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Population and age structure in Hungary: a residential preference and age dependency approach to disaggregate census data

  • Sen Li*
  • , Linda Juhász-Horváth
  • , Paula A. Harrison
  • , László Pintér
  • , Mark D.A. Rounsevell
  • *Corresponding author for this work
  • University of Oxford
  • Central European University
  • Centre for Ecology and Hydrology
  • International Institute for Sustainable Development (IISD)
  • University of Edinburgh

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

We present a simple model to disaggregate age structured population census data to a 1-km grid for Hungary. A dasymetric approach was used to predict the spatial distribution of population in different age groups by distinguishing residential preferences (in relation to accessible social, economic and green amenities) for working age groups (15–29, 30–49 and 50–64) and population dependencies for children and the elderly (aged 0–14 and 65+). By using open-access land cover data and fine-level population census data as inputs, the model predicts the likely spatial distribution of population and age structure for Hungary in 2011. The resulting map and gridded data provide information to support spatial planning of residential development and urban infrastructure. The model is less data-demanding than most existing approaches, but provides greater power for describing population patterns. It can also be used to create scenarios of future demographic change.

Original languageEnglish
Pages (from-to)560-569
Number of pages10
JournalJournal of Maps
Volume12
DOIs
StatePublished - 4 Nov 2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Age structure
  • dasymetric mapping
  • land cover
  • population dependency
  • population distribution
  • residential preference

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