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Ukončeno v akademickém roce 2018/2019

Data and Model Uncertainty

Type of study Follow-up Master
Language of instruction Czech
Code 548-0052/01
Abbreviation NEDAM
Course title Data and Model Uncertainty
Credits 5
Coordinating department Department of Geoinformatics
Course coordinator prof. Ing. Jiří Horák, Dr.

Osnova předmětu

Terminology (uncertainty, ambiguity, vagueness, fuziness, quality, accuracy, errors, reliability), semantic issues. Dominant concepts in dealing with uncertainty (inheritent complexity and details of the world and phenomena, inheritent vagueness of definitions and concept, missing natural units for analysis, ambiguity of indirect indicators). Sources of errors and uncertainty. Introduction to application of Monte Carlo method. Geographical uncertainty (crisp boundaries, location etc.), attribute uncertainty. Ecological falacy, MAUP and data agreggation. Spatial autocorrelation. Errors of vector-raster conversions. Error propagation (statistical aproach, simulation aproach). Error balancing. Internal and external validation. Senstivity analysis. Methods based on simulations or decomposing the variance of the output. Reliability and Survival in Econometrics and Finance. Metadata. Bayesian theory, Bayesian belief networks. Dempster-Shafer theory. Techniques for reducing, quantifying and visually representing uncertainty. Cost and benefits of uncertainty decreasing. Uncertainty of decision making.

Povinná literatura

Shi W.: Principles of Modeling Uncertainties in Spatial Data and Spatial Analysis. CRC Press (Taylor & Francis) 2010.
Zhang J.X., Goodchild M.F. (2002): Uncertainty in Geographic Information. New York. Taylor & Francis.

Doporučená literatura

Longley, P.A., Goodchild M.F., Maguire D.J., Rhind D.W.: Geographical Information Systems and Science. Wiley, 2005 (s. 127-153)
Burrough P., McDonnell A.: Principles of Geographical Information Systems. Oxford University Press 1998, 333 stran. s.220-264.
Maguire, DJ, Batty M, Goodchild MF: GIS, Spatial Analysis and Modeling. ESRI 2005. s. 68-129.
Andrea Saltelli, Stefano Tarantola, Francesca Campolongo and Marco Ratto (2004) SENSITIVITY ANALYSIS IN PRACTICE. A GUIDE TO ASSESSING SCIENTIFIC MODELS. Wiley. ISBN 0-470-87093-1 .