GMT745 - GEOMETRICAL SENSOR MOD. FOR AERIAL & SAT. IMAGERY

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
GEOMETRICAL SENSOR MOD. FOR AERIAL & SAT. IMAGERY GMT745 Any Semester/Year 3 0 3 10
PrequisitesNone
Course languageEnglish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Question and Answer
Drill and Practice
Project Design/Management
Other: Presentation  
Instructor (s)Prof. Dr. Sultan KOCAMAN GÖKÇEOÄžLU 
Course objectiveInform the students on the state-of-the-art on the rigorous and generic sensor modeling approaches.  
Learning outcomes
  1. The students who successfully completed this course can:
  2. use direct and indirect georeferencing methods,
  3. implement and test rigorous sensor models for aerial and satellite imagery,
  4. use self-calibration technique for the elimination of systematic errors,
  5. follow newest research for the development of rigorous sensor models for optical imagery.
Course ContentDiscussing how to difference between generic and rigorous sensor modeling. The differences between the satellite and aerial optical images based on their geometry. Modeling of systematic errors through self-calibration and test field calibration of satellite images. 
References- Modelling of Spaceborne Linear Array Sensors. D. Poli. ETH Zurich, 2005.
- Sensor Modeling and Validation for Linear Array Aerial and Satellite Imagery. S. Kocaman. ETH Zurich, 2008. 

Course outline weekly

WeeksTopics
Week 1Introduction to georeferencing
Week 2Direct and indirect georeferencing methods
Week 3Generic models for geometrical modelling
Week 4Physical models for geometrical modelling
Week 5Modeling of systematical errors
Week 6Modeling of systematical errors
Week 7Use of GPS/INS data for direct sensor orientation
Week 8Midterm Exam
Week 9Use of GPS/INS data for direct sensor orientation
Week 10Development of physical sensor models
Week 11Development of physical sensor models
Week 12Testing of physical sensor models
Week 13Application project using satellite images
Week 14Application project using satellite images
Week 15Preparation for the final exam
Week 16Final Exam

Assesment methods

Course activitiesNumberPercentage
Attendance140
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments00
Presentation110
Project120
Seminar00
Midterms120
Final exam150
Total100
Percentage of semester activities contributing grade succes1750
Percentage of final exam contributing grade succes150
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 3 42
Laboratory 0 0 0
Application14040
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)14798
Presentation / Seminar Preparation12020
Project15050
Homework assignment000
Midterms (Study duration)21020
Final Exam (Study duration) 12020
Total Workload34150290

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Advances contemporary knowledge in the field of geomatics engineering based on novel thinking and research.   X 
2. Possesses creative and critical thinking, problem solving, and decision making abilities.   X 
3. Conducts a thorough novel research from scratch independently.    X
4. Acquires interdisciplinary knowledge of common terminology and joint working culture.  X  
5. Cooperates with national and international scientific research groups.    X
6. Attains the capacity to publish an international peer-reviewed journal manuscript.     X
7. Maintains ethical responsibility.    X 
8. Obtains the skills to teach undergraduate and graduate level courses offered in geomatics engineering.    X
9. Conducts verbal-written communication, surveys the literature, and prepares thesis in advanced level English.   X 

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest