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The Estimation of Temporary Populations in Australia

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Demography for Planning and Policy: Australian Case Studies

Part of the book series: Applied Demography Series ((ADS,volume 7))

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Abstract

Temporary or non-resident populations can generate significant demand for goods and services within local areas with implications for planning and service provision, fiscal allocation and emergency preparedness. Recognition of the importance of temporary populations has grown considerably in recent decades, both in Australia and overseas, however a standard methodology for their estimation has yet to be advanced. This paper reviews available data and methods for the estimation of temporary populations in Australia. Three broad approaches are identified: direct approaches which draw on censuses and surveys to estimate temporary stocks and flows; indirect methods, which rely on symptomatic indicators of population flux; and data derived from information and communication technologies. A model framework capable of integrating multiple data sets, VisPOP, is then described. The utility of different data sets for the estimation of temporary populations in Australia are assessed using Noosa, Queensland as a case study. While no single data source is likely to prove a panacea for the estimation of temporary populations in all locations and contexts, results suggest that it is possible to integrate multiple data sets to produce reliable estimates of non-resident populations.

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Notes

  1. 1.

    The population temporarily absent from a region can also be estimated by substituting information on the number of people temporarily away from a region and the average duration of absence.

  2. 2.

    VisPop prediction intervals are not shown.

References

  • ABS. (2004, November). Service population concepts (pp. 11–12). Paper presented at the Population Estimates Technical Workshop, Adelaide.

    Google Scholar 

  • ABS. (2012). Reflecting a nation: Stories from the 2011 census, 2012–2013. Canberra: Australian Bureau of Statistics.

    Google Scholar 

  • ABS. (2013a). The Australian Statistical Geography Standard (ASGS) 2011 structure and summary, Australian Bureau of Statistics. Canberra: Australian Bureau of Statistics.

    Google Scholar 

  • ABS. (2013b). Tourist accommodation, small area data, Australia, June 2013. Canberra: Australian Bureau of Statistics.

    Google Scholar 

  • Bell, M., & Brown, D. (2006). Who are the visitors? Characteristics of temporary movers in Australia. Population, Place and Space, 12(2), 77–92.

    Article  Google Scholar 

  • Bell, M., & Charles-Edwards, E. (2013). Cross-National comparisons of internal migration: An update on global patterns and trends (Technical Paper No. 2013/1). New York: United Nations Department of Economic and Social Affairs: Population Division.

    Google Scholar 

  • Bell, M., & Ward, G. (1998). Which population? Australian Planner, 35(1), 32–38.

    Article  Google Scholar 

  • Bell, M., & Ward, G. (2000). Comparing temporary mobility with permanent migration. Tourism Geographies, 2(1), 87–107.

    Article  Google Scholar 

  • Charles-Edwards, E., Bell, M., & Brown, D. (2008). Where people move and when: temporary population mobility in Australia. People and Place, 16(1), 21–30.

    Google Scholar 

  • Charles-Edwards, E. (2011). Modelling flux: Towards the estimation of small area temporary populations in Australia. PhD thesis, University of Queensland, Brisbane.

    Google Scholar 

  • Charles-Edwards, E., & Bell, M. (2013). Estimating the service population of a large metropolitan university campus. Applied Spatial Analysis and Policy, 6(3), 209–228.

    Article  Google Scholar 

  • Charles-Edwards, E., & Bell, M. (2015) Seasonal flux in Australia’s population geography: Linking space and time. Population, Space and Place, 21(2), 103–123.

    Google Scholar 

  • Choi, H., & Varian, H. (2009). Predicting the present with Google Trends. http://google.com/googleblogs/pdfs/google_predicting_the_present.pdf. Accessed 06 Mar 2015.

  • Deville, P., Linard, C., Martin, S., Gilbert, M., Stevens, F. R., Gaughan, A. E., Blondel, V. D., & Tatem, A. J. (2014). Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences, 111(45), 15888–15893.

