548-0115/01 – Uncertainty in Geoinformatics (NEGET)

Gurantor departmentDepartment of GeoinformaticsCredits5
Subject guarantordoc. Ing. Jiří Horák, Dr.Subject version guarantordoc. Ing. Jiří Horák, Dr.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semesterwinter
Study languageCzech
Year of introduction2016/2017Year of cancellation
Intended for the facultiesHGFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
HOR10 doc. Ing. Jiří Horák, Dr.
RUZ02 Ing. Kateřina Růžičková, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 6+6

Subject aims expressed by acquired skills and competences

The objective is to explain basic concepts of uncertainty, the role of uncertainty during spatial data processing and spatial modelling, to learn how to apply suitable methods for performing spatial data analysis, to be able to integrate information from other application field with approaches recommended for control and management of uncertainty, and to evaluate the data quality.

Teaching methods

Lectures
Tutorials

Summary

Introduction to typology of uncertainty and its application in geoinformatics. Eplanation of basic concept such as imprecision, vagueness, ambiguity. Explanation of error types, reliability and its measurement, error evaluation for quantitative and qualitative data, error propagation. Description and explanation of data quality which are used in metadata. Dealing with sources of uncertainty and methods of description. Explanation of fuzziness (fuzzy set, operation, fuzzy region, topological and other spatial operation. Dealing with qualitative measurements of uncertainty, multivalue logic, endorsement theory, Bayes theory and Dempster-Shafer theory. Introduction to uncertainty visualization.

Compulsory literature:

CAERS J. Modeling uncertainty in the Earth Sciences. Wiley-Blackwell, 2011. ISBN 978-1-119-99263-9 DEVILLERS R., JEANSOULIN R. (Eds): Fundamentals of spatial data quality. London: ISTE. 2006. SHI W. Principles of Modeling Uncertainties in Spatial Data and Spatial Analysis. CRC Press (Taylor & Francis) 2010. WORBOYS M., DUCKHAM M. Geographic Information Systems: A Computing Perspective (2nd Edition), CRC Press, Boca Raton, Florida, 2004. ISBN 0415283752

Recommended literature:

CAHA, J. Uncertainty Propagation in Fuzzy Surface Analysis. PhD thesis, Palacky University in Olomouc, 2014 HEUVELINK, G.B.M., BROWN, J.D., VAN LOON, E.E. A probabilistic framework for representing and simulating uncertain environmental variables. International Journal of Geographic Information Science, 2006, 2/5, p. 497-513. KINKELDEY, C., SENARATNE, H. Representing Uncertainty. The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2018 Edition), John P. Wilson (ed.). DOI:10.22224/gistbok/2018.2.3 MASON J.S., RETCHLESS D., KLIPPEL A. Domains of uncertainty visualization research: a visual summary approach, Cartography and Geographic Information Science, 2016. DOI: 10.1080/15230406.2016.1154804

Way of continuous check of knowledge in the course of semester

E-learning

Other requirements

No additional requirements are applied.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Definition of main concepts and ideas for understanding uncertainty in geoinformatics. 2. Error, reliability, error evaluation, sampling 3. Error propagation, Monte Carlo simulation. 4. Data quality and description, elements of data quality. 5. Standardization of data quality description, storage. 6. Organisation of data collection. 7. Sources of uncertainty and methods of description. 8. Sensitivity analysis. 9. Fuzzy set, fuzzy numbers, region, fuzzy spatial operation 10. Rough sets theory. 11. Qualitative measurements of uncertainty - Revision of belief. Multivalue logic. Endorsement theory. 12. Quantitative measurements of uncertainty - Bayes theory. Dempster-Shafer theory. 13. Validity and objectiveness. 14. Uncertainty visualization

Conditions for subject completion

Part-time form (validity from: 2017/2018 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  17
        Examination Examination 67  18
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2021/2022 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Compulsory study plan
2021/2022 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Compulsory study plan
2020/2021 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Compulsory study plan
2020/2021 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Compulsory study plan
2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Compulsory study plan
2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Compulsory study plan
2017/2018 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Compulsory study plan
2017/2018 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

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