Introduction to Geostatistics
Einführung in die Geostatistik
6 CPWinterENno longer offered
Prerequisites
Recommended, as written
Basic knowledge of R programming is essential.
Contents
Handling spatial data in R, visualizing spatial data, sampling and estimation, variogram analysis, spatial predictions and interpolations (e.g. Kriging methods), geostatistical simulation and introduction to machine learning.
Learning outcomes
This module provides an introduction to the theory and practice of statistics used in the analysis of data arising in the earth and environmental sciences. At the end of this module students have a good knowledge of basic theory of geostatistics and are able to implement spatial data analysis using R.
Assessment
• Homework (5 semester exercises) - each with 10 % weight • Written examination (60 minutes) - 50 % weight
Literature (2)
- Bivand, R. S., Pebesma, E., Gómez-Rubio, V., 2013, Applied Spatial Data Analysis with R (Second Edition), Springer New York Heidelberg Dordrecht London.
- Webster, R, Oliver, M. A., 2007, Geostatistics for Environmental Scientists (Second Edition), John Wiley & Sons.
Remarks
Complementary module for study programme Master Environmental and Resource Management.
Source: BTU's module description · retrieved 17 Oct 2026Original