The BTS is the primary source of forecasts of population and dwellings at the small area (travel zone) level for the Sydney Greater Metropolitan Area. This area includes the Sydney Greater Capital City Statistical Area, and the Illawarra and Hunter regions. There are 2,949 travel zones in the Sydney GMA.

The latest September 2014 Release Population Forecasts provide forecasts at travel zone level for the following variables:

• Population (Estimated Resident Population) by 5-year Age categories by Sex

• Occupied Private Dwellings (Households)

• Population in Occupied Private Dwellings

• Population in Non-Private Dwellings

The forecasts in this release are five-yearly, from 2011 to 2041.

The BTS is the primary source of forecasts of population and dwellings at the small area (travel zone) level for the Sydney Greater Metropolitan Area. This area includes the Sydney Greater Capital City Statistical Area, and the Illawarra and Hunter regions. There are 2,949 travel zones in the Sydney GMA. The latest September 2014 Release Population Forecasts provide forecasts at travel zone level for the following variables: Population (Estimated Resident Population) by 5-year Age categories by Sex Occupied Private Dwellings (Households) Population in Occupied Private Dwellings Population in Non-Private Dwellings The forecasts in this release are five-yearly, from 2011 to 2041.

This dataset contains projected population figures from Transport for NSW’s Travel Zone Projection 2016 (TZP2016) model (formally known as LU16*). The data includes: • Estimated Resident Population …Show full descriptionThis dataset contains projected population figures from Transport for NSW’s Travel Zone Projection 2016 (TZP2016) model (formally known as LU16*). The data includes: • Estimated Resident Population (ERP) (including 5-year age categories by sex); • Population in occupied private dwellings (POPD) • Population in non-private dwellings (PNPD); and • Occupied private dwellings (OPD) The TZP2016 projections reflect the Sydney Greater Metropolitan Area (GMA) and are provided on a 5-yearly basis for the period 2011-2056.

This dataset contains projected population figures from Transport for NSW’s Travel Zone Projection 2016 (TZP2016) model (formally known as LU16*). The data includes:

• Estimated Resident Population (ERP) (including 5-year age categories by sex);

• Population in occupied private dwellings (POPD)

• Population in non-private dwellings (PNPD); and

• Occupied private dwellings (OPD)

The TZP2016 projections reflect the Sydney Greater Metropolitan Area (GMA) and are provided on a 5-yearly basis for the period 2011-2056.

