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| JDZL5820 | Remote Sensing and Image Processing | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of GEOMATICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Doç. Dr. Volkan YILMAZ | | Co-Lecturer | | | Language of instruction | | | Professional practise ( internship ) | None | | | | The aim of the course: | | To acquire fundamental knowledge about remote sensing and to produce products tailored to various professional disciplines from different satellite images is the primary goal. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Have ability to understanding of geometric and spectral properties of remotely sensed images, analog and digital images, and electro-optical and microwave systems. | 1,5,10 | | | PO - 2 : | Select appropriate RS data to answer particular geographic questions. | 1,5,10 | | | PO - 3 : | Use at an elementary level an industry standard software package for processing remotely sensed images. Processing will include classification and rectification of image data. | 1,5,10 | | | PO - 4 : | Get familiar with the fundamentals of Digital Image Processing techniques. | 1,5,10 | | | PO - 5 : | Reliably demonstrate the ability to implement IP tools in combination to solve remote-sensing applications problems within software such as MATLAB, Erdas. | 1,5,10 | | | 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 | | |
| Basic principles of Remote Sensing. Electromagnetic radiation and its properties, interaction of electromagnetic radiation with the atmosphere and Earth's surface objects. Concepts of spatial, spectral, and radiometric resolution. Optical and near-infrared sensors. Thermal and microwave image sensors. Characteristics and formats of digital remote sensing images. Atmospheric and geometric corrections in remotely sensed images. Image enhancement techniques. Transformation methods of images into other spaces. Image filtering techniques. Unsupervised and supervised classification. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction, scope of the course, concepts, general definitions, resources | | | Week 2 | Spatial, spectral, and radiometric resolution concepts. | | | Week 3 | Optical and near-infrared sensors. | | | Week 4 | Thermal and microwave image sensors.
| | | Week 5 | Characteristics and format types of digital remote sensing images. | | | Week 6 | Atmospheric and geometric corrections in remotely sensed images | | | Week 7 | Image enhancement techniques. | | | Week 8 | Transformation methods of images into other spaces, such as PCA and IHS transformations. | | | Week 9 | Mid-term exam | | | Week 10 | Image filtering techniques. | | | Week 11 | Writing various filtering algorithms in Matlab. | | | Week 12 | Definition of parametric and non-parametric signatures and their collection and evaluation methods. | | | Week 13 | Unsupervised classification concept. Unsupervised classification algorithms. | | | Week 14 | Supervised classification concept. Supervised classification algorithms. | | | Week 15 | Supervised classification algorithms. | | | Week 16 | Final exam | | | |
| 1 | Mather, P.M. 1987; Computer Processing of Remotely Sensed Images, USA. | | | 2 | Campbell, J. B. 1996; Introduction to Remote Sensing, The Guilford Press. | | | 3 | Lillesand, T.M , Kiefer, R.W. 1997; Remote Sensing and Image Interpretation, John Wiley Sons, USA. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | 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 work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 6 | 8 | 48 | | Arasınav için hazırlık | 6 | 6 | 36 | | Arasınav | 1 | 1 | 1 | | Ödev | 6 | 4 | 24 | | Dönem sonu sınavı için hazırlık | 6 | 5 | 30 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 182 |
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