Overseas Migration: Overseas migration is the leading contributor to population growth for both Albury and Wodonga. Internal Migration: Albury outpaces Wodonga in net internal migration, showing it is slightly more attractive to domestic movers. Natural Growth: Wodonga's population relies more heavily on natural growth compared to Albury, suggesting a relatively younger or more family-oriented demographic profile.

Population projection data for New South Wales to the year 2031. Data is provided at Local Government Area (LGA) level.

ABS Census data extract - G09 COUNTRY OF BIRTH OF PERSON BY AGE providing a breakdown of population at LGA level and by:age groupscountry of birth of person(a)Australia(b)China (excludes SARs and Taiwan)(c)Hong Kong (SAR of China)(c)Born elsewhere(d)This data is based on place of usual residence.(a) This list consists of the most common 50 Country of Birth responses reported in the 2016 Census and 2011 Census.(b) Includes 'Australia', 'Australia (includes External Territories), nfd', 'Norfolk Island' and 'Australian External Territories, nec'.(c) Special Administrative Regions (SARs) comprise 'Hong Kong (SAR of China)' and 'Macau (SAR of China)'. (d) Includes countries not identified individually, 'Inadequately described', and 'At sea'. Excludes not stated.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.

This study is a companion effort by the Cities Commission to the Multinational Time Budget Studies conducted in 1965 and 1966 in twelve European and American countries. Samples of the Albury-Wodonga and Melbourne populations were drawn to examine use of time in both a large and a small centre. The main topic of investigation was activity over a 24-hour period, its nature, duration, location and whether any others had participated. Interview questions also sought information on activities over a longer term. Background variables included occupation, including second job (if any), hours of paid work, whether shift work was involved, and details of journey to work, birthplace, parents' birthplace, marital status, home ownership, duration of residence at current address, locale of upbringing, places of residence since age 18, preferred community size, consumer durables including vehicles, telephone renting, use of paid domestic help, religious affiliation, library use, education, current educational activities, provision for retirement, household income and head of household income. Adult females were asked about housework including care of dependent household members, and the resultant amount and use of uncommitted time.

ABS Census data extract - G19 TYPE OF LONG-TERM HEALTH CONDITION(a) BY AGE BY SEX providing a breakdown of population with long term health condition at LGA level and by:age groupssexThis table is based on place of usual residence.(a) Measures the number of people who reported that they have been told by a doctor or nurse that they have any of these long-term health conditions. Includes health conditions that have lasted or are expected to last six months or more, may occur from time to time, are controlled by medication or are in remission. (b) 'COPD' refers to Chronic Obstructive Pulmonary Disease(c) Includes any long-term health condition other than the ones listed. (d) Respondents had the option to record multiple long-term health conditions therefore the sum of total responses count will not equal the total person count. Please note that there are small random adjustments made to all values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.

Census employment and income data for persons working in creative industries and creative occupations.

This dataset consists of 14 individual datasets that underpin the interactive dashboards on the project's Data Tables webpage.

Project background:

Australian cultural and creative activity: A population and hotspot analysis is an Australian Research Council Linkage project (LP160101724) being undertaken by QUT and the University of Newcastle, in partnership with Arts Queensland, Create NSW, Creative Victoria, Arts South Australia and the Western Australian Department of Local Government, Sport and Cultural Industries.

This comprehensive project aims to grasp the contemporary dynamics of cultural and creative activity in Australia. It brings together population-level and comparative quantitative and qualitative analyses of local cultural and creative activity. The project will paint a complete national picture, while also exploring the factors that are producing local and regional creative hotspots.

Creative hotspots for study were selected in consultation with state research partners:

Queensland – Cairns, Sunshine Coast + Noosa, Gold Coast, Central West Queensland
New South Wales – Coffs Harbour, Marrickville, Wollongong, Albury
Victoria – Geelong + Surf Coast, Ballarat, Bendigo, Wodonga
Western Australia – Geraldton, Fremantle, Busselton, Albany + Denmark
South Australia – to be confirmed shortly

Statistical summaries drawn from a diverse range of data sources including the Australian Census, the Australian Business Register, IP Australia registration data, infrastructure availability lists and creative grants and rights payments as well as our fieldwork, inform hotspot reports.

