Exploring the spatio-temporal dynamics of geographical processes with geographically weighted regression and geovisual analytics

Urska Demsar, A. Stewart Fotheringham, Martin Charlton

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

The paper examines the potential for combining a spatial statistical methodology - Geographically Weighted Regression (GWR) - with geovisual analytical exploration to help understand complex spatio-temporal processes. This is done by applying the combined statistical - exploratory methodology to a simulated data set in which the behaviour of regression parameters was controlled across space and time. A variety of complex spatio-temporal processes was captured through space-time (i.e. as spatio-temporal) varying parameters whose values were known. The task was to see if the proposed methodology could uncover these complex processes from the data alone. The results of the experiment confirm that the combined methodology can successfully identify spatio-temporal patterns in the local GWR parameter estimates that correspond to the controlled behaviour of the original parameters. Information Visualization (2008) 7, 181-197. doi: 10.1057/palgrave.ivs.9500187

Original languageEnglish
Pages (from-to)181-197
Number of pages17
JournalInformation Visualization
Volume7
Issue number3-4
DOIs
Publication statusPublished - 2008

Fingerprint

Dive into the research topics of 'Exploring the spatio-temporal dynamics of geographical processes with geographically weighted regression and geovisual analytics'. Together they form a unique fingerprint.

Cite this