Household Travel Survey (HTS) is the most comprehensive source of personal travel data for the Sydney Greater Metropolitan Area (GMA). This data explores average weekday travel patterns for residents in Sydney GMA.\r \r The Household Travel Survey (HTS) collects information on personal travel behaviour. The study area for the survey is the Sydney Greater Metropolitan Area (GMA) which includes Sydney Greater Capital City Statistical Area (GCCSA), parts of Illawarra and Hunter regions. All residents of occupied private dwellings within the Sydney GMA are considered within scope of the survey and are randomly selected to participate.\r The HTS has been running continuously since 1997/981 and collects data for all days through the year – including during school and public holidays.\r \r Typically, approximately 2,000-3,000 households participate in the survey annually. Data is collected on all trips made over a 24-hour period by all members of the participating households.\r \r Annual estimates from the HTS are usually produced on a rolling basis using multiple years of pooled data for each reporting year2. All estimates are weighted to the Australian Bureau of Statistics’ Estimated Resident Population, corresponding to the year of collection3. Unless otherwise stated, all reported estimates are for an average weekday.\r \r \r \r Due to disruptions in data collection resulting from the lockdowns during the COVID-19 pandemic, post-COVID releases of HTS data are based on a lower sample size than previous HTS releases. To ensure integrity of the results and mitigate risk of sampling errors some post-COVID results have been reported differently to previous years. Please see below for more information on changes to HTS post-COVID (2020/21 onwards).\r \r 1. Data collection for the HTS was suspended during lock-down periods announced by the NSW Government due to COVID-19.\r \r 2. Exceptions apply to the estimates for 2020/21 which are based on a single year of sample as it was decided not to pool the sample with data collected pre-COVID-19. \r \r 3. HTS population estimates are also slightly lower than those reported in the ABS census as the survey excludes overseas visitors and those in non-private dwellings.\r \r Changes to HTS post-COVID (2020/21 onwards)\r \r HTS was suspended from late March 2020 to early October 2020 due to the impact and restrictions of COVID-19, and again from July 2021 to October 2021 following the Delta wave of COVID-19. Consequently, both the 2020/21 and 2021/22 releases are based on a reduced data collection period and smaller samples.\r \r Due to the impact of changed travel behaviours resulting from COVID-19 breaking previous trends, HTS releases since 2020/21 have been separated from pre-COVID-19 samples when pooled. As a result, HTS 2020/21 was based on a single wave of data collection which limited the breadth of geography available for release. Subsequent releases are based on pooled post-COVID samples to expand the geographies included with reliable estimates.\r \r Disruption to the data collection during, and post-COVID has led to some adjustments being made to the HTS estimates released post-COVID:\r \r SA3 level data has not been released for 2020/21 and 2021/22 due to low sample collection.\r LGA level data for 2021/22 has been released for selected LGAs when robust Relative Standard Error (RSE) for total trips are achieved\r Mode categories for all geographies are aggregated differently to the pre-COVID categories\r Purpose categories for some geographies are aggregated differently across 2020/21 and 2021/22.\r A new data release – for six cities as defined by the Greater Sydney Commission - is included since 2021/22.\r Please refer to the Data Document for 2022/23 (PDF, 262.54 KB) for further details.\r \r \r RELEASE NOTE\r \r The latest release of HTS data is 15 May 2025. This release includes Region, LGA, SA3 and Six Cities data for 2023/24. Please see 2023/24 Data Document for details.\r \r A revised dataset for LGAs and Six Cities for HTS 2022/23 data has also been included in this release on 15 May 2025. If you have downloaded HTS 2022/23 data by LGA and/or Six Cities from this link prior to 15/05/2025, we advise you replace it with the revised tables. If you have been supplied bespoke data tables for 2022/23 LGAs and/or Six Cities, please request updated tables.\r \r Revisions to HTS data may be made on previously published data as new sample data is appended to improve reliability of results. Please check this page for release dates to ensure you are using the most current version or create a subscription (https://opendata.transport.nsw.gov.au/subscriptions) to be notified of revisions and future releases.\r

The statistic shows the ten largest cities in Australia in 2021. In 2021, around 5.26 million people lived in Sydney and the surrounding area, making it the most populous city in Australia.

TPA provides projections of workforce, employment, and population at Travel Zone level for the Sydney Greater Metropolitan Area (GMA).

A Heat Vulnerability Index was built with Open Data for Metropolitan Sydney, for the years 2011 and 2016. Vulnerability is defined as the propensity of a population to be adversely affected by extreme heat and depends on 3 components: the exposure, sensitivity and adaptive capacity of the population. These 3 sub-indexes were calculated with various indicators that you can find as attributes to this layer. The scale of the study is the Statistical Areas 2 (SA2) of the Australian Bureau of Statistics. Bodilis, Carole ; Yenneti, Komali; Hawken, Scott (2018): Heat Vulnerability Index for Sydney. Faculty of Built Environment, UNSW Sydney.

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.

The 2022 Heat Vulnerability Index (HVI) for Greater Sydney aims to combine information on urban heat, built form and population demographics to provide a fine-grained understanding of the spatial distribution of heat vulnerable populations. The Index combines indicators of heat exposure, sensitivity to heat, and adaptive capacity to produce the composite vulnerability index. The 2022 HVI dataset is built upon the methodology established in the creation of the 2016 Sydney HVI dataset (Sun et al 2018), integrating land cover, urban heat, and demographic data, aggregated to Statistical Area Level 1 (SA1) of the Australian Statistical Geography Standard (ASGS) produced by the Australian Bureau of Statistics (ABS). Broad comparisons can be made between the 2022 and 2016 HVI datasets, however there are multiple factors that may limit direct comparability over time. This includes variations in underlying datasets, the relative nature of the HVI, and the change in size of the study area between 2016 and 2022. When undertaking comparison it is recommended to examine the changes in the underlying datasets and the absolute values of the heat exposure, sensitivity and adaptive capacity indicators. This approach helps to explain the variations in HVI and informs effective heat mitigation strategies. The 2022 HVI is most useful at the SA1 scale. It is not recommended to aggregate the HVI dataset to larger scales (i.e. average HVI for a suburb or LGA). Aggregating spatially specific and individual data to geographic areas smooths out local variation, losing locational specificity and population variation. In cases where individual human exposure is of concern, this may either increase or decrease the representation of the actual exposure of a given individual, causing the neighbourhood effect averaging problem (NEAP) (Kwan 2018). Please refer to the methodology report for more information.

