• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. Obtain the detailed knowledge on current geodesy problems and applications

   Contribution to Program Outcomes

   1. Formulate and solve advanced engineering problems
   2. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
   3. Acquire scientific knowledge
   4. Design and conduct research projects independently

   Method of assessment

   1. Written exam
   2. Homework assignment
2. Model specific geodetic measurement and GPS observation problems

   Contribution to Program Outcomes

   1. Define and manipulate advanced concepts of Geodesy and Photogrammetry Engineering
   2. Formulate and solve advanced engineering problems
   3. Recognize, analyze and solve engineering problems in surveying, planning, GIS and remote sensing fields
   4. Operate modern equipments and hardwares, and use related technical skills in the field of Geodesy and Photogrammetry Engineering.
   5. Acquire scientific knowledge

   Method of assessment

   1. Written exam
   2. Homework assignment
3. Obtain advanced level knowledge on observation methods and modern equipment

   Contribution to Program Outcomes

   1. Formulate and solve advanced engineering problems
   2. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
   3. Acquire scientific knowledge
   4. Design and conduct research projects independently

   Method of assessment

   1. Written exam
   2. Homework assignment

Contents
Week 1:	Monitoring crustal movements with geodetic methods.
Week 2:	Kinematic measurement techniques and their applications.
Week 3:	The use of satellite observations and terrestrial measurements.
Week 4:	Engineering surveying.
Week 5:	Control and renewal measurements for railways.
Week 6:	Integration of various observation methods.
Week 7:	Kalman filtering and its application to geodesy.
Week 8:	Application of artificial intelligence methods in geodetic problems.
Week 9:	Exam
Week 10:	Wavelet transformation and its application to geodetic problems.
Week 11:	GPS system design for automatic vehicle trackig
Week 12:	Filtering of laser scanner data
Week 13:	Design and optimization of geodetic networks
Week 14:	Geodetic coordinate systems and transformations
Week 15*:	General review.
Week 16*:	Final exam
Textbooks and materials:
Recommended readings:	Koch, K. R., 1988, Parameter Estimation and Hypothesis Testing in Linear Models, Berlin, Springer-Verlag. Mikhail, E. M., 1976, Observations and Least Squares, New-York, Dun-Donnelley Publisher. Rao, C. R., Mitra, S. K., 1971, Generalized Inverse of Matrices and its Applications, New-York, John Wiley and Sons. Torge, W., 1991, Geodesy, Walter de Gruyter, Berlin. Seeber, G., 1993, Satellite Geodesy, Walter de Gruyter, Berlin. Cocard, M., 1995, High Precision GPS Processing in Kinematic Mode, Technical Report: Volume 52, Institute für Geodesie und Photogrametterie, Zurich, Switzerland.
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	9	40
Other in-term studies:		0
Project:		0
Homework:		0
Quiz:		0
Final exam:	16	60
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	3	14
Practice, Recitation:	0	0
Homework:	6	10
Term project:	0	0
Term project presentation:	0	0
Quiz:	0	0
Own study for mid-term exam:	15	1
Mid-term:	1	1
Personal studies for final exam:	10	2
Final exam:	2	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)