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Lecturer(s)
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Miřijovský Jakub, RNDr. Ph.D.
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Course content
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1. Remote sensing in the thermal part of EM spectrum (emissivity of surfaces, correction, basics of physics) 2. Remote sensing of the Earth in the microwave parts of the EM spectrum I (interferometry, altimetry) 3. Remote sensing of the Earth in the microwave parts of the EM spectrum II (polarimetry) 4. Hyperspectral images in remote sensing 5. Remote sensing data processing in Python programming language 6. Machine learning in remote sensing 7. Classification tools for object and texture recognition 8. Google Earth Engine
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Learning activities and teaching methods
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Lecture, Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
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Learning outcomes
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The aim of the course is to introduce to students Advanced methods of remote sensing (theoretically and practically). The course presents using of remote sensing methods in various application. The student will gain advanced knowledge of remote sensing data processing in different softwares.
Define the main ideas and conceptions of the subject, describe the main approaches of the studied topics, recall the theoretical knowledge for solution of model problems.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Mark, Written exam
Student has to prove the knowledge of the subject topics
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Recommended literature
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? Ferretti, A., Monti Guarnieri, A., Prati, C., Rocca, F., & Massonnet, D. (2007). INSAR Principles A.
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Campbell, J., B. (2002). Introduction to Remote Sensing. 3rd ed.. Taylor and Francis, London and Ney York, 621 s.
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Lillesand, T. M., Kiefer, R. W. (2000). Remote Sensing and Image Interpretation. New York: John Wiley and Sons, Inc.
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