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Forecasting Patterns of Metropolitan Growth Using an Optimised Allocation Procedure

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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

Planning for the provision of infrastructure and services to accommodate urban growth calls for detailed forecasts of the scale and distribution of housing and population up to 30 years ahead. While a wide range of forecasting methodologies are is use, integrated urban models that link housing demand to land availability and planning constraints by simulating real world processes offer the greatest potential for policy analysis and scenario development. Their major drawbacks lie in extensive data requirements and the specification of realistic modelling parameters. This paper describes a Large Scale Urban Model (LSUM) model developed to predict disaggregate patterns of housing development and population in the rapidly growing region of Southeast Queensland. The LSUM model uses a combination of statistical and dynamic rules to model patterns of housing development across a multi-resolution spatial grid, with aggregate projections constrained to exogenous regional forecasts developed from a suite of demographic models. We outline the main structure of the model, examine key issues in its development, provide illustrative results and explain how it can be employed to explore policy options.

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Acknowledgments

This chapter is based on research funded by Australian Research Council Linkage grant. LP0453563 with additional support from the industry partner, the Office of Economic and Statistical research in the Queensland Treasury. The views expressed in the paper do not necessarily reflect Queensland government policy.

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Correspondence to David Pullar .

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Pullar, D., Bell, M., Cooper, J., Stimson, R., Corcoran, J. (2016). Forecasting Patterns of Metropolitan Growth Using an Optimised Allocation Procedure. 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_7

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  • DOI: https://doi.org/10.1007/978-3-319-22135-9_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22134-2

  • Online ISBN: 978-3-319-22135-9

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