    Article  Google Scholar 

  • Erny-Albrecht, K., Brown, L., Raven, M., & Bywood, P. (2014). Fly-in fly-out/drive-in drive-out practices and health service delivery in rural areas of Australia. Adelaide: Primary Health Care Research & Information Service.

    Google Scholar 

  • Frost, W. (2004). A hidden giant: Second homes and coastal tourism in south-eastern Australia. In C. Hall & D. Muller (Eds.), Tourism, mobility and second-homes: Between elite landscape and common ground (pp. 162–195). Clevedon: Channel View Publications.

    Google Scholar 

  • Hanson, J., & Bell, M. (2007). Harvest trails in Australia: Patterns of seasonal migration in the fruit and vegetable industry. Journal of Rural Studies, 23(1), 101–117.

    Article  Google Scholar 

  • Hugo, G., & Harris, K. (2013). Time and tide: Moving towards an understanding of temporal population changes in coastal Australia. Prepared for the National Sea Change Taskforce. Adelaide: The University of Adelaide.

    Google Scholar 

  • Hylleberg, S. (1992). Modelling seasonality. Oxford: Oxford University Press.

    Google Scholar 

  • Költringer, C., & Wöber, K. (2010). Information needs of city travellers. In J. Mazanec & K. Wöber (Eds.), Analysing international city tourism (pp. 109–126). Vienna: Springer.

    Chapter  Google Scholar 

  • Lee, S. (1999). An investigation to assess the feasibility of producing service population estimates for selected LGAs. Canberra: Australian Bureau of Statistics.

    Google Scholar 

  • Long, L. (1991). Residential mobility differences among developed countries. International Regional Science Review, 14(2), 133–147.

    Article  Google Scholar 

  • Markham, F., Bath, J., Taylor, J., & Doran, B. (2013). New directions in indigenous service population estimation (CAEPR Working Paper No. 88/2013). Canberra: Centre for Aboriginal Economic Policy Research.

    Google Scholar 

  • McKenzie, F. H. (2010). Fly-in fly-out: The challenges of transient populations in rural landscapes. In G. W. Luck, R. Black, & D. Race (Eds.), Demographic change in Australia’s rural landscapes (pp. 353–374). Dordrecht: Springer.

    Chapter  Google Scholar 

  • McKenzie, F., Martin, J., & Paris, C. (2008). Fiscal policy and mobility: The impact of multiple residences on the provision of place-based service funding. Australasian Journal of Regional Studies, 14(1), 53–71.

    Google Scholar 

  • McPherson, T., & Brown, M. (2004). Estimating daytime and nighttime population distributions in U.S. cities for emergency response activities. In Symposium on planning, nowcasting, and forecasting in the urban zone, 84th AMS annual meeting, Seattle.

    Google Scholar 

  • Melbourne City Research. (2013). City of Melbourne, daily population estimates and forecasts: A case for planning now for over one million people travelling to the city by 2030. Melbourne: City of Melbourne.

    Google Scholar 

  • Müller, D. (2002). German second homeowners in Sweden. Some remarks on the Tourism–Migration–Nexus. Revue européenne des migrations internationals, 18(1), 67–86.

    Article  Google Scholar 

  • O’Brien, J. W., et al. (2013). A model to estimate the population contributing to the wastewater using samples collected on census day. Environmental Science & Technology, 48(1), 517–525.

    Article  Google Scholar 

  • Paris, C., & Thredgold, C. (2014). Second homes and changing populations: Impacts and implications for local government in South Australia. Adelaide: Centre for Housing, Urban and Regional Planning (CHURP), University of Adelaide.

    Google Scholar 

  • PIFU. (2006). Full-time equivalent population estimates for nine Local Government Areas in the Bowen Basin. Brisbane: Planning Information and Forecasting Unit, Queensland Government.

