1. Definition of main concepts and ideas for understanding uncertainty in geoinformatics.
2. Imprecision, accuracy, vagueness, ambiguity
3. Error, reliability, error evaluation, sampling
4. Error propagation, Monte Carlo simulation.
5. Data quality and description, elements of data quality.
6. Standardization of data quality description, storage.
7. Organisation of data collection, methods.
8. Sources of uncertainty and methods of description. Sensitivity analysis.
9. Measurement of vagueness. Fuzzy set, fuzzy numbers, operations with fuzzy sets.
10. Spatially uncertain objects, fuzzy spatial operation. 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. Uncertainty visualization. UVI concept. Intrinsic and extrinsic variables.
2. Imprecision, accuracy, vagueness, ambiguity
3. Error, reliability, error evaluation, sampling
4. Error propagation, Monte Carlo simulation.
5. Data quality and description, elements of data quality.
6. Standardization of data quality description, storage.
7. Organisation of data collection, methods.
8. Sources of uncertainty and methods of description. Sensitivity analysis.
9. Measurement of vagueness. Fuzzy set, fuzzy numbers, operations with fuzzy sets.
10. Spatially uncertain objects, fuzzy spatial operation. 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. Uncertainty visualization. UVI concept. Intrinsic and extrinsic variables.