Sensing Technologies

This course provides an overview on the principles and applications of spaceborne, airborne and terrestrial sensing technologies for geographic data acquisition as well as techniques for processing and information extraction from the acquired data. The topics of this course include:

• Physics of Remote Sensing: Electromagnetic(EM) spectrum and EM interaction with atmosphere and earth surface

• Satellite imagery data processing and machine learning techniques for thematic information extraction

• Principles and applications of RADAR and SONAR

• Principles of Airborne and terrestrial Lidar, introduction to point cloud data acquisition techniques and their applications in different domains

• Principles of Photogrammetry (acquisition, aerotriangulation, adjustment, Stereophotogrammetry, orthophoto and quality assessment)

• Introduction to positioning systems

• Introduction on preparing sensor outputs for GIS storage: (1) image matching techniques; (2) digital image processing; (3) machine learning for automated information extraction and quality assessment approaches including (4) least squares adjustment (LSA); (5) surface fitting for outlier detection.

Written exam and individual formative assignments. An overall grade of 5.75 or above is required to pass the course.

Assignments submitted after the deadline: the grade will be deducted with 10% per day late, and not accepted after 3 days late.

Only students that failed an assignment (grade lower than 5.75) are eligible for a repair task. A successful repair task will result in maximum grade of 6,0 for that assignment.