    Google Scholar 

  • Reades, J., Calabrese, F., Sevtsuk, A., & Ratti, C. (2007). Cellular census: Explorations in urban data collection. IEEE Prevasive Computing, 6(3), 30–38.

    Article  Google Scholar 

  • Rees, P., & Wilson, A. (1977). Spatial population analysis. London: Edward Arnold (Publishers) Ltd.

    Google Scholar 

  • Reimondos, A., Evans, A., & Gray, E. (2011). Living-apart-together (LAT) relationships in Australia. Family Matters, 87, 43–55.

    Google Scholar 

  • Sevtsuk, A., & Ratti, C. (2010). Does urban mobility have a daily routine? Learning from the aggregate data of mobile networks. Journal of Urban Technology, 17(1), 41–60.

    Article  Google Scholar 

  • SGS. (2007). Impacts of coastal population fluctuations. Melbourne: Report prepared for Department of Sustainability and Environment, Victorian Government.

    Google Scholar 

  • Silm, S., & Ahas, R. (2010). The seasonal variation of population in Estonian municipalities. Environment and Planning A, 42(10), 2527–2546.

    Article  Google Scholar 

  • Smith, S. K. (1989). Toward a methodology for estimating temporary residents. Journal of the American Statistical Association, 84(406), 430–436.

    Article  Google Scholar 

  • Smith, E., & White, S. (2011). What Insights Can Google Trends Provide About Tourism in Specific Destinations? Paper presented at the Move 2011: 2nd international conference on the Measurement and Economic Analysis of Regional Tourism, Bilbao, Spain.

    Google Scholar 

  • State, B., Rodriguez, M., Helbing, D., & Zagheni, E. (2014). Migration of professionals to the U.S. In L. Aiello & D. McFarland (Eds.), Social informatics (Vol. 8851, pp. 531–543). Switzerland: Springer International Publishing.

    Google Scholar 

  • Statistics New Zealand. (2012). Using cellphone data to measure population movements. Wellington: Statistics New Zealand.

    Google Scholar 

  • Tatem, A. J. (2014). Mapping population and pathogen movements. International Health, 6(1), 5–11.

    Article  Google Scholar 

  • Taylor, J. (1998). Measuring short-term population mobility among indigenous Australians: Options and implications. Australian Geographer, 29(1), 125–137.

    Article  Google Scholar 

  • Taylor, J., & Bell, M. (2012). Towards comparative measures of circulation: Insights from Indigenous Australia. Population, Space and Place, 18(5), 567–578.

    Article  Google Scholar 

  • TRA. (2014). CD MOTA: Monitor of tourist activity. Canberra: Tourism Research Australia.

    Google Scholar 

  • United Nations. (2008). Principles and recommendations for population and housing censuses. New York: United Nations.

    Google Scholar 

  • Zagheni, E., Garimella, V. R. K., Weber I., & State, B. (2014). Inferring international and internal migration patterns from Twitter data. In Proceedings of the companion publication of the 23rd international conference on World wide web companion (pp. 439–444). International World Wide Web Conferences Steering Committee, Seoul, Republic of Korea.

    Google Scholar 

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Authors and Affiliations

  1. Queensland Centre for Population Research, School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, QLD, 4072, Australia

    Elin Charles-Edwards

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  1. Elin Charles-Edwards
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Correspondence to Elin Charles-Edwards .

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Editors and Affiliations

  1. Northern Institute, Charles Darwin University, Darwin, Northern Territory, Australia

    Tom Wilson

  2. Queensland Centre for Population Research, School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Queensland, Australia

    Elin Charles-Edwards

  3. Queensland Centre for Population Research, School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Queensland, Australia

    Martin Bell

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Charles-Edwards, E. (2016). The Estimation of Temporary Populations in Australia. In: Wilson, T., Charles-Edwards, E., Bell, M. (eds) Demography for Planning and Policy: Australian Case Studies. Applied Demography Series, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-22135-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-22135-9_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22134-2

  • Online ISBN: 978-3-319-22135-9

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