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Methodologies for Image Processing of Remote Sensing Data
Last Updated: 2026-02-05 16:22:47
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 , NDS
- 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 |
|
2 h weekly |
Offered In
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Electives (The entire course programs of ETH Zurich and the University of Zurich are open to the students to individual selection.)
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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.)
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Elective Modules (For all majors.)
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EM: Landscape (Elective Module for Majors "Environmental Technologies", "Resource Management", "River and Hydraulic Engineering" and "Urban Water Management".)
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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: 701-1674-00L Spatial Analysis, Modelling and Optimisation (FS) or 701-1644-00L Mountain Forest Hydrology (HS).)
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MAS in Sustainable Water Resources (The Master of Advanced Studies in Sustainable Water Resources is a 12 month full time postgraduate diploma programme. The focus of the programme is on issues of sustainability and water resources in Latin America, with special attention given to the impacts of development and climate change on water resources. The programme combines multidisciplinary coursework with high level research. Sample research topics include: water quality, water quantity, water for agriculture, water for the environment, adaptation to climate change, and integrated water resource management. Language: English. Credit hours: 66 ECTS. For further information please visit: )