Exploring Relationships Between the Global and Regional Measures of Spatial Autocorrelation

Abstract

Abstract The objective of this research is to investigate dimensions of geographic variation in spatial dependency contained within large multilevel data sets. We calculate 1990 population density by census block group, county, and state for the 48 coterminous states and the District of Columbia of the United States, calculations of interest to a wide variety of spatial scientists. We explore relations between these levels and their variation across the nation. The empirical findings generated by this work furnish implications concerning the Modifiable Areal Unit Problem (MAUP), spatial autocorrelation statistics, scale effects, and resolution.