1. Definition, history and objectives of spatial analysis. Spatial statistics for point pattern.
2. Modelling of point spatial patterns – theoretical models.
3. Inferential statistical tests for point pattern. Analysis of multivariable point events.
4. Introduction to the graph theory. Graph types, spatial structures.
5. Statistical description of graphs and networks. Transport accessibility.
6. Selected tasks in graphs (MST, Gabriel network, Steiner tree, optimal route, traveler salesman problem).
7. Location and allocation tasks. Gravity theory. Analysis of interaction data.
8. Selected analysis for polygons (Areal interpolation. Districting, regionalization. Smoothing. Regression).
9. Multivariate techniques for spatial data – PCA, FA, DA
10. Multivariate techniques for spatial data - hierarchical and non-hierarchical spatial clustering
11. Spatial analysis of continual fields (principles of geostatistics, spatial autocorrelation, structural analysis, anisotropy).
12. Spatial analysis of continual fields (kriging and its variants, co-kriging, stochastic simulations).
13. Fractal dimension.
2. Modelling of point spatial patterns – theoretical models.
3. Inferential statistical tests for point pattern. Analysis of multivariable point events.
4. Introduction to the graph theory. Graph types, spatial structures.
5. Statistical description of graphs and networks. Transport accessibility.
6. Selected tasks in graphs (MST, Gabriel network, Steiner tree, optimal route, traveler salesman problem).
7. Location and allocation tasks. Gravity theory. Analysis of interaction data.
8. Selected analysis for polygons (Areal interpolation. Districting, regionalization. Smoothing. Regression).
9. Multivariate techniques for spatial data – PCA, FA, DA
10. Multivariate techniques for spatial data - hierarchical and non-hierarchical spatial clustering
11. Spatial analysis of continual fields (principles of geostatistics, spatial autocorrelation, structural analysis, anisotropy).
12. Spatial analysis of continual fields (kriging and its variants, co-kriging, stochastic simulations).
13. Fractal dimension.