548-0143/01 – Geostatistics (GS)
| Gurantor department | Department of Geoinformatics | Credits | 5 |
| Subject guarantor | Ing. Lucie Orlíková, Ph.D. | Subject version guarantor | Ing. Lucie Orlíková, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 1 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2021/2022 | Year of cancellation | |
| Intended for the faculties | HGF | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
The objective is to acquaint the students with basic properties and modelling of natural objects. The main emphasis lays in explanation of fundamental principles of geostatistical methods and of their general properties, the students learn how to process data using exloratory data analysis, how is spatial autocorrelation important, select the best variogram for interpolation method, how to validate the interpolation methods.
Teaching methods
Lectures
Tutorials
Summary
The subject introduces a concept of spatial autocorrelation, explanation of basic geostatistical concepts (random function and regionalized variables), covariance function, computing and modelling variogram, using geostatistical interpolation methods including a stochastic simulation and nonlinear kriging methods.
Compulsory literature:
Recommended literature:
ISAAKS, E. H., SRIVASTAVA, R. M.Applied geostatistics. 2010. New York: Oxford University Press.
OLIVER, M. A., WEBSTER, R. Basic steps in geostatistics: The variogram and kriging. 2015. Cham: Springer.
WACKERNAGEL, H. Multivariate geostatistics: An introduction with applications. 2010. Berlin: Springer.
MONTERO, J. M., AVILÉS, G. F., MATEU, J. Spatial and spatio-temporal geostatistical modeling and kriging. 2015. Chichester: Wiley.
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.
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. Introduction to geostatistics. Basic concepts. Spatial autocorrelation.
2. Random Function, Regionalized Variable.
3. Global and local interpolation techniques, exact and inexact interpolator. Deterministic methods.
4. Stationarity and intrinsic hypothesis. Basic geostatistical tool for measuring spatial autocorrelation of a regionalized variable.
5. Variogram. Experimental variogram. Range and anizotropy. Regularized and deregularized semivariogram model. Covariation.
6. Trends in geostatistics - polynomial, global, local.
7. Spatially continuous data analysis. Kriging. Simple, ordinary, universal kriging.
8. Spatially continuous data analysis. Indicator kriging, probability kriging.
9. Spatially continuous data analysis. Co-kriging.
10. Cross validation approaches. Error assessment.
11. Empirical Bayesian kriging.
12. Nonlinear kriging methods.
13. Geostatistic conditional simulation.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction