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Contents
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| Week 1: |
Fundamental terms and definitions, historical development of remote sensing, remote senisng in our daily lifes, major applications of remote sensing (geological, environmental, surveying, planning etc.) |
| Week 2: |
Electromagnetic spectrum (visible, infrared, thermal and radar images), Characteristics of images in specific regions and their basic applications. What is an image band ? How a pixel is formed ? |
| Week 3: |
Light and light sources for remote sensing. Fundamentals and working principles of active and passive sensors used in remote sensing. Image display methods and interpretation of pseudocolour images. |
| Week 4: |
Energy-object interactions, signatures of the objects, Atmospheric efefcts and their modelling through some approaches. Atmospheric windows and available band ranges. |
| Week 5: |
Details on resolutions in remote sensing (Spatial, Spectral, Radiometric and Temporal Resolutions). Various sensors characteristics and their possible applications. Homework-1 |
| Week 6: |
Relationship between spatial resolution and point spread function. Distortions and other factors affecting images (systematic and nonsytematic factors). Preprocessing of satellite images (e.g. missing scan line defects) |
| Week 7: |
Description of sensor systems (whiskbroom, pushbroom, digital cameras and types of radiometres). Pros and Cons of sensor systems. Sample sensors using specific types of systems. |
| Week 8: |
Midterm Exam, Technical specifications and comparisons of Whiskbrrom and Pushbroom sensors |
| Week 9: |
Photographic and optic sensing systems and their comparisons, description of radar systems, their working principlesi applications, defects and their corrections in radar images. principles of SAR and SLAR systems. Example sensor systems (e.g. SIR program) |
| Week 10: |
Introduction to digital image processing, eadiometric and geometric rectification/restoration, image enhancement techniques mainly to enhance image contrast |
| Week 11: |
Introduction to the topic of vegetation indicies, their importance in agriculatural applications, vegetation monitoring and precision farming. Principla component analysis, Fourier transformation for image transformation and enhancement. |
| Week 12: |
Approaches developed for pattern recognition, Classification of satellite images. Different approaches and basis for classification (hard-soft, pixel-parcel, statictical-nonstatistical etc.), supervised and unsupervised classification techniques.Homework-2 |
| Week 13: |
Supervised classification techniques, analysis of classification rssults using contingency matrices. Various accuracy estimates used to evaluate the quality of image classifications. Tehmatic maps and their chracteristics. |
| Week 14: |
Basic principles of advanced classification techniques (artificial eural networks, support vector machies, decision trees, etc.). The use of contexual and textural information in remote sensing. Application of basic image processing tasks on sample images in laboratry using well-known software packages. |
| Week 15*: |
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| Week 16*: |
Final exam |
| Textbooks and materials: |
Lillesand, T.M. Kiefer, R.W., Chipman, J.W., 2018. Uzaktan Algılama ve Görüntü Yorumlama, Palme Yayınevi.
Mather, P. M., 1999, Computer processing of remotely-sensed images: an introduction: Chichester, John Wiley.
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| Recommended readings: |
Jensen, J. R., 1996, Introductory digital image processing - a remote sensing perspective: London, Prentice Hall.
Lillesand, T. M., and R. W. Kiefer, 1994, Remote sensing and image interpretation: New York, John Wiley & Sons.
Campbell, J. B., 1987, Introduction to remote sensing: London, The Guilford Press.
Maktav, D. ve Sunar, F., 1991, Uzaktan algılama, kantitatif yaklaşım: İstanbul, Hürriyet Ofset A.Ş.
Barrett, E.C., and Curtis, L.F., 1999, An introduction to environmental remote sensing, Routledge.
Congalton, R.G., and Green, K., 1998, Assessing the accuracy of remotely sensed data: principles and practices, Lewis Publishers. |
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* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
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