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103-0287-00L 6 Credits MSC D-BAUG , D-MAVT , D-PHYS , D-ERDW , D-ITET

Image-based Mapping

Lecturers & Examiners: Dr. Torben Peters

VVZ CR n/a

Last Updated: 2026-06-03 00:07:45

Abstract

Application of photogrammetry and remote sensing methods for mapping and Earth observation.

Objective

Learn how to apply photogrammetry, image analysis and machine learning to mapping tasks; hands-on experience in implementing automatic image analysis methods, and in judging their results.

Content

Preprocessing of satellite images, atmospheric correction; extraction of features (radiometric indices, texture descriptors, etc.) from raw image intensities; semantic image segmentation (e.g., cloud masking); physical parameter estimation (e.g., vegetation height); practical deployment of geometric and semantic computer vision and image analysis methods for mapping; assessment of prediction results

General Information

Language: English
Levels: MSC
Frequency: Yearly recurring

Examination

Type: graded semester performance

During the course, student groups will implement several image analysis tasks, and present their projects in class. The grade will be determined by the submitted assignments and the associated presentations.

Course Components

Type	Title	Time & Place	Hours
lecture with exercise	Image-based Mapping	No time listed	2 h weekly

Offered In

Geomatics Master
- Master Studies (Programme Regulations 2022)
  - Core Electives
Space Systems Master
- Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
  - Earth Observation
    - Deep Track Earth Observation (These courses can be credited either as a specialization subject or as an elective subject.)