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701-0104-00L 3 Credits BSC , MSC D-USYS , D-ERDW
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Statistical Modelling of Spatial Data

Statistische Modellierung von räumlichen Daten

Lecturers & Examiners: Dr. Andreas Jürg Papritz
VVZ CR n/a

Last Updated: 2026-02-05 15:29:07

Abstract

In environmental sciences one often deals with spatial data. When analysing such data the focus is either on exploring their structure (dependence on explanatory variables, autocorrelation) and/or on spatial prediction. The course provides an introduction to geostatistical methods that are useful for such purposes.

Objective

The course will provide an overview of the basic concepts and stochastic models that are commonly used to model spatial data. In addition, the participants will learn a number of geostatistical techniques and acquire some familiarity with software that is useful for analysing spatial data.

Content

After an introductory discussion of the types of problems and the kind of data that arise in environmental research, an introduction into linear geostatistics (models: stationary and intrinsic random processes, modelling large-scale spatial patterns by regression, modelling autocorrelation by variogram; kriging: mean-square prediction of spatial data) will be taught. The lectures will be complemented by data analyses that the participants have to do themselves.

Resources

Lecture Notes

Lecture notes, descriptions of the problems for the data analyses and work-out solutions to them will be provided. The course material is available fromhttp://elbanet.ethz.ch/wikifarm/spatstat/.

Literature

Cressie, N.A.C. 1993. Statistics for Spatial Data. Wiley.

General Information

Language
German
Levels
BSC , MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
oral 30 minutes

Course Components

Type Title Time & Place Hours
lecture with exercise Statistische Modellierung von räumlichen Daten
  • Wed 08:15-10:00 (CHN G 42)
  • 23.04 Date 13:15-15:00 (ML H 37.1)
  • 30.04 Date 13:15-15:00 (CAB G 52)
2 h weekly

Offered In