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Statistical Modelling of Spatial Data
Statistische Modellierung von räumlichen Daten
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 |
|
2 h weekly |
Offered In
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Major in Climate and Water: Electives (Advisor of the BSc-major "Climate and Water" is Dr. M. Wüest, Institute for climate and atmosphere (IAC).)
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Major Electives (From the elective courses of the 5th and 6th semester, 24 credits have to be acquired. Other courses have to be granted by the advisor, Dr. M. Wüest, IAC.)
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