The NSW Heat Vulnerability Index (HVI) dataset identifies areas to monitor where populations in the Sydney Greater Metropolitan Area are more vulnerable to the adverse effects of urban heat, as of Summer 2015-2016. HVI utilises indicators for exposure, sensitivity and adaptive capacity to calculate an overall heat vulnerability index. Expressed through the data, a vulnerability of 1 represents a combination of low exposure, low sensitivity and/or high adaptive capacity. A vulnerability of 5 represents high exposure, high sensitivity and/or low adaptive capacity. The calculation of HVI and the inputs to the exposure, sensitivity and adaptive capacity indicators are explained in the metadata. \r The HVI data is aggregated to the Australian Bureau of Statistics (ABS) Statistical Area Level 1 (SA1) polygon dataset to enable spatial analysis to support local policy and decision making. It can be used in conjunction with the NSW urban vegetation cover dataset for the same time period for broader analysis of the relationship of heat to green cover.

TPA provides projections of workforce, employment, and population at Travel Zone level for the Sydney Greater Metropolitan Area (GMA).

This SEPP contains planning provisions:\r \r - for the assessment and development of mining, petroleum production and extractive material resource proposals in NSW\r - which aim to facilitate the development of extractive resources in proximity to the population of the Sydney Metropolitan Area by identifying land which contains extractive material of regional significance\r \r This SEPP has consolidated and repealed the:\r \r - SEPP (Mining, Petroleum Production and Extractive Industries) 2007\r - Sydney Regional Environmental Plan No. 9 – Extractive Industries (No 2 – 1995)\r

Since the 1960s, Australia's urbanization rate has consistently been above 80 percent, and in 2024 it has reached its highest ever rate at 86.75 percent. Historically, Australia has been one of the most urbanized countries in the world, due to high rates of immigration since the 20th century, which were generally to coastal, urban areas. However, despite its high urbanization rate, Australia is among the largest countries in the world; therefore its population density is among the lowest in the world.

The NSW Heat Vulnerability Index (HVI) dataset identifies areas to monitor where populations in the Sydney Greater Metropolitan Area are more vulnerable to the adverse effects of urban heat, as of Summer 2015-2016. HVI utilises indicators for exposure, sensitivity and adaptive capacity to calculate an overall heat vulnerability index. Expressed through the data, a vulnerability of 1 represents a combination of low exposure, low sensitivity and/or high adaptive capacity. A vulnerability of 5 represents high exposure, high sensitivity and/or low adaptive capacity. The calculation of HVI and the inputs to the exposure, sensitivity and adaptive capacity indicators are explained in the metadata. The HVI data is aggregated to the Australian Bureau of Statistics (ABS) Statistical Area Level 1 (SA1) polygon dataset to enable spatial analysis to support local policy and decision making. It can be used in conjunction with the NSW urban vegetation cover dataset for the same time period for broader analysis of the relationship of heat to green cover.

