Investigating Metropolitan Hierarchies through a Spatially Explicit (Local) Approach

Abstract

Assuming a non-neutral impact of space, an explicit assessment of metropolitan hierarchies based on local regression models produces a refined description of population settlement patterns and processes over time. We used Geographically Weighted Regressions (GWR) to provide an enriched interpretation of the density gradient in Greece, estimating a spatially explicit rank–size relationship inspired by Zipf’s law. The empirical results of the GWR models quantified the adherence of real data (municipal population density as a predictor of metropolitan hierarchy) to the operational assumptions of the rank–size relationship. Local deviations from its prediction were explained considering the peculiarity of the metropolitan cycle (1961–2011) in the country. Although preliminary and exploratory, these findings decomposed representative population dynamics in two stages of the cycle (namely urbanization, 1961–1991, and suburbanization, 1991–2011). Being in line with earlier studies, this timing allowed a geographical interpretation of the evolution of a particularly complex metropolitan system with intense (urban) primacy and a weak level of rural development over a sufficiently long time interval. Introducing a spatially explicit estimation of the rank–size relationship at detailed territorial resolutions provided an original contribution to regional science, covering broad geographical scales.