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Software iconList of FOSS software used in this course and installation instructions. Follow these instructions to prepare and customize the software before the beginning of the course.

Literature used

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

Events

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Graeler: Spatio-temporal geostatistics: choosing and fitting models, interpolation

Date & Time: Thursday 19 June 09.00-17.00

Objective: to gain insights in spatio-temporal interpolation methods and their application in gstat.

General descriptionModelling spatio-temporal phenomena is a key issue in today's research. However, the extension from pure spatial to a spatio-temporal kriging 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, ...). The practical part deals with the exploration of empirical variograms and the different variogram models applied to an own data set or a provided example.

Suggested back-ground knowledge: spatial kriging, spacetime classes in R
Software / R packages required: R packages: spacetime, gstat

09:00 - 10:30: Spatial and Spatio-Temporal Kriging: slides

11:00 - 12:00: Copulas in Spatial Statistics: slides

12:00 - 12:30: Hands-on Spatial Kriging with gstat: script

13:30 - 15:00: Hands-on Spatio-Temporal kriging with gstat: script

15:30 - 17:00: work on interpolation challenge & copulas: script

Literature:

  • Gräler, B., L. Gerharz and E. Pebesma (2012): Spatio-temporal analysis and interpolation of PM10 measurements in Europe. 
    ETC/ACM Technical Paper 2011/10, January 2012.

  • Pebesma, E. and B. Gräler (2014): Spatio-temporal geostatistics using gstat. gstat vignette, April 2014.

Location

NHH
workshop B
Bergen
Norway
AttachmentSize
part01.pdf2.23 MB
part02.pdf1.8 MB
fields_clean.R1.8 KB
space-time_clean.R5.09 KB
copulas_clean.R1.39 KB
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