Z8108 Remote sensing

Faculty of Science
Spring 2019
Extent and Intensity
2/1/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ing. Kateřina Tajovská, Ph.D. (lecturer)
Mgr. Jan Chytrý (assistant)
Guaranteed by
prof. RNDr. Rudolf Brázdil, DrSc.
Department of Geography – Earth Sciences Section – Faculty of Science
Contact Person: Ing. Kateřina Tajovská, Ph.D.
Supplier department: Department of Geography – Earth Sciences Section – Faculty of Science
Timetable
Mon 18. 2. to Fri 17. 5. Mon 15:00–16:50 Z4,02028
  • Timetable of Seminar Groups:
Z8108/01: Mon 18. 2. to Fri 17. 5. Mon 17:00–17:50 Z1,01001b, K. Tajovská
Z8108/02: Mon 18. 2. to Fri 17. 5. Tue 13:00–13:50 Z1,01001b, K. Tajovská
Z8108/03: Mon 18. 2. to Fri 17. 5. Tue 12:00–12:50 Z1,01001b, K. Tajovská
Prerequisites (in Czech)
KREDITY_MIN(60)
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 60 student(s).
Current registration and enrolment status: enrolled: 0/60, only registered: 0/60
fields of study / plans the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to understand and be able to explain the following topics: Concepts and foundations of Remote Sensing. Energy sources and radiation principles, energy interactions in the atmosphere and with the Earth surface features. Electromagnetic spectrum and its basic parts used in Remote Sensing. History of Remote Sensing. Ideal and real Remote Sensig system. Methods of Remote Sensing. Spectral reflectance curves. Basic elements of photographic systems. Principles of multispectral images. Multispectral, thermal and hyperspectral scanning. Satellite systems. Basic orbits. Characteristic of Earth resources satellites and Meteorological satellites. Principles of photointerpretation. Principles of photogrammetry and orthophoto. Principles of digital image processing. Utilization of pictures nad images in geographical disciplines. Student should be able to understand basic features of remote sensing data and methods explained in individual lectures. He/she would be able to explain when to apply individual data and make reasoned decisions about preconditions that are necessary for proper utilization of RS methods in question. He/she would be able to work with information on satellite data preparation, make deductions based on acquired knowledge concerning remotely sensed data and properly interpret results of multispectral image classification.
Learning outcomes
At the end of this course, the student will be able to understand and explain the concept, advantages and shortcomings of Remote Sensing data that are explained in each lesson.
He will be able to explain when to use specific data and methods with respect to their time, spatial, spectral and radiometric resolution, to provide a rational justification for the conditions of use of the Remote Sensing data.
He should be able to make professional decisions about data preparation, application of basic image processing methods, and interpret and verify the results of analyzes based on acquired knowledge.
Syllabus
  • 1. Definition of Remote Sensing (RS) 2. Physical basis of RS, radiation laws 3. Spectral characteristics of objects. Spectral signatures of basic surfaces. 4. Aerial photography and aerial imaging, flight planing, interpretation of aerial photography. 5. Digital imagery. RS Satellite systems 6. Basic features of digital imagery 7. Thermal RS, features of thermal imagery 8. Microwave RS, active RS, features of RADAR imagery. 9. Current satellite systems. Meteorological satellites 10. Current satellite systems on Earth resources 11. RS Change detection 12. Selected applications of RS methods 13. Thematic and topographic mapping from satellites, data sources
Literature
  • LILLESAND, Thomas M., Ralph W. KIEFER and Jonathan W. CHIPMAN. Remote sensing and image interpretation. 6th ed. New York: John Wiley & Sons, 2008, xii, 756. ISBN 9780470052457. info
  • CAMPBELL, James B. and Randolph H. WYNNE. Introduction to remote sensing. Fifth edition. London: Guilford Press, 2011, xxxi, 667. ISBN 9781609181765. info
  • DOBROVOLNÝ, Petr. Dálkový průzkum Země. Digitální zpracování obrazu. 1. vyd. Brno: Masarykova univerzita, 1998, 208 s. ISBN 8021018127. info
  • Computer processing of remotely sensed imagesan introduction. Edited by Paul M. Mather. 4th ed. Chichester, West Sussex, England: John Wiley & Sons, 2011, xx, 434 p. ISBN 9780470742396. info
  • Remote sensing, models, and methods for image processing. Edited by Robert A. Schowengerdt. 3rd ed. Burlington, MA: Academic Press, 2007, 515 p. ISBN 0123694078. info
  • SVATOŇOVÁ, Hana and Lubomír LAUERMANN. Dálkový průzkum Země - aktuální zdroj geografických informací. 1. vydání. Brno: Masarykova univerzita, 2010, 96 pp. ISBN 978-80-210-5162-1. info
  • HALOUNOVÁ, Lena and Karel PAVELKA. Dálkový průzkum Země. Vyd. 1. Praha: Vydavatelství ČVUT, 2005, 192 s. ISBN 8001031241. info
Teaching methods
Lectures explaining basic terms of remote sensing (RS) and presenting individual examples using RS data and methods step by step. Practical training based on exercises that are solved using satelite imagery and image processing software.
Assessment methods
Lecture and compulsory practical class exercises. Sucessfull pass of all exercises is necessary prerequisite of written test on theory of RS.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2008 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Autumn 2018, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2019, recent)
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