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

Comber, Alexis; Harris, Paul; Brunsdon, Chris

doi:10.4230/LIPIcs.GIScience.2023.22

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Document Identifiers

DOI: 10.4230/LIPIcs.GIScience.2023.22
URN: urn:nbn:de:0030-drops-189173

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

Cite AsGet BibTex

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)
https://doi.org/10.4230/LIPIcs.GIScience.2023.22

Abstract

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

Keywords

Spatial Analysis
Spatiotemproal Analysis

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References

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.
Ludwig Fahrmeir, Thomas Kneib, Stefan Lang, and Brian D Marx. Regression models. In Regression, pages 23-84. Springer, 2021.
John McPeak. Confronting the risk of asset loss: What role do livestock transfers in northern kenya play? Journal of Development Economics, 81(2):415-437, 2006.
Stan Openshaw. Developing gis-relevant zone-based spatial analysis methods. Spatial analysis: modelling in a GIS environment, pages 55-73, 1996.
Narumasa Tsutsumida, Paul Harris, and Alexis Comber. The application of a geographically weighted principal component analysis for exploring twenty-three years of goat population change across mongolia. Annals of the American Association of Geographers, 107(5):1060-1074, 2017.
Simon N Wood. Generalized additive models: an introduction with R. Chapman Hall/CRC, 2006.