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102-0617-01L 3 Credits MSC D-ITET , D-BAUG , D-MATH , D-ERDW , D-MAVT , D-PHYS

Methodologies for Image Processing of Remote Sensing Data

Lecturers: Prof. Dr. Irena Hajnsek, Dr. Othmar Frey
Examiners: Prof. Dr. Irena Hajnsek, Dr. Othmar Frey, Dr. Lanqing Huang
VVZ CR n/a

Last Updated: 2026-06-03 00:14:38

Abstract

The aim of this course is to get an overview of several methodologies/algorithms for analysis of different sensor specific information products. It is focused at students that like to deepen their knowledge and understanding of remote sensing for environmental applications.

Objective

The course is divided into two main parts, starting with a brief introduction to remote sensing imaging (4 lectures), and is followed by an introduction to different methodologies (8 lectures) for the quantitative estimation of bio-/geo-physical parameters. The main idea is to deepen the knowledge in remote sensing tools in order to be able to understand the information products, with respect to quality and accuracy.

Content

Each lecture will be composed of two parts: Theory: During the first hour, we go trough the main concepts needed to understand the specific algorithm. Practice: During the second hour, the student will test/develop the actual algorithm over some real datasets using Matlab. The student will not be asked to write all the code from scratch (especially during the first lectures), but we will provide some script with missing parts or pseudo-code. However, in the later lectures the student is supposed to build up some working libraries.

Resources

Lecture Notes

Handouts for each topic will be provided.

Literature

Suggested readings: T. M. Lillesand, R.W. Kiefer, J.W. Chipman, Remote Sensing and Image Interpretation, John Wiley & Sons Verlag, 2008 J. R. Jensen, Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall Series in Geograpic Information Science, 2000

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance

Course Components

Type Title Time & Place Hours
lecture with exercise Methodologies for Image Processing of Remote Sensing Data
  • Thu 08:00-09:35 (HIL E 15.2)
2 h weekly

Offered In

  • Mathematics Master
    • Application Area (Only necessary and eligible for the Master degree in Applied Mathematics. One of the application areas specified must be selected for the category Application Area for the Master degree in Applied Mathematics. At least 8 credits are required in the chosen application area. Credits from other application areas cannot be recognised for further application areas.)
  • Environmental Engineering Master
    • Majors
    • Elective Modules (For all majors.)
      • EM: Landscape (Elective Module for Majors "Environmental Technologies", "Resource Management", "River and Hydraulic Engineering" and "Urban Water Management". Note: Students taking both of the modules LAND and RIVER must take the course 101-1250-00 Transport Processes in Torrents as replacment for for River Basin Erosion that is listed in both modules. Remark: Students also taking module "Remote Sensing and Earth Observation" as replacement of 102-0617-01L Methodologies for Image Processing of Remote Sensing Data in module "Landscape" have to chose one out following list: -701-1241-00L Atmospheric Remote Sensing (HS, 3 KP) -701-1232-00L Radiation and Climate Change (FS, 3 KP) -701-1644-00L Mountain Hydrology (HS, 5KP).)
      • EM: Remote Sensing and Earth Observation (Elective Module for Majors "Environmental Technologies", "Resource Management", "River and Hydraulic Engineering", "Urban Water Management" and "Water Resources Management". Remark: Students also taking module "Remote Sensing and Earth Observation" as replacement of 102-0617-01L Methodologies for Image Processing of Remote Sensing Data in module "Landscape" have to chose one out following list: -701-1241-00L Atmospheric Remote Sensing (HS, 3 KP) -701-1232-00L Radiation and Climate Change (FS, 3 KP) -701-1644-00L Mountain Hydrology (HS, 5KP).)
  • Space Systems Master