teach_2024_msc_envscience_remote_sensing_and_geoinformatics

Teaching material for the MSc Module "Remote Sensing and Geoinformatics"

News

• For the 12.04.2024 the plan is to work on the chapter 04_earth_observation_products_automl.ipynb and the corresponding assignemnts.
• For the 11.04.2024 the meeting for the joint drone campaign is given here: https://www.google.com/maps/d/u/0/viewer?mid=1Ah2MfKngwOZFqpjER-AID_RQrqEj5aw

Small list of advices or this course:

• dare to ask many questions
• dare to give feedback
  • in the course, to teja.kattenborn@geosense.uni-freiburg or also here in Github unter "Issues" or "Disscussions)
  • For instance, feedback on improvements for the course, errors in the code, analysis of interest, etc.
• Be patient with yourself (expect both flat and steep learning curves)
• Help eachother :-)

Access to the data

• All data can be found here.
• In total the data amounts to 18 GB. Let me know if you do not have sufficient storage ressources for the duration of the course.

Where to perform the analysis?

• Your own computer
• CIP-Pool computers
• Google Colab: https://colab.research.google.com/
• Colab-JuPyteR shortcuts: https://colab.research.google.com/drive/13IO3-gfyS9mSPuzAo6-wsYBUOVpxb_va?usp=sharing

install packages

• pip install rioxarray (in colab)
• alternatives conda or mamba (conda install -c conda-forge)
• list of packages that should be installed for the course: rioxarray rioxarray matplotlib numpy xarray glob2 pandas geopandas rasterstats rasterio