250 pages | 8 Color Illus. | 40 B/W Illus.
Practical Spatial Statistics is designed as an introductory text for entry-level programmers utilizing statistics and spatial analysis for GIS. The book presents fundamental statistics and GIS theories and concepts. It elaborates on how to conceptualize spatial problems, organize spatial dataset and build analysis framework. The core of the book demonstrates essential spatial statistics techniques from basic spatial data analysis to point pattern analysis and spatial modeling, such as hot-spots analysis and Geographically Weighted Regression (GWR). In addition to easy-to-understand metaphors and lessons, the book provides easily accessible exercises to assist with retention.
1. Practical Spatial Statistics: Fundamental Theories, Techniques and Applications.
2. Spatial statistics overview: History; Four Fundamental Concepts.
3. The Famous Geography Theories: Spatial autocorrelation; Spatial heterogeneity.
4. Spatial Relationships: The various spatial relationships.
5. Statistical measurements in GIS: P value and Z score; Hypothesis testing; Location, attributes, topology, spatial parameters.
6. Basic spatial data discovery: Data integration; Visualization.
7. Building spatial statistical analysis framework.
8. Point data pattern analysis: Attributes of point datasets; Frequency and density; Sampling and Interpolation.
9. Spatial relationship analysis: Clustering analysis; Spatial Autocorrelation analysis; Hot-spots analysis.
10. Spatial regression and modelling: Spatial regression; Geographically Weighted Regression.