548-0009/08 – GIS Data Processing (ZDGIS)

Gurantor departmentDepartment of GeoinformaticsCredits6
Subject guarantorIng. Lucie Orlíková, Ph.D.Subject version guarantorIng. Lucie Orlíková, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year2Semesterwinter
Study languageCzech
Year of introduction2021/2022Year of cancellation
Intended for the facultiesHGFIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
HOR10 prof. Ing. Jiří Horák, Dr.
JUR02 Ing. Lucie Orlíková, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+3
Part-time Credit and Examination 8+12

Subject aims expressed by acquired skills and competences

The aim of the subject is to give information students about methods and processes in Data processing in GIS, mainly data analysis. Beside to obtained overview the student will be able to design and realise appropriate procedures and critically evaluate different variants of the solution.

Teaching methods

Lectures
Tutorials
Project work

Summary

The lectures include a review of various possibilities of spatial data processing in geographical information systems. Following main topics are explained: concepts of modifications and transformations of spatial data, basics of map algebra, overlay analysis, neighbourhood analysis including geostatistics and contiguity analysis. A typology of spatial analysis are completed by explanation of mathematical principles and concepts of appropriate algorithms, pros and cons or constraints of each method, case studies and examples of implementation in usual software.

Compulsory literature:

Smith M.J., Goodchild M.F., Longley P.A.: Geospatial Analysis. 2021. http://www.spatialanalysisonline.com Roberts S.A., Robertson C.: Geographic Information Systems and Science. Oxford University Press, 2016. Kanevski M. (ed): Advanced Mapping of Environmental Data. ISTA 2008. Worboys M., Duckham M.: GIS. A computing perspective. CRC Press, ISBN 0-415-28375-2. 2004, 426 stran.

Recommended literature:

Kanevski M. F.: Advanced mapping of environmental data : geostatistics, machine learning and Bayesian maximum entropy. ISTE 2008. 313 s., 978-1-84821-060-8 Zeiler M.: Modeling our World. ESRI Press, Redlands, CA, 1999, 199 pages Wingle W., Poeter E.: Geostatistical Analysis Tutor. Colorado School of Mines. 1999. Available at http://www.uncert.com/tutor/ Burrough P., McDonnell A.: Principles of Geographical Information Systems. Oxford University Press, 1998, 333 stran.

Way of continuous check of knowledge in the course of semester

Students are asked about knowledge from areas that they should have already known from previous lectures. Students also work on individual tasks. Tasks are frequently based on understanding of previous, simpler tasks. Student must pass writing and oral exam.

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:

1. Abstraction, models and modelling. Maintenance and analysis of graphical data. 2. Geometric transformation. Conflaction - horizontal, vertical. Editing graphical data. 3. Generalisation, topological controls. 4. Maintenance and analysis of attribute data. Geocoding. 5. Simple calculations. Descriptive statistics for points. 6. Map algebra. Overlays, quantification of overalys. 7. Multicriteria evaluation. Multitarget evaluation. 8. Neighbor analysis. Searching. Points and lines in polygones. Calculations and classifications using neighbor analysis. Topographical functions. Thiessen polygons. 9. Methods of interpolation. 10. Geostatistics (structural functions, kriging) 11. Analysis of connectivity. Continuity measures. 12. Network analysis. Spreading analysis. Introduction to the graph theory. Searching of optimal paths 13. Visibility analysis. Illumination.

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
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  17
        Examination Examination 67 (67) 18 3
                písemná zkouška Written examination 50  18
                ústní zkouška Oral examination 17  0
Mandatory attendence participation: Continuous check of processing tasks during exercises. Written and oral examination.

Show history

Conditions for subject completion and attendance at the exercises within ISP: Materials for an individual study are available at http://homel.vsb.cz/~hor10/Vyuka/ where you can find also topics for the exam. Consultations (both personal and online) with the lecturer are possible. The exercises are individual based on a semester project which has to be completed to the end of the exam period for the given semester. The exam is conducted only in person.

Show history

Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2024/2025 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan
2023/2024 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2023/2024 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan
2022/2023 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan
2022/2023 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2021/2022 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2021/2022 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction



2023/2024 Winter
2022/2023 Winter