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| HRT3009 | Remote Sensing | 2+1+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of GEOMATICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 2 hours of lectures and 1 hour of practicals per week | | Lecturer | Doç. Dr. Volkan YILMAZ | | Co-Lecturer | DOCTOR LECTURER Esra TUNÇ GÖRMÜŞ, | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | Objectives of this course are to explain the basic fundamentals of remote sensing, how to get information from satellite image and how to interpret them, review of basic and advanced principles of image analysis; advanced laboratory techniques, integration of remote sensing with GIS. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Have ability to understanding of geometric and spectral properties of remotely sensed images, analog and digital images, and electro-optical and microwave systems. | 4,6 | 1 | | LO - 2 : | Be aware of the range of satellite data available from earth orbiting remote sensing satellites. | 4,6 | 1 | | LO - 3 : | Understand the properties of such data relevant for GIS users. | 4,6 | 1,3 | | LO - 4 : | Select appropriate RS data to answer particular geographic questions. | 4,6 | 1 | | LO - 5 : | Analyze remotely sensed data in order to generate information suitable for a GIS application. | 4,6 | 1,3 | | LO - 6 : | Manage a simple remote sensing data chain from acquisition, and manage a project sourced remote sensing data. | 4,6 | 3 | | LO - 7 : | Use at an elementary level an industry standard software package for processing remotely sensed images to perform image processing applications such as | 4,6 | 1,3 | | 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), LO : Learning Outcome | | |
| Introduction, Energy sources and radiation principles, Energy interactions in the atmosphere, Energy interactions with earth surface features (Vegetation, Soil, Water) , Thermal Remote Sensing, Thermal images, thermal characteristics of objects, Microwave Remote Sensing, Digital image, Resolutions, Characteristics of an idea/real remote sensing system, Multispectral sensing, Reference data, Color, Earth resource satellites and characteristics, Preprocessing, Radiometric correction, Atmospheric correction, Noise reduction, Geometric correction, (Rectification, Registration) , Image enhancement , Contrast enhancement, Filtering, Image rationing: VI, NDVI, Feature extraction, Classification algorithms, Unsupervised classification, Supervised classification. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction, content of the course, conceps, general descriptions and course materials | | | Week 2 | Energy sources and radiation principles | | | Week 3 | Energy interactions in the atmosphere, Energy interactions with earth surface features (Vegetation, Soil, Water) | | | Week 4 | Satellites, sensors and their properties | | | Week 5 | Digital image, resolution concept, properties of remote sensing systems | | | Week 6 | Multispectral and hyperspectral remote sensing, band and spectral information concepts | | | Week 7 | Preprocessing of images, radiometric correction, atmospheric correction, noise reduction | | | Week 8 | Image registration and rectification | | | Week 9 | Mid-term exam | | | Week 10 | Image enhancement, contrast enhancement, filtering, band ratios (VI, NDVI) | | | Week 11 | Image enhancement applications | | | Week 12 | Feature extraction, classification algorithms | | | Week 13 | Unsupervised classification | | | Week 14 | Supervised Classification | | | Week 15 | Classification applications | | | Week 16 | End-of-term exam | | | |
| 1 | Mather, P.M. 1987; Computer Processing of Remotely Sensed Images, USA. | | | 2 | Erdas Fieldguide | | | |
| 1 | Lillesand, T.M , Kiefer, R.W., 1997; Remote Sensing and Image Interpretation, John Wiley Sons, USA. | | | 2 | Campbell, J. B., 1996; Introduction to Remote Sensing, The Guilford Press. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 1 | 30 | | Homework/Assignment/Term-paper | 12 | | 2 | 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 | 8 | 5 | 40 | | Arasınav | 1 | 1 | 1 | | Ödev | 3 | 3 | 9 | | Dönem sonu sınavı için hazırlık | 8 | 6 | 48 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 189 |
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