refer to the TZP24 Technical Guide . \r \r Additional land use information for workforce and employment as well as Travel Zone 2021 boundaries for NSW (TZ21) and concordance files are also available for download on the Open Data Hub.\r \r Visualisations of the population projections are available on the Transport for NSW Website under Data and research/Reference Information .\r \r Cautions\r \r The TZP24 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and employment projections.\r \r The projections are not based on specific assumptions about future new transport infrastructure but do take into account known land-use developments underway or planned, and strategic plans.\r \r *\tTZP24 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns.\r \r *\tThe TZP24 outputs represent a point in time set of projections (as at early 2024).\r \r *\tThe projections are not government targets.\r \r *\tTravel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results.\r \r *\tAs a general rule, TZ-level projections are illustrative of a possible future only.\r \r *\tMore specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub.\r \r *\tCaution is advised when comparing TZP24 with the previous set of projections (TZP22) due to addition of new data sources for the most recent years, and adjustments to methodology.\r \r Further cautions and notes can be found in the TZP24 Technical Guide\r \r Important note: \r \r The Department of Planning, Housing & Infrastructure (DPHI) published the 2024 NSW Population Projections in November 2024. As per DPHI’s published projections, the following variables are excluded from the published TZP24 Population and Dwellings Projections:\r \r *\tStructural Private Dwellings for Travel Zones in 43 councils across Greater Sydney, Illawarra-Shoalhaven, Central Coast, Lower Hunter and Greater Newcastle\r \r *\tOccupied Private Dwellings for Travel Zones in NSW.\r \r Furthermore, in TZP24, the Structural Private Dwellings variable aligns with the 2024 Implied Dwelling projections while the Occupied Private Dwellings variable aligns with the 2024 Households projections at SA2 level prepared by DPHI.\r \r The above variables are available upon request by contacting model.selection@transport.nsw.gov.au - Attention Place Forecasting.