ENLIGHT Courses

Remote Sensing Image Processing with Open Source Software

Students will acquire theoretical knowledge and practical competencies in fundamental principles, techniques, and applications of remote sensing. They will gain hands-on experience in digital image processing, analysis, and information extraction using the open-source GIS software QGIS installed on their own laptops. Additionally, students will develop skills in automating remote sensing workflows through Python scripting within the Copernicus cloud processing environment.

About the course

Content

The course introduces the theory of remote sensing image processing and applications of remote sensing workflows implemented in Python. Remote sensing data mainly from the satellite sensor Sentinel-2 and Sentinel-1 are used to develop analysis workflows for forestry and environmental monitoring applications. Common steps and methods of remote sensing analysis such as preprocessing, image enhancement, sampling of reference data, automated classification, change detection and map validation are presented. In the practical labs students learn how to use Python for cloud-based remote sensing.

Learning outcomes

Upon completion of this course, students will be able to:

  • Explain the fundamental principles of electromagnetic radiation and describe its interactions with the atmosphere.
  • Demonstrate proficiency in basic techniques related to remote sensing image acquisition, pre-processing, enhancement, and classification.
  • Gain a basic understanding of the QGIS software environment.
  • Understand, manipulate and execute Python scripts to automate and support remote sensing data processing workflows.
  • Evaluate and interpret the quality of remote sensing products by performing accuracy assessments and validation analyses.

Teaching format

Synchronous online lecture with practical group work

Assessment

Form of assessment:  E-Exam of 90 min duration

Timing for assessment: probably at the end of February

Calculation of the examination mark: The course will be passed with 50% of the total points.

Lecturers

Dr. Nils Nölke

Course dates

Academic Year: winter term 2025/26

Course schedule: The course takes place every week on Tuesday from 14:15h to 16:00h and Wednesday from 8:15h to 10:00h during the lecture period from October 27, 2025 until February 13, 2026 with a break from December 22, 2025 to January 2, 2026.

  • Type: virtual course
  • Level: Master
  • Host: University of Göttingen
  • Study Field: Science and Technology
  • Course dates: 27 Oct 2025 - 13 Feb 2026
  • Apply by: 17 October 2025
  • ECTS: 6
  • Registration status: Open
  • Number of places available: 10 in total