Linking UK public geospatial data to build 24/7 space-time specific population surface models

Samuel Leung, David Martin, Samantha Cockings

Research output: Contribution to conferencePaperpeer-review

Abstract

Until recently any attempt to model population distribution over space has been largely dependent on georeferencing of resident population and therefore presents an abstract representation of night-time population pattern. There are however, good arguments for modelling population at different times, incorporating population movements from seasonal to diurnal timescales so as to predict, for example, vulnerable population for rapid disaster relief or potential customer numbers during a working day. This paper presents early results from a publicly-funded project to develop space-time specific population surface models of the UK. The project extends Martin’s adaptive kernel density approach into a spatio-temporal kernel density estimation for building gridded surface population models. We begin by briefly reviewing relevant methods, then move on to our conceptual modelling and data linkage and conclude with some early illustrative results.
Original languageEnglish
Number of pages7
Publication statusPublished - 14 Sep 2010
Externally publishedYes
EventGIScience 2010: Sixth international conference on Geographic Information Science - University of Zurich, Zurich, Switzerland
Duration: 14 Sep 201017 Sep 2010

Conference

ConferenceGIScience 2010: Sixth international conference on Geographic Information Science
Country/TerritorySwitzerland
CityZurich
Period14/09/1017/09/10

Keywords

  • spatio-temporal
  • population modelling
  • open data
  • gridded population
  • KML
  • GoogleEarth
  • visualisation

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