103-0128-00L Remote Sensing Lab
Semester | Spring Semester 2018 |
Lecturers | E. Baltsavias |
Periodicity | yearly recurring course |
Language of instruction | English |
Courses
Number | Title | Hours | Lecturers | ||||
---|---|---|---|---|---|---|---|
103-0128-00 G | Remote Sensing Lab Permission from lecturers required for all students.
Persons without sufficient knowledge of remote sensing, photogrammetry and image processing, should first contact the lecturer and get permission to attend the course. Students should preferably have a basic knowledge of MATLAB programming or being willing to acquire it through self-study. | 2 hrs |
| E. Baltsavias |
Catalogue data
Abstract | This course focuses mainly on photogrammetric processing and classification of optical and especially multispectral satellite images with practical work and own programming. |
Objective | The aims of this course are: - the main aim is practical photogrammetric processing and classification of optical and especially multispectral satellite images using mostly own programming in MATLAB and commercial software tools. - some theoretical background will be provided, in addition to other ETHZ courses mentioned below (mainly given in Bachelor). - further developing skills in report writing and presentations. |
Content | The lecture builds on the courses Erdbeobachtung (Earth Observation), Photogrammetrie, Photogrammetrie II, Image Interpretation and Bildverarbeitung (Image Processing). The focus is on practical work and use of programs with optical satellite data. The work is composed of two large labs. In the first, the main photogrammetric processing chain from preprocessing to visualisation is treated. In the second, the focus is on various multispectral classification techniques and their comparison. |
Lecture notes | Teaching material will be made available on the dedicated moodle page. |
Prerequisites / Notice | Persons without sufficient knowledge of remote sensing, photogrammetry and image processing, should first contact the lecturer and get permission to attend the course. Students should preferably have a basic knowledge of MATLAB programming or being willing to acquire it through self-study. |
Performance assessment
Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
ECTS credits | 3 credits |
Examiners | E. Baltsavias |
Type | graded semester performance |
Language of examination | English |
Repetition | Repetition only possible after re-enrolling for the course unit. |
Additional information on mode of examination | Mark is put together as follows: Lab 1 Report: 25% Lab 2 Report: 25% Presentation of Lab 1 or Lab 2: 10% - 15% Questionnaire on Labs 1 and 2: 40% - 35% |
Learning materials
No public learning materials available. | |
Only public learning materials are listed. |
Groups
No information on groups available. |
Restrictions
General | Permission from lecturers required for all students |
Offered in
Programme | Section | Type | |
---|---|---|---|
Geomatic Engineering Master | Major in Engineering Geodesy and Photogrammetry | W |