103-0128-00L  Remote Sensing Lab

SemesterSpring Semester 2018
LecturersE. Baltsavias
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
103-0128-00 GRemote 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
Tue14:45-16:30HIL C 71.1 »
E. Baltsavias

Catalogue data

AbstractThis course focuses mainly on photogrammetric processing and classification of optical and especially multispectral satellite images with practical work and own programming.
ObjectiveThe 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.
ContentThe 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 notesTeaching material will be made available on the dedicated moodle page.
Prerequisites / NoticePersons 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 credits3 credits
ExaminersE. Baltsavias
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationMark 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

GeneralPermission from lecturers required for all students

Offered in

ProgrammeSectionType
Geomatic Engineering MasterMajor in Engineering Geodesy and PhotogrammetryWInformation