Assessing the accuracy of kernel smoothing population surface models for Northern Ireland using geographically weighted regression

Behnam Firoozi Nejad*, Christopher Lloyd

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

This paper makes use of two sets of Census outputs for Northern Ireland – counts by (i) output areas (OAs) and (ii) 100 m grid cells. Population surfaces are derived from OAs using a kernel smoothing approach and the accuracy of these surfaces is assessed using the 100-m grid square product. The key contribution of this paper is in pulling together the benefits of a gridded population data source with local regression procedures to provide a more detailed assessment of surface modelling accuracy than possible in any previous studies.

Original languageEnglish
Number of pages19
JournalJournal of Spatial Science
Early online date02 Apr 2018
DOIs
Publication statusEarly online date - 02 Apr 2018

Keywords

  • census
  • geographically weighted regression (GWR)
  • ordinary least squares (OLS)
  • Population surface modelling
  • spatial variation

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Energy(all)
  • Atmospheric Science

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