Methods for Spatial Data Analysis

Lectures

Lesson 1: Historical overview, introductory concepts and definitions, general applications

Lesson 2: Spatial Data, Data Formats, Types of Spatial Objects or Elements, Spatial Measurement Performance

Lesson 3: Introduction to spatial analysis, spatial models

Lesson 4: Spatial point patterns

Lesson 5: Random, Clustered, and Uniform Point Spatial Patterns

Lesson 6: The method of nearest neighbor distance

Lesson 7: Ripley's K function

Lesson 8: Space-time clustering of point observations

Lesson 9: Analysis of contiguous spatial data

Lesson 10: Spatial Autocorrelation. Semi-variograms. correlograms

Lesson 11: Visualization and exploration of contiguous spatial data

Lesson 12: Spatial Interpolation. Kriging.

Lesson 13: Other Spatial Interpolation Methods

LABORATORY EXERCISES

Exercise 1: Investigating spatial point patterns

Exercise 2: The method of nearest neighbor distances

Exercise 3: Ripley's K function

Exercise 4: Spatio-temporal accumulation of point observations

Exercise 5 Analysis of continuous spatial data

Exercise 6: Spatial autocorrelation. Semivariograms. Correlation charts

Exercise 7: Spatial interpolation I

Exercise 8: Spatial interpolation II

Exercise 9: Spatial interpolation III

Exercise 10: The kernel method

Exercise 11: Geographically weighted regression

Exercise 12: Spatial regression I

Exercise 13: Spatial regression II