+ search

Spatial Statistics

Degree type
Language of education
English (100%)
6 weeks
Tuition fee EU/EEA
Please enquire
Tuition fee Non EU/EEA
Please enquire
Education type
Start of program
Please enquire
Application deadline
Please enquire
Type of institution
Research University

Program description

This course aims to provide you with an introduction to theory and practice of Geostatistics and is designed to give you a head start on the analysis they will need to do their research.

This course aims to provide you with an introduction to the theory and practice of Geostatistics. By the end of the course you should have a good knowledge of basic theory AND be able to implement analysis Geostatistics is statistical inference for data with known locations.

The attention to location is what differentiates the statistics that you study in this module from the classical statistics that you studied previously. Location is fundamental to geodata, so geostatistics find wide application in the different disciplines at ITC.

Geostatistical analysis will be implemented mainly in the R software. Where appropriate, we will also link to GIS software. In contrast with previous years, greater emphasis will be placed on remote sensing, although field data will still be considered.

This course is designed to give you a head start on the analysis they will need to do their research, by learning the principles of data analysis as well as specific techniques according to their research topics.

To develop a strong knowledge of fundemental theory for spatial statistics (geostaistics, point statistics, lattice analysis)... AND be able to implement this for various types of geodata and applications using appropriate software.

Calculate sample variograms and fit models to those sample variograms AND justify choices made during this process; Implement ordinary kriging and interpret the results (mean and kriging variance); Extend the ordinary kriging case to regression kriging through the use of appropriate covariates; Explain the concept of co-kriging and implement it for a simple example; Explain the concept of probability mapping and implement indicator kriging; Design an optimal sampling scheme; Develop and present a thorough analysis of a dataset. Students should be prepared to properly analyze their field or lab data and to design a sound sampling scheme. They will be able to use the R environment for statistical computing at a basic to intermediate level. Instruction modes Lectures, supervised practicals, unsupervised practicals, group assignments, individual assignments, self-study.

Regionalized variable theory; classical & model-based geostaistics; CAR and SAR modelling; point pattern analysis; lattice analysis; Bayesian networks; sampling; software implementation using R & GIS.

First module: We then model autocorrelation using variograms and covariance functions and then apply the variogram for prediction using ordinary kriging. We conclude with a mapping exercise. More advanced topics are regression kriging, universal kriging, co-kriging, sampling and simulation. We also look at probability maps.

The third week is an extended case study, where you conduct geostatistical analysis on a dataset of your choice. Statistical inference for research; A data analysis strategy; The R environment for statistical computing; Review of descriptive statistics and exploratory data analysis; Linear modelling and extensions; Selecting appropriate analytical methods; learning techniques from literature; Basic sampling theory.

Students choose a guided self-study in techniques, including: Geostatistics, modelling spatial structure, mapping by interpolation; Multivariate modeling including factor analysis, Logistic regression; Weights-of-evidence; Time-series analysis; Fragmentation statistics, pattern analysis; Non-linear modelling, curve fitting.

About the University of Twente

The University of Twente focuses on the development of technology and its impact on people and society. It offers bachelor, master and postgraduate programs in the field of Technology, Behavioral and Social Sciences. University of Twente students are always encouraged to look beyond the boundaries of their own field and establish links with other disciplines.

High tech, human touch. This is what characterizes the University of Twente. Some 3,300 scientists and other professionals working together on cutting-edge research, innovations with real-world relevance and inspiring education for more than 9,000 students. The enterprising university encourages students to develop an entrepreneurial spirit and is a partner of Knowledge Park Twente.

More information about the University of Twente

Admission requirements

Previous education

Modules 1-11 of the ITC MSc programme. Where this has not been followed we will assess the suitability of candidates on an individual basis.

University level basic statistics course; familiarity with spatial data

Professional experience

A few years of professional experiences is recommended.

Language test

IELTS overall band 6.0
TOEFL computer based 213
TOEFL internet based 80
TOEFL paper based 550
Cambridge Advanced English C1
Cambridge Professional English C2


Share your thoughts on
studying abroad.

Join the study in the Netherlands facebook community!


Share your thoughts on
studying abroad.

Join the study in the Netherlands facebook community!

We use non-commercial cookies only. More information. Close this message.×