548-0950/01 – Advanced Methods of Remote Sensing (PMDPZ)

Gurantor departmentDepartment of GeoinformaticsCredits10
Subject guarantorprof. Ing. Jiří Horák, Dr.Subject version guarantorprof. Ing. Jiří Horák, Dr.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageCzech
Year of introduction2021/2022Year of cancellation
Intended for the facultiesHGFIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
HOR10 prof. Ing. Jiří Horák, Dr.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 20+0
Part-time Examination 20+0

Subject aims expressed by acquired skills and competences

The objective is to develop student’s knowledge of the branch of remote sensing including advanced methods of image processing, image segmentation, object-oriented classification, using uncertainty for classification, using machine-learning for classification, image spectroscopy, radar systems and lidars.

Teaching methods

Lectures
Individual consultations
Other activities

Summary

The course extends knowledge of remote sensing. It is focused on radiometric and atmospherical corrections, advanced methods of image filtration and utilization of derived indicators such as local textural measures, image segmentation methods, Fourier transformation, Hough transformation, advanced methods of clasification suitable for contemporary data with high resolution (object-oriented and neural clasifications, using SVM), image spectroscopy, radar systems, and lidar.

Compulsory literature:

LIU J.G, MASON P.J. Image Processing and GIS for Remote Sensing. Willey, 2016. ISBN 9781118724200 LILLESAND T., KIEFER R., CHIPMAN J. Remote sensing and image interpretation. Wiley, 2015, 736 stran. ISBN: 978-1-118-34328-9 BLASCHKE, T., LANG, S., HAY, G. (Eds.). Object-Based Image Analysis. Springer Lecture Notes in Geoinformation and Cartography, 2008, XVII, 817 p. GRUBESIC, T.H., NELSON, J.R., 2020. UAVs and urban spatial analysis: an introduction. Springer, Cham. S. 206. ISBN 978-3-030-35865-5.

Recommended literature:

SMITH, R. B. Analyzing hyperspectral data. Microimages, Inc., 2013. Dostupné na https://www.microimages.com/documentation/Tutorials/hypanly.pdf RICHARDS, J.A. Remote Sensing with Imaging Radar. Springer Verlag, 2009. ISBN: 3642020194. CHUVIECO, E. Fundamentals of satellite remote sensing: an environmental approach, Second edition. ed. CRC Press, Taylor & Francis Group, Boca Raton, 2016. S. 468. ISBN 978-1-4987-2805-8 MOTT, H. Remote sensing with polarimetric radar. IEEE Press ; Wiley-Interscience, 2007. s. 309. ISBN 978-0-470-07476-3

Way of continuous check of knowledge in the course of semester

Účast na konzultacích, seminární práce, ústní zkouška.

E-learning

Other requirements

No additional requirements are imposed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Radiometric and atmospherical corrections Filtration, edge detectors, Laplacian operators, Texture, local textural measures Image segmentation methods Fourier transformation. Hough transformation Object-oriented clasification Classification based on machine learning (deep learning, convolutional neural network). Classification and uncertainty. Mixed pixels. Image spectroscopy. Radar systems Lidar

Conditions for subject completion

Full-time form (validity from: 2021/2022 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)		Min. number of pointsMax. počet pokusů
Examination Examination   3
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (P0532D330037) Geoinformatics K Czech Ostrava Choice-compulsory type B study plan
2024/2025 (P0532D330037) Geoinformatics P Czech Ostrava Choice-compulsory type B study plan
2023/2024 (P0532D330037) Geoinformatics K Czech Ostrava Choice-compulsory type B study plan
2023/2024 (P0532D330037) Geoinformatics P Czech Ostrava Choice-compulsory type B study plan
2022/2023 (P0532D330037) Geoinformatics P Czech Ostrava Choice-compulsory type B study plan
2022/2023 (P0532D330037) Geoinformatics K Czech Ostrava Choice-compulsory type B study plan
2021/2022 (P0532D330037) Geoinformatics P Czech Ostrava Choice-compulsory type B study plan
2021/2022 (P0532D330037) Geoinformatics K Czech Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

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