Multiscale Spatially and Temporally Varying Coefficient Modelling Using a Geographic and Temporal Gaussian Process GAM (GTGP-GAM) (Short Paper)

Authors Alexis Comber , Paul Harris , Chris Brunsdon

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Author Details

Alexis Comber
  • School of Geography, University of Leeds, UK
Paul Harris
  • Sustainable Agriculture Sciences, Rothamsted Research, Harpenden, UK
Chris Brunsdon
  • National Centre for Geomcomputation, National University of Ireland, Maynooth, Ireland

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Alexis Comber, Paul Harris, and Chris Brunsdon. Multiscale Spatially and Temporally Varying Coefficient Modelling Using a Geographic and Temporal Gaussian Process GAM (GTGP-GAM) (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 22:1-22:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


The paper develops a novel approach to spatially and temporally varying coefficient (STVC) modelling, using Generalised Additive Models (GAMs) with Gaussian Process (GP) splines parameterised with location and time variables - a Geographic and Temporal Gaussian Process GAM (GTGP-GAM). This was applied to a Mongolian livestock case study and different forms of GTGP splines were evaluated in which space and time were combined or treated separately. A single 3-D spline with rescaled temporal and spatial attributes resulted in the best model under an assumption that for spatial and temporal processes interact a case studies with a sufficiently large spatial extent is needed. A fully tuned model was then created and the spline smoothing parameters were shown to indicate the degree of variation in covariate spatio-temporal interactions with the target variable.

Subject Classification

ACM Subject Classification
  • Information systems → Spatial-temporal systems
  • Spatial Analysis
  • Spatiotemproal Analysis


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  1. Alexis Comber, Paul Harris, and Chris Brunsdon. Multiscale spatially varying coefficient modelling using a geographical gaussian process gam. International Journal of Geographical Information Science, submitted. Google Scholar
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