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 language | English |
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Number of pages | 7 |
Publication status | Published - 14 Sept 2010 |
Externally published | Yes |
Event | GIScience 2010: Sixth international conference on Geographic Information Science - University of Zurich, Zurich, Switzerland Duration: 14 Sept 2010 → 17 Sept 2010 |
Conference
Conference | GIScience 2010: Sixth international conference on Geographic Information Science |
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Country/Territory | Switzerland |
City | Zurich |
Period | 14/09/10 → 17/09/10 |
Keywords
- spatio-temporal
- population modelling
- open data
- gridded population
- KML
- GoogleEarth
- visualisation