ABSTRACT
Chapter 1 focuses on concepts, evolution, and growth, and provides example applications of spatial analysis. The field of spatial analysis is mostly inspired by a strong logical positivist tradition that involves inductive and deductive reasoning, hypothesis testing, and model building. Five principal concepts and practical examples including data representation, spatial scale, spatial proximity, spatial autocorrelation, and a modifiable unit areal problem are presented in this chapter. In spatial analysis, we perform specific tasks that are related to visualization, analysis, and modeling subsets of data patterns at different spatial, temporal, or spatiotemporal scales; we determine whether different subsets of data patterns are similar, dissimilar, interconnected, or not, by examining their underlying spatial structure; and we use different spatial units to make, record, or analyze observations. Concepts in this chapter are valuable and helpful in describing spatial features and relationships around places where we live, play, work, worship, shop, eat, or learn.
