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High-resolution satellite and drone-based remote sensing in Environmental Sciences (2018)

ECTS credits:

Course parameters:
Language: English
Level of course: PhD course
Time of year: 12-16 November 2018
No. of contact hours/hours in total incl. preparation, assignments or the like: 40/80
Capacity limits: 15 participants

Objectives of the course:
The objective of the course is to give the participants the tools and insight needed to get started with using high resolution remote sensing data to answer questions of relevance for environmental sciences. Specifically, the course will introduce the students to:

  1. Image processing in the ENVI software
  2. Pixel-based classification methods in ENVI
  3. Image segmentation and object-based classification approaches in the eCognition software
  4. Change detection techniques
  5. Unmanned aerial image processing and data handling methods, and
  6. Data download and handling in Google Earth Engine. The course will alternate between lectures, where the students are introduced to the different methods, and exercises, where the students will apply the methods to various image data sets.

Learning outcomes and competences:
At the end of the course, the students should be able to:

  • Understand the basic principles of remote sensing and its applications in environmental science.
  • Explain how fundamental image processing operations work for extracting thematic and biophysical information from remotely sensed data.
  • Be able to locate, download and order commercially available remote sensing data sets and understand their strengths and weaknesses.
  • Start conducting advanced pixel-based and object-based analyses.
  • Plan and execute a remote sensing project, including appropriate image data acquisition, pre-processing and data integration, data analysis, integration of field and image data, error assessment, and general reporting requirements.

Compulsory programme:
Preparation and active participation

Course contents:
Lectures and computer exercises. Students need to bring their own computers.


Name of lecturers:

  • Gary Richard Watmough (Aarhus University)
  • Urs Treier (Aarhus University)
  • Signe Normand (Aarhus University)

Information on obligatory material to be read before the course will be send out at the latest 14 days before the course start.

Course homepage:

Course assessment:
Active participation

Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University

Course organiser: Signe Normand

9 am – 5 pm each day

Building 1540, room 324, Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Ny Munkegade 114, 8000 Aarhus C.

Deadline for registration is 20 October 2018.
PhD students from Science and Technology at Aarhus University have preference.
If you have any questions, please contact Urs Treier e-mail: urs.treier@bios.au.dk.

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