155RESE Remote Sensing

Basic Information

• 2 hours lectures per week
• 2 hours exercises per week
• 6 credits
• finished with an exam
• winter semester

Anotation

This lecture shows basics processing methods and use of remotely sensed data. Theoretical lectures provide basics in optics, mathematics, surveying and physics for full understanding of the theme. In practical lessons the theory turns to practice and students process their own data from Sentinel 2 satelite using an open source ESA SNAP software.

Literature

Lillesand, T.M., Kiefer, R.W., Chipman, J.W.: Remote Sensing and Image Interpretation, 7th Ed., Wiley, 2007. ISBN: 978-1-118-34328-9

Canty, M.J.: Image Analysis, Clasification and Change Detection in Remote Sensing. CRC Taylot& Francis. 2007. ISBN: 0-8493-7251-8

Lectures

Lecturer: prof. Dr. Ing. Karel Pavelka

prof. Dr. Ing. Karel Pavelka

or

prof. Dr. Ing. Karel Pavelka

Practical exercises: Ing. Eva Matoušková, PhD. and Ing. Tomáš Bouček

Exercises

• Introduction
• Data download
• Working with remote sensing data 1
• Working with remote sensing data 2
• Image filtering and processing
• Vegetation indeces
• Unsupervised classification
• Supervised classification
• Practical example - land cover
• Classification accuracy
• Introduction to hyperspectral data
• Principal Component Analysis