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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of GEOMATICS ENGINEERING
Masters with Thesis
Course Catalog
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FBE
GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of GEOMATICS ENGINEERING / Masters with Thesis
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JDZL5980Advanced Remote Sensing3+0+0ECTS:7.5
Year / SemesterFall Semester
Level of CourseSecond Cycle
Status Elective
DepartmentDEPARTMENT of GEOMATICS ENGINEERING
Prerequisites and co-requisitesNone
Mode of Delivery
Contact Hours14 weeks - 3 hours of lectures per week
LecturerDoç. Dr. Volkan YILMAZ
Co-Lecturer
Language of instruction
Professional practise ( internship ) None
 
The aim of the course:
The purpose of this course is to teach basic principles of remote sensing. Upon successful completion of this course students will be able to produce processed image products for different disciplines using remote sensing images.
 
Programme OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
PO - 1 : Understand spatial and spectral properties of remotely sensed images and get familiar with optical and SAR systems1,21,
PO - 2 : Sort different images based on their spatial and spectral resolutions and preprocess them to make ready for different applicatons. 1,2,51,
PO - 3 : Use different remote sensing software package 51,3,
PO - 4 : Write their own image enhancement codes and apply them to remote sensing images51,3,
PO - 5 : Plan and complete a remote sensing project2,5,61,3,
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome

 
Contents of the Course
Basic principles of remote sensing. Electromagnetic radiation and its properties. Energy interactions in the atmosphere, Energy interactions with earth surface features (Vegetation, Soil, Water). Spatial, radiometric and spectral resolution. Optical and near-infrared sensors. Thermal and microwave sensors. Properties of digital remote sensing images. Different image formats. Atmospheric and geometric corrections. Image enhancement techniques and applications. Image transforms and applications. Image filtering techniques and applications. Supervised and unsupervised classification algorithms and their applications.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Introduction, content of the course, concepts, general descriptions and course materials
 Week 2Concept of spatial, spectral and radiometric resolution.
 Week 3Optıcal and near ınfrared sensors
 Week 4Thermal and microwave sensors
 Week 5Properties of remote sensing images and different image formats.
 Week 6Atmospheric and geometric corrections of remotely sensed images.
 Week 7Image enhancement techniques
 Week 8Mid-term exam
 Week 9Theory of image transforms. PCA and IHS transform algorithms.
 Week 10Matlab applications of PCA ve IHS transform algorithms
 Week 11Image filtering techniques.
 Week 12Matlab applications of different filtering techniques
 Week 13Definitions of parametric and non-parametric signatures. Different techniques of creating and evaluating parametric and non-parametric signatures.
 Week 14Concept of unsupervised classification. Theory of unsupervised classification algorithms
 Week 15Concept of supervised classification. Theory of supervised classification algorithms
 Week 16Final exam
 
Textbook / Material
1Mather, P.M. 1987; Computer Processing of Remotely Sensed Images, USA.
2Mather, P.M. 1987; Computer Processing of Remotely Sensed Images, USA.
3Erdas Fieldguide
4Erdas Fieldguide
 
Recommended Reading
1Campbell, J. B. 1996; Introduction to Remote Sensing, The Guilford Press.
2Campbell, J. B. 1996; Introduction to Remote Sensing, The Guilford Press.
3Lillesand, T.M , Kiefer, R.W. 1997; Remote Sensing and Image Interpretation, John Wiley Sons, USA.
4Lillesand, T.M , Kiefer, R.W. 1997; Remote Sensing and Image Interpretation, John Wiley Sons, USA.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 1 30
Homework/Assignment/Term-paper 12 1 20
End-of-term exam 16 1 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 14 42
Sınıf dışı çalışma 5 7 35
Arasınav için hazırlık 8 2 16
Arasınav 1 1 1
Ödev 5 8 40
Proje 17 1 17
Dönem sonu sınavı için hazırlık 8 2 16
Dönem sonu sınavı 1 1 1
Total work load168