Remote sensing data analysis in R-Studio - short course dates

Posted on May 31, 2022

The department of Geography, Geoinformatics and Meteorology will offer a Remote sensing data analysis in R-Studio: A machine learning perspective from 8-10 November 2022. This course will be led by Dr. Philemon Tsele and is targeting those working with big data within the remote sensing industry and how certain advanced algorithms such as artificial intelligence and machine learning are used within this context. This remote sensing data analysis course covers the physical principles of satellite remote sensing and remote sensor data processing using machine learning methods

Once you have completed the course, you will: 

  • Know how to set up and use R-studio for satellite image data processing and analysis i.e., do basic programming
  • Carry out satellite image pre-processing (including atmospheric correction) in R-studio and assess image quality using image statistics in R-studio
  • Carry out supervised classification using different machine learning algorithms on a series of raster layers and to do validation of the classification results
  • Carry out linear and linear non-parametric methods to make estimations and/or predictions of terrestrial biophysical variables like the Leaf area index (LAI), Chlorophyll, and Fractional Vegetation Cover.
  • Carry out statistical analysis of error for various modeling scenarios

For more information please visit

- Author Department of Geography, Geoinformatics and Meteorology
Published by Christel Hansen

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