Spatial Analysis Theory and Practice

Designed as an entry-level text, this book teaches spatial analysis and spatial statistics using GIS software. Every chapter introduces a set of methods and measures, shows how to read the output, and walks through a worked example.

The coverage moves through several areas: exploratory spatial data analysis, which describes and maps data; the study of geographic distributions and point patterns; spatial autocorrelation; spatial clustering; and both geographically weighted regression and ordinary least squares regression, along with spatial econometrics. A single real-world case study runs through the examples, so the theory is always tied to a concrete problem. Each exercise is first solved in ArcGIS and then repeated in GeoDa.

The author follows a simple framework: describe the dataset, examine spatial relationships and associations, then build models. Results are interpreted with a critical eye, and the book weighs the strengths and weaknesses of each technique. It is aimed at graduate students and researchers who work with geospatial data in environmental science, geography, and the social sciences.