The rent price index in Australia in the first quarter of 2025 was *****, marking an increase from the same quarter of the previous year. Rent prices had decreased in 2020; in Melbourne and Sydney, this was mainly attributed to the absence of international students during the coronavirus outbreak. The current state of the rental market in Australia The rental market in Australia has been marked by varying conditions across different regions. Among the capital cities, Sydney has long been recognized for having some of the highest average rents. As of March 2025, the average weekly rent for a house in Sydney was *** Australian dollars, which was the highest average rent across all major cities in Australia that year. Furthermore, due to factors like population growth and housing demand, regional areas have also seen noticeable increases in rental prices. For instance, households in the non-metropolitan area of New South Wales’ expenditure on rent was around ** percent of their household income in the year ending June 2024. Housing affordability in Australia Housing affordability remains a significant challenge in Australia, contributing to a trend where many individuals and families rent for prolonged periods. The underlying cause of this issue is the ongoing disparity between household wages and housing costs, especially in large cities. While renting offers several advantages, it is worth noting that the associated costs may not always align with the expectation of affordability. Approximately one-third of participants in a recent survey stated that they pay between ** and ** percent of their monthly income on rent. Recent government initiatives, such as the 2024 Help to Buy scheme, aim to make it easier for people across Australia to get onto the property ladder. Still, the multifaceted nature of Australia’s housing affordability problem requires continued efforts to strike a balance between market dynamics and the need for accessible housing options for Australians.

The Australian commercial office furniture market, valued at $2.46 billion in 2025, is projected to experience steady growth, exhibiting a Compound Annual Growth Rate (CAGR) of 3.54% from 2025 to 2033. This growth is driven by several factors, including a burgeoning demand for flexible and adaptable workspaces in response to evolving work styles and the increasing adoption of hybrid work models. The rise of coworking spaces and a focus on employee well-being are also significant contributors, pushing businesses to invest in ergonomic and aesthetically pleasing furniture. Furthermore, technological advancements in furniture design, incorporating smart features and sustainable materials, are fueling market expansion. Key players like Advanta, Krost Business Furniture, and others are strategically adapting their product portfolios to cater to these trends, offering modular designs and customizable solutions that optimize space utilization and enhance employee productivity. Competition remains robust, with companies focusing on building strong brand reputations, offering comprehensive after-sales services, and expanding their online presence to reach a broader customer base. However, the market faces some challenges. Economic fluctuations can impact investment decisions, potentially slowing down growth. Supply chain disruptions and increasing raw material costs also present headwinds. Despite these restraints, the long-term outlook remains positive, fuelled by sustained demand for modern and functional office spaces and a continuing shift towards employee-centric office designs. The market segmentation, although not explicitly detailed, likely includes categories such as seating, desks, storage, and collaborative furniture, with varying growth rates based on specific trends and technological advancements within each segment. The regional distribution of market share within Australia will likely be influenced by population density and economic activity across various states and territories, with major metropolitan areas like Sydney and Melbourne exhibiting higher demand. Key drivers for this market are: Rise in New Offices in South Korea, Wide Range of Design Broadening Consumer Base. Potential restraints include: Fluctuations in Raw Material Prices and Rise in Shipping Prices, Intense Competition from Both Local and International Players. Notable trends are: Rise in Commercial Space Construction.

