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ASDAR bookList of books / lecture notes used in this course. See also: CRAN Task View: Analysis of Spatial Data.

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Spatio-Temporal Geostatistics

LocationIfGI CIP pool

Objective: to gain insight in a set of spatio-temporal interpolation methods
General description: Modelling spatio-temporal phenomena is a key issue in today's research. However, the extension from pure spatial to a spatio-temporal approach is not trivial. We will look into a set of different perceptions of saptio-temporal dependence and the resulting covariance models (separable, product-sum, metric, asymmetric, ...).
Required back-ground knowledge: Students should be familiar with the basic concepts of kriging.
R packages required: spacetime, gstat, (outlook: spcopula);
Reading material: Gräler, B., L. E. Gerharz, & E. Pebesma (2012): Spatio-temporal analysis and interpolation of PM10 measurements in Europe. ETC/ACM Technical Paper 2011/10, January 2012

 

The morning session is now available at: http://archive.org/details/GeostatSpatio-temporalGeostatistics..

 

 9:00–10:30 Introduction to different concepts of spatio-temporal dependence separable, product-sum and metric covariance models in theory and gstat.

10:30–11:00 Coffee break 

11:00–12:30 Copulas in geostatistics.

12:30–14:00 Lunch break 

14:00–15:30 Exercise 1: fit and model a separable covariance model to some spatio-temporal phenomenon (redoing the examples from the slides)

15:30–16:00 Coffee break

16:00–17:30 Exercise 2: fit and model a product-sum/metric covariance model to some spatio-temporal phenomenon (redoing the examples from the slides)

AttachmentSize
part01.pdf411.11 KB
part02.pdf4.05 MB
notes.R1.01 KB
Graeler-Modelling_Dependence_in_Space_and_Time.pdf742.02 KB
ex_spatio-temporal.zip147.43 KB
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