Single-Course English 5 ECTS

Analysis of spatial and temporal data within geoscience

Overall Course Objectives

The course aims to give the student insight into and practical experience with methods to analyze and process spatial and temporal data. The methodologies are applied to data sets within the fields of mapping, navigation, and earth observations.

This course has a strong practical aspect. The students are presented with the methodologies providing the foundation for their own implementation (in R) and real data analysis.

Learning Objectives

  • list and describe commonly used covariance models
  • describe the principle of maximum likelihood estimation
  • explain the concept in a state-space model
  • apply well known processes in modeling such as a random walk and an autoregressive model
  • implement different algorithms for spatial modeling such as kriging and Gaussian Markov random fields
  • compare and evaluate models
  • discuss and defend choice of model
  • design a spatial or temporal model to analyse real data
  • document and present scientific work.

Course Content

Spatial and temporal data are an integrated part of earth science. The content of this course will introduce some general tools to handle such data.
Some specific topics are:
• Maximum likelihood estimation
• Covariance functions
• Gaussian Markov random field
• State-space model
• Kriging
• Model evaluation

Recommended prerequisites

30201/30202/30230, Knowledge of programming

Teaching Method

Lectures, exercises, project work in groups.


See course in the course database.





3 weeks




DTU Lyngby Campus

Course code 30545
Course type Candidate
Semester start Week 1
Semester end Week 35
Days Mon-fri 8:00-17:00

7.500,00 DKK