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Dasymetric Modelling of Population Distribution – Large Data Approach

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  • Dmowska Anna

    (Department of Geoinformation, Institute of Geoecology and Geoinformation, Adam Mickiewicz University in Poznań, Poland)

Abstract

Existing resources of population data, provided by national censuses in the form of areal aggregates, have usually insufficient resolution for many practical applications. Dasymetric modelling has been a standard technique to disaggregate census aggregates into finer grids. Although dasymetric modelling of population distribution is well-established, most literature focuses on proposing new variants of the technique, while only few are devoted to developing broad-scale population grids that could be used for real-life applications. This paper reviews literature on construction of broad-scale population grids using dasymetric modelling. It also describes an R implementation of fully automated framework to calculate such grids from aggregated data provided by national censuses. The presented implementation has been used to produce high resolution, multi-year comparable, U.S.-wide population datasets that are the part of the SocScape (Social Landscape) project.

Suggested Citation

  • Dmowska Anna, 2019. "Dasymetric Modelling of Population Distribution – Large Data Approach," Quaestiones Geographicae, Sciendo, vol. 38(1), pages 15-27, March.
    • Handle: RePEc:vrs:quageo:v:38:y:2019:i:1:p:15-27:n:8
    DOI: 10.2478/quageo-2019-0008
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    References listed on IDEAS

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    1. Andrea E Gaughan & Forrest R Stevens & Catherine Linard & Peng Jia & Andrew J Tatem, 2013. "High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    2. M F Goodchild & L Anselin & U Deichmann, 1993. "A Framework for the Areal Interpolation of Socioeconomic Data," Environment and Planning A, , vol. 25(3), pages 383-397, March.
    3. Filipe Batista e Silva & Javier Gallego & Carlo Lavalle, 2013. "A high-resolution population grid map for Europe," Journal of Maps, Taylor & Francis Journals, vol. 9(1), pages 16-28, March.
    4. Flowerdew, Robin & Green, Mick, 1992. "Developments in Areal Interpolation Methods and GIS," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 67-78, April.
    5. Andrew J Tatem & Abdisalan M Noor & Craig von Hagen & Antonio Di Gregorio & Simon I Hay, 2007. "High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa," PLOS ONE, Public Library of Science, vol. 2(12), pages 1-8, December.
    6. Michael Reibel & Michael E Bufalino, 2005. "Street-Weighted Interpolation Techniques for Demographic Count Estimation in Incompatible Zone Systems," Environment and Planning A, , vol. 37(1), pages 127-139, January.
    7. Philip Berke & Galen Newman & Jaekyung Lee & Tabitha Combs & Carl Kolosna & David Salvesen, 2015. "Evaluation of Networks of Plans and Vulnerability to Hazards and Climate Change: A Resilience Scorecard," Journal of the American Planning Association, Taylor & Francis Journals, vol. 81(4), pages 287-302, October.
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