Spatio-temporal interpolation using gstat

Edzer Pebesma, Gerard Heuvelink

Research output: Contribution to journalArticleAcademicpeer-review

399 Citations (Scopus)


We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. In a real-world application we compare spatiotemporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the extension of gstat facilitates and eases spatio-temporal geostatistical modelling and prediction for R users

Original languageEnglish
Pages (from-to)204-218
JournalR Journal
Issue number1
Publication statusPublished - 2016


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