Remote Sensing of the Bio-Geosphere (Part 2)

Course content

This competence-line course teaches state-of the art research of advanced Earth Observation (EO) based methods for global change studies of the bio-geosphere. Software based analysis tools will be tested and learned in a number of practical PC-based hands-on exercises and a research project will be conducted by the students. The overall aim is to provide an understanding of relevant theories and methodologies for advanced global change studies of the bio-geosphere based on various state-of-the-art remote sensing systems. Approaches for advanced multi-year analysis of changes in space and time (linear change and/or abrupt change methods, changes in seasonality) with particular relevance for assessing the impact from climate change and anthropogenic influence will be presented and discussed during classes. Time series parameterisation (including TIMESAT for extracting seasonal parameters, BFAST (Breaks For Additive Season and Trend), PCA (Principal Component Analysis) and advanced image classification algorithms will be tested and applied by the students to solve a selected research problem and presented through a research project conducted during the course.


MSc Programme in Geography and Geoinformatics
MSc Programme in Geography and Geoinformatics with a Minor Subject
MSc Programme in Agriculture

Learning outcome


  • Advanced Earth Observation based time series analysis
  • Remote Sensing based changes in the bio-geosphere
  • Advanced geoinformatics
  • Independent project work



  • Find and understand relevant scientific literature related to research project conducted.
  • Identification, downloading and pre-processing of appropriate remote sensing data for use in research project.
  • Apply correct remote sensing data, methods and analysis for research project conducted.
  • Use appropriate software for time series parameterisation.
  • Apply remote sensing time series PCA (Principal Component Analysis) in ecosystem analysis.
  • Describe recent development in image classification algorithms



  • Understand and evaluate applicability of relevant remote sensing data for ecosystem change assessment in space and time.
  • Compare and evaluate the usability of various Earth Observation time series analysis tools for solving complex climate change and anthropogenic influence on ecosystem change.
  • Conduct an independent research project including the integration of appropriate literature, data collection, methods and analysis.
  • Present and discuss (oral and written assignments) the appropriate use of theory and methods for a successful remote sensing based research project outcome.

The form of teaching is theory exercises combined with ad hoc lectures. For the teaching plan, please see Absalon.

Please see Absalon course page.

BSc in Geography and Geoinformatics or equivalent. In order to participate, students must have knowledge corresponding to that obtained in part 1 of the course.

7,5 ECTS
Type of assessment
Written assignment
Oral examination, 20 minutes
The written assignment is prepared during the course and must be handed in prior to the exam week. The oral exam uses the written assignment as its point of departure. It includes the titles listed in the officially approved reading list. A combined grade is given after the oral exam.
All aids allowed
Marking scale
7-point grading scale
Censorship form
External censorship
Criteria for exam assessment

Please see learning outcomes.

Single subject courses (day)

  • Category
  • Hours
  • Theory exercises
  • 35
  • Project work
  • 35
  • Preparation
  • 136
  • English
  • 206