The Australian taxi industry, currently valued at approximately $3.73 billion (2025 estimated), is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 9.60% from 2025 to 2033. This growth is fueled by several key factors. Increasing urbanization and population density in major Australian cities like Sydney and Melbourne are driving demand for convenient and efficient transportation solutions. The rising adoption of smartphone technology and the increasing popularity of ride-hailing apps like Uber and Ola are significantly impacting the industry, shifting consumer preferences towards online booking options. Furthermore, the expanding middle class with increased disposable income contributes to higher spending on transportation services, boosting the market. However, the industry faces challenges such as stringent government regulations regarding licensing and fares, intense competition from ride-sharing platforms, and fluctuating fuel prices which impact operational costs. The segmentation of the market reveals a strong preference for online bookings, with a growing demand for SUVs/MPVs reflecting changing consumer needs. Companies like Uber Technologies Inc., Ola, and local players like Legion Cabs and GoCatch are key players vying for market share, adapting to technological advancements and consumer expectations. The competitive landscape fosters innovation, resulting in improved service offerings, technological integrations and more competitive pricing strategies. The future of the Australian taxi industry is dynamic. While the dominance of ride-hailing apps continues to shape the market, traditional taxi services are also adapting, often incorporating technological upgrades to enhance customer experience and operational efficiency. The industry’s growth trajectory will depend on successfully navigating regulatory hurdles, maintaining cost-effectiveness in a competitive landscape, and continuing to meet evolving consumer preferences. Further diversification of services, such as airport transfers and specialized transportation, will be crucial for sustained growth. Regional variations in market penetration exist; larger metropolitan areas naturally experience greater demand and higher adoption of technology compared to more rural regions. The industry's ability to leverage technological innovations to offer efficient, safe, and affordable services will be key to sustained success. This comprehensive report provides a detailed analysis of the Australian taxi industry, covering the period from 2019 to 2033. It leverages historical data (2019-2024), focusing on the base year 2025 and forecasting market trends until 2033. The report examines key market players, including Uber Technologies Inc, Taxi Apps Pty Ltd (GoCatch), GM Cabs, and others, offering invaluable insights for investors, businesses, and policymakers. With a focus on high-growth segments, including ride-hailing and ridesharing services, this report is essential for understanding the dynamic landscape of the Australian taxi market. Recent developments include: October 2022: Ingenico, the most trusted technological partner for payment acceptance, and Live Payments, one of Australia's leading payment service providers, announced their cooperation for long-term strategic partnerships to equip retailers and taxis with seamless and convenient payment and commerce solutions., October 2022: Uber announced the addition of the 500 Polestar 2s from Australia's largest provider of vehicle subscriptions to the rideshare segment. It announced its plans to offer them as the backbone of new electric rideshare from 2023 called Custom Electric for the taxi services in Sydney., April 2023: GM Cabs, the integral taxi service in Australia with a network of 30,000 taxis, announced the official launch of Taxi-Share 2023, a progressive and hybrid taxi service that combines the best of taxis and rideshare under the GM Cabs brand.. Key drivers for this market are: Growing Tourism Industry in Australia. Potential restraints include: Varying Government Regulations on Taxi Services. Notable trends are: Online Booking Holds the Highest Share.

The Sewerage and Drainage Services industry has had limited expansion opportunities due to stunted price increases across the country. Regulatory controls and difficult economic conditions for downstream service users have forced businesses to limit price growth over the past five years, causing revenue to stagnate. Industry revenue is expected to decline at an annualised 1.1% over the five years through 2025-26, to total $12.8 billion, including a 1.3% decline anticipated in the current year. However, strong profit margins due to a lack of direct competition between service providers have limited the impact on bottom lines. Numerous service providers have also been working on futureproofing their wastewater networks by investing heavily in infrastructure upgrades. These initiatives aim to accommodate future population growth and renew ageing sewerage infrastructure. This focus on infrastructure investment can be seen in the merger of City West Water and Western Water to form Greater Western Water in Victoria. The merger led to a $1.7 billion commitment towards capital investment for western metropolitan suburbs in Melbourne, where population growth is rapid. Rising prices and demand growth are forecast to drive revenue growth over the next five years. The completion of several new and upgraded wastewater treatment plants will also enhance the industry's capability to support a growing population. Moreover, government policies and environmental challenges are set to shift the focus to initiatives like wastewater recycling. The Water Infrastructure for Sustainable and Efficient Regions (WISER) initiative will also support small-scale water infrastructure projects across regional Australia. This initiative will aid many rural sewerage and drainage service providers in significantly improving their water infrastructure to ensure longevity. Overall, revenue is projected to rise at an annualised 1.2% through the end of 2030-31, to $13.7 billion. However, profit margins are forecast to decline marginally over the period due to rising wage costs.

This SEPP contains planning provisions:

• for the assessment and development of mining, petroleum production and extractive material resource proposals in NSW
• which aim to facilitate the development of extractive resources in proximity to the population of the Sydney Metropolitan Area by identifying land which contains extractive material of regional significance

This SEPP has consolidated and repealed the:

• SEPP (Mining, Petroleum Production and Extractive Industries) 2007
• Sydney Regional Environmental Plan No. 9 – Extractive Industries (No 2 – 1995)