Universität Wien

290237 VU Image Processing and Remote Sensing, Group B (2014W)

3.00 ECTS (2.00 SWS), SPL 29 - Geographie
Continuous assessment of course work

Termine:
MI 01.10.2014 16:30-18:00 Ort: Computerkartographie (MM-Labor)
MI 15.10.2014 16:30-18:00 Ort: Computerkartographie (GIS-Labor)
MI 29.10.2014 16:30-18:00 Ort: Computerkartographie (GIS-Labor)
MI 12.11.2014 15:00-16:30 (A), 16:30-18:00(B), 18:00-19:30(C) Uhr, HS 5A (1. Teilprüfung)
MI 19.11.2014 16:30-18:00 Ort: Computerkartographie (GIS-Labor)
MI 26.11.2014 16:30-18:00 Ort: Computerkartographie (GIS-Labor)
MI 03.12.2014 16:30-18:00 Ort: Computerkartographie (GIS-Labor)
MI 10.12.2014 16:00-17:30 (A), 17:30-19:00(B), 19:00-20:30(C) Uhr, HS 4C (2. Teilprüfung)
MI 07.01.2015 16:30-18:00 Ort: Hörsaal 5A Geographie NIG 5.OG A0518
DO 08.01.2015 09:00-10:00 Ort: Hörsaal 5A Geographie NIG 5.OG A0518
DO 08.01.2015 12:00-13:00 Ort: Computerkartographie (MM-Labor)
DO 08.01.2015 15:00-16:00 Ort: Ort: Hörsaal 5A Geographie NIG 5.OG A0518
SA 10.01.2015 09:30-11:00 Ort: Ort: Hörsaal 5A Geographie NIG 5.OG A0518
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: German

Lecturers

Classes

Currently no class schedule is known.

Information

Aims, contents and method of the course

Earth observation represents a major information source for geo-applications. New fields of remote sensing application are evolving due to the improvement of spatial and spectral resolution. But data acquisition alone is not sufficient to benefit from these technological developments.

Assessment and permitted materials

Three Exams, one per Part/Lecturer.

Minimum requirements and assessment criteria

The lecture aims at providing the fundamentals of remote sensing and basics of digital image processing.

Examination topics

It is rather necessary to develop methods and techniques for transforming the huge amount of data acquired by satellite sensors into useful information for the different fields of application. A prerequisite to perform this task is an understanding of physical fundamentals of remote sensing and the properties of sensors, knowledge of mathematical and statistical models and algorithms for analysing the data and finally an insight into application processes, where the extracted information is used.

Reading list

Association in the course directory

(B11-6.4)

Last modified: Mo 07.09.2020 15:42