Z6101 Introduction to geostatistics

Faculty of Science
Spring 2022
Extent and Intensity
1/2. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Petr Dobrovolný, CSc. (lecturer)
Mgr. Lukáš Slezák (seminar tutor)
Guaranteed by
prof. RNDr. Petr Dobrovolný, CSc.
Department of Geography – Earth Sciences Section – Faculty of Science
Contact Person: prof. RNDr. Petr Dobrovolný, CSc.
Supplier department: Department of Geography – Earth Sciences Section – Faculty of Science
Timetable
Wed 9:00–9:50 Z3,02045
  • Timetable of Seminar Groups:
Z6101/01: Tue 18:00–19:50 Z1,01001b, L. Slezák
Prerequisites (in Czech)
! Z8102 Spatial modelling and geostat.
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 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20
fields of study / plans the course is directly associated with
Course objectives
Main objectives can be summarized as follows: statistical analysis of spatial data with the help of geoinformatics. The course is oriented on deterministic methods of interpolation, modeling of continuous fields (surfaces), concept of spatial autocorrelation, structural analysis and structural functions, variogram modeling, fundamentals of kriging, statistical properties of continuous fields such as homogeneity, continuity, isotropy, point descriptors, pattern detectors for point, line and polygon objects. At the end of the course student should be able to understand basic geostatistical methods explained in individual lectures. He/she would be able to explain when to apply individual methods and make reasoned decisions about preconditions that are necessary for proper utilization of geostatistical methods in question. He/she would be able to work with information on data preparation, make deductions based on acquired knowledge concerning geostatistical methods and properly interpret results from various geographical disciplines (landscape ecology, demography, precision farming etc.).
Learning outcomes
Completing the course students will be able to:
- select suitable deterministic model of spatial interpolation
- apply structural analysis and to set up varigram model
- apply method of Kriging for spatial interpolation of geographical data
- use simple descriptors of spatial distribution of objects
- aplly measures of spatial autocorrelation (Moran's I)
Syllabus
  • 1. Concept of spatial autocorrelation 2. Methods of Exploratory Spatial Data Analysis (ESDA) 3. Deterministic interpolation methods, concept, data sources, data sampling 4. Global and local interpolators, exact and approximating methods, Thiessen polygons, IDW, Spline functions, Trend analysis 5. Polygon spatial interpolation methods 6. Structural analysis and structural functions 7. Variogram modeling and interpretation 8. Geostatistical methods of interpolation, Kriging 9. Point, line and polygon descriptors 10. Detectors of spatial distribution for point, line and polygon objects, Moran Index, G-statistics 11. Local Indicators of Spatial Autocorrelation (LISA) 12. Methods of objective classification
Literature
  • WEBSTER, R. and M. A. OLIVER. Geostatistics for environmental scientists. 2nd ed. Chichester: John Wiley & Sons, 2007, xii, 315. ISBN 9780470028582. info
  • DE SMITH, Michael John, Michael F. GOODCHILD and Paul LONGLEY. Geospatial analysis : a comprehensive guide to principles, techniques and software tools. 2nd ed. Leicester: Metador, 2007, xxii, 491. ISBN 9781906221980. info
  • BORROUGH, P.A., McDONNELL, R.,A (1988): Principles of Geographical Information Systems. Oxford University Press, Oxford, 333s.
  • MCKILLUP, Steve and M. Darby DYAR. Geostatistics explained : an introductory guide for earth scientists. 1st pub. Cambridge: Cambridge University Press, 2010, xvi, 396. ISBN 9780521746564. info
Teaching methods
Lectures explaining basic terms from geostatistics and spatial autocorrelation and presenting individual examples step by step. Practical training based on 11 exercises that are solved using GIS and geostatistical software.
Assessment methods
One written test at the end. Elaboration of all practical excercises is the necessary conditon for passing the exam.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2008 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, 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, Spring 2019, Spring 2020, Spring 2021, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2022/Z6101