Data source: ABSEPSG: 7855Socio-Economic Indexes for Areas (SEIFA) is an ABS product that ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes are based on information from the five-yearly Census of Population and Housing.SEIFA 2016 has been created from Census 2016 data and consists of four indexes: The Index of Relative Socio-economic Disadvantage (IRSD); The Index of Relative Socio-economic Advantage and Disadvantage (IRSAD); The Index of Education and Occupation (IEO); The Index of Economic Resources (IER).Each index is a summary of a different subset of Census variables and focuses on a different aspect of socio-economic advantage and disadvantage.SEIFA indexes1.Index of Relative Socio-economic Advantage / Disadvantage (IRSAD)A composite index where lower scores indicate more disadvantaged areas and higher scores indicate more advantaged areas.This index is constructed using a number of different variables that indicate both advantage (e.g., high income, having a degree qualification) and disadvantage (e.g., unemployment status, low income, number of bedrooms)2.Index of Relative Socio-economic Disadvantage (IRSD)Identifies areas with lower educational attainment, people in low-skilled occupations, low employment and other indicators of disadvantage.This index ranks areas from most disadvantaged to least disadvantaged3.Index of Economic Resources (IER)Includes variables such as rent paid, household income and mortgage payments4.Index of Education and Occupation (IEO)Includes education and occupation variablesSource: SEIFA

ABS Census data extract - G13 LANGUAGE USED AT HOME BY PROFICIENCY IN SPOKEN ENGLISH providing a breakdown of population at LGA level and by:speaks English onlyother language(a)not stated(b)other Chinese languages(c)other Indo-Aryan languages(d)other Southeast Asian Austronesian languages(e)other(f)This data is based on place of usual residence.(a) This list of languages consists of the most common Language used at home responses reported in the 2016 Census and 2011 Census. (b) Includes the categories 'Proficiency in English not stated' and 'Language and proficiency in English not stated'.(c) Comprises 'Chinese, nfd', 'Hakka', 'Wu', 'Min Nan' and 'Chinese, nec'.(d) Comprises' Indo-Aryan, nfd', 'Konkani', 'Marathi', 'Sindhi', 'Assamese', 'Dhivehi', 'Kashmiri', 'Oriya', 'Fijian Hindustani' and 'Indo-Aryan, nec'.(e) Comprises 'Bikol', 'Bisaya', 'Cebuano', 'Ilokano', 'Ilonggo (Hiligaynon)', 'Pampangan', 'Malay', 'Tetum', 'Timorese', 'Acehnese', 'Balinese', 'Iban', 'Javanese', 'Southeast Asian Austronesian Languages, nec' and 'Southeast Asian Austronesian Languages, nfd'.(f) Includes languages not identified individually, 'Inadequately described' and 'Non-verbal, so described'.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.

The Australian transportation infrastructure construction industry is experiencing robust growth, projected to reach a market size of $25.80 billion in 2025, with a Compound Annual Growth Rate (CAGR) exceeding 5.45% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing urbanization and population growth necessitate the development of efficient and expansive transportation networks, including road upgrades, rail expansions, and improved waterway and airway infrastructure. Government initiatives focused on infrastructure investment, aimed at boosting economic activity and addressing logistical challenges, are significantly contributing to this growth. Furthermore, a rising demand for sustainable and resilient infrastructure, incorporating innovative materials and construction techniques, is shaping the industry's trajectory. Key players such as CPB Contractors, Lendlease, and others are strategically positioning themselves to capitalize on these opportunities, competing for large-scale projects and driving innovation within the sector. However, the industry also faces certain challenges. Fluctuations in government spending and potential delays in project approvals can impact growth trajectories. Moreover, securing skilled labor and managing rising material costs remain critical concerns. Despite these restraints, the long-term outlook for the Australian transportation infrastructure construction industry remains positive. Continued investment in infrastructure, coupled with the adoption of advanced technologies and sustainable practices, is likely to maintain a healthy growth trajectory throughout the forecast period (2025-2033). The segmentation by type (roadways, railways, waterways, airways) offers various avenues for growth, with roadways likely to remain the dominant sector due to ongoing urbanization and the need for efficient road networks. Recent developments include: September 2023, INLAND Rail has marked the start of construction on the 170km Stockinbingal - Parkes section in New South Wales with a launch event at Forbes station. Martinus Rail has been awarded an AUD 403.5m (USD 259.3m) contract to design and construct enhancement works on the Stockinbingal - Parkes and Albury - Illabo sections. Construction on the Inland Rail project to connect Melbourne and Brisbane with a new 1600km freight corridor through Victoria, New South Wales, and Queensland started in 2018. Inland Rail will provide an alternative to the congested coastal route through Sydney. The project involves upgrading existing lines and some new construction., May 2023, The federal government-owned Australian Rail Track Corporation (ARTC) has confirmed the will utilize ground-mounted solar arrays coupled with battery energy storage systems to power more than 80 signaling sites dotted along the rail corridor when the Inland Rail line becomes operational. Following a successful trial of a solar-powered signaling system at Coolleearlee, about 50km from Moree in northern New South Wales (NSW), ARTC has approved its use at the remaining 82 signaling sites that will likely operate along the rail corridor from Albury in the state’s south to Gowrie in southeast Queensland.. Key drivers for this market are: 4., Investments in Land Transportation Infrastructure4.; Development of shipping industry. Potential restraints include: 4., Investments in Land Transportation Infrastructure4.; Development of shipping industry. Notable trends are: Investments in Land Transportation Infrastructure is Driving the Market.

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.