• Tedstone Andrew

• Machguth Horst
• Pohl Eric
• Tedstone Andrew

The course focuses on processing, analyzing and applying of environmental data, with a focus on mountainous regions. Dedicated scientific tools and methods are introduced and hands-on exercises allow for in-depth training. The students will apply the skills they have learned by conducting their own small project. They will share their findings first via a presentation and initial discussion of their results within the class, and second through a written scientific report.

Most of the data used in this course are relevant with regard to climate change. This course places special emphasis on the possibilities and limitations of the data and methods in view of societal relevant aspects like climate change adaptation and risks.

The students will work with different types of climate data and will receive practical training on different environmental data formats and analysis tools. They will extract information from remote sensing data and use them for further calculations (e.g. glacier volume) in a GIS. The combination of climate and remotely sensed data will enable integrated climate change impacts assessments.

Intended Learning Outcomes

• Have a comprehensive understanding of research design in a range of contexts associated with environmental science
• have the ability to analyse and evaluate the utility of different types of data, how it is collected and analysed in order to make sound judgements about the quality of the research
• have the ability to make hypotheses relevant to environmental problems and research
• have communication skills in exploring, interpreting, and presenting data graphically
• have the ability to interpret and communicate findings from environmental research clearly and coherently.

You should have some basic familiarity with using script/code approaches to analyse quantitative data, preferably Python. If you have never used computer scripting languages then please consider following “Data Analytics in Python”, either online or in-presence, before the block course:

https://www.unifr.ch/digitalskills/fr/student/index.html

We will recap on the essential aspects of interpreting multispectral satellite imagery at the start of the course, but we will assume a basic level of understanding of geographical information systems.

- - - - Requirement for students from other Swiss universities - - - -

The participation to the course and the registration for the exam are conditional to the enrollment as BENEFRI or guest students. At the beginning of the semester at latest :

- Students from the universities of Bern and Neuchâtel (BENEFRI) are invited to follow the steps of the procedure described on https://www3.unifr.ch/studies/fr/admission/admission-etudiant-hote/programme-benefri.html in order to be identified as BENEFRI students.

- Students from other Swiss universities are invited to follow the procedure described on https://www3.unifr.ch/studies/fr/admission/admission-etudiant-hote/hote-complementaire.html in order to be enrolled as guest students.

Below is some information concerning the registration to exams. Please be aware that registration to exams is mandatory and does not automatically happen if you are registered to a class:

https://www3.unifr.ch/scimed/en/studies/register.