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#40621 / #5

SS 2017 - WS 2018/19

English

Optical Remote Sensing

6

Hellwich, Olaf

benotet

Schriftliche Prüfung

Zugehörigkeit


Fakultät IV

Institut für Technische Informatik und Mikroelektronik

34341600 FG Computer Vision and Remote Sensing

No information

Kontakt


MAR 6-5

Hellwich, Olaf

olaf.hellwich@tu-berlin.de

Learning Outcomes

The module imparts primarily professional and methodological expertise in analyzing remote sensing data. The exploration of the context between physical reality of the environment and data collected with imaging sensors are in the foreground. Mathematical modells are used for description. Data analysis, e.g. object extraction, is conducted with methods of the automatic image analysis. Remote sensing is conceived as an electronical-physically motivated area of computer vision. Interdisciplinary application of the contents are demonstrated using various illustrative examples from e.g. manufacturing industries to geography, medicine and social sciences.

Content

Physical basics, optical sensors, multi- and hyper spectral-sensors, functionality of optical sensors, geometrical and radiometrical image calibration, pre-processing of satellite images, arithmetic image operations, principal axis transform, Tasseled Cap Transform, supervised and unsupervised classification processes, BRDF, spectral demixing, image textures, microwave systems, radar with synthetic aperture (SAR)

Module Components

Pflichtteil:

All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Optical Remote SensingVL0433 L140WiSeNo information2
Optical Remote SensingUE0433 L141WiSeNo information2

Workload and Credit Points

Optical Remote Sensing (VL):

Workload descriptionMultiplierHoursTotal
Attendance15.02.0h30.0h
Preparation/ Post-processing15.02.0h30.0h
60.0h(~2 LP)

Optical Remote Sensing (UE):

Workload descriptionMultiplierHoursTotal
Attendance15.02.0h30.0h
Preparation/ Post-processing15.06.0h90.0h
120.0h(~4 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Underlying sensor components, methods and algorithms are explained in a way allowing transmission of the handled sensor- and system aspects to other cases. Methods and algorithms are implemented and applied exemplarily in the exercises taking part in parallel.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

none

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Written exam

Language

English

Duration/Extent

90 minutes

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Wintersemester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Registration for the exam has to be made online.

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

 

Electronical lecture notes

Availability:  available
Additional information:
https://isis.tu-berlin.de

 

Literature

Recommended literature
No recommended literature given

Assigned Degree Programs


This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
This module is not used in any degree program.

Students of other degrees can participate in this module without capacity testing.

Nebenhörerinnen / Nebenhörer können an der Veranstaltung teilnehmen.

Miscellaneous

The module is offered each winter term.