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Contents
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| Week 1: |
Remote sensing technologies, satellite platforms, sensors and their usage in practice. |
| Week 2: |
Characteristic features of satellite images (geometric, radiometric and spectral features). Introduction to ERDAS and ENVI software, image display and exploring the basic features of sample satellite imagery. |
| Week 3: |
Image analysis and pre-processing in remote sensing (atmospheric and radiometric corrections). Applications related to atmospheric correction in ERDAS and ENVI software using sample satellite images. |
| Week 4: |
Image analysis and pre-processing in remote sensing (geometric correction). Applications related to geometric correction in ERDAS and ENVI software using sample satellite images. |
| Week 5: |
Image transforms and applications in remote sensing (principal component analysis, independent component analysis, hue-saturation-intensity transform). Applications related to image transform techniques in ERDAS and ENVI software using sample satellite images. |
| Week 6: |
Image transforms and applications in remote sensing (band ratios, vegetation indices and texture features). Applications related to image transform techniques in ERDAS and ENVI software using sample satellite images. |
| Week 7: |
Designing a program for the calculation of vegetation indices using MATLAB software. |
| Week 8: |
Midterm Exam |
| Week 9: |
Spectral features of the objects, field spectral measurements, spectroradiometer measurements and analysis of spectral features, building a spectral library, it’s usage and application fields |
| Week 10: |
Application related to Spectral measurements in field and laboratory with a ASD Field Spec3 field spectroradiometer, analysis of spectral features of different surface features, building a sample spectral library and integrating the library with satellite images. |
| Week 11: |
Image pan-sharpening in remote sensing and examining of basic operating principles of the sharpening algorithms. Applications related to image fusion (sharpening) techniques in ERDAS and ENVI software using sample satellite images. |
| Week 12: |
Thematic information extraction using satellite images. Basic information and working principle of classification approaches. Applications related to unsupervised classification methods in ERDAS and ENVI software using sample satellite images. |
| Week 13: |
Thematic information extraction using satellite images. Supervised classification, pre-classification steps and accuracy analysis. Applications related to supervised classification methods in ERDAS and ENVI software using sample satellite images. |
| Week 14: |
Change detection analysis using satellite images, techniques (e.g. image differencing, image rationing and change vector analysis) and its application fields. Applications related to change detection analysis methods in ERDAS and ENVI software using sample satellite images. |
| Week 15*: |
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| Week 16*: |
Final exam |
| Textbooks and materials: |
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| Recommended readings: |
- Mather, P.M. & Koch, M. (2011). Computer Processing of Remotely-Sensed Images: An Introduction. 4th Edition. Chichester, UK: Wiley-Blackwell.
- Lillesand, T.M., Kiefer, R.W. & Chipman, J.W. (2015). Remote Sensing and Image Interpretation. 7th edition, New York, USA: John Wiley & Sons.
- Campbell, J.B & Wynne, R.H. (2011). Introduction to Remote Sensing (5th ed.), NewYork, USA: The Guilford Press.
- Richards, J.A. (2013). Remote Sensing Digital Image Analysis: An Introduction. Fifth Edition. New York, USA: Springer-Verlag.
- 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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