ABSTRACT
Urban and regional studies begin with analyzing the spatial structure, particularly population density patterns, in a city or region. Analysis of changing population distribution patterns over time is a starting point for examining economic development patterns in a city or region. Chapter 6 discusses how we find the best-fitting function to capture the density pattern, and what we can learn about urban and regional growth patterns from this approach. Urban and regional density patterns mirror each other: the central business district (CBD) is the center of a city, whereas the whole city itself is the center of a region, and densities decline with distances both from the CBD in a city and from the central city in a region. While the theoretical foundations for urban and regional density patterns are different, the methods for empirical studies are similar and closely related. The methodological focus is on function fittings by regressions and related statistical issues, such as justifications for using nonlinear regression or weighted regression. Various density functions are used to examine urban and regional structures and their evolution from monocentricity to polycentricity. A case study in the Chicago region illustrates the techniques (monocentric vs. polycentric models, linear vs. nonlinear, and weighted regressions).
