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ARTÍCULO
TITULO

Central Locations across Spatial Scales: A Quantitative Evaluation for Italy Using Census Enumeration District Indicators

Gianluigi Salvucci    
Luca Salvati and Maria Felice Arezzo    

Resumen

?Marginal? urban settlements can be assumed as specific locations within a metropolitan area that are unable to attract (incoming) commuter flows. The official statistical system of Italy (headed by the National Statistical Institute, Istat) introduced a summary index of ?urban marginality? following the original definition proposed by a national, ad hoc Parliamentary Committee and assessing together social vulnerability and material deprivation at a sufficiently detailed spatial scale. More specifically, the index?intended as a composite indicator of territorial marginality with a normative meaning?was calculated as a specific elaboration of the commuting matrix derived from decadal population censuses considering a municipal-level resolution. In this perspective, the ability of a given municipality to attract bigger (or smaller) inflows than outflows, indicates a specific demand for services allowing the identification of (respectively) central places and peripheral locations. Starting from the index described above, our study generalizes this approach to a wider background context, investigating the roles of spatial scale and geographical coverage. By providing a novel (functional) approach to centrality and periphery, we analyzed commuting patterns at a submunicipal level, indirectly focusing on patterns and processes of local development. A spatial clustering of a standardized polarization index quantifying home-to-work daily travels delineated submunicipal (homogeneous) areas taken as sinks (centers) or sources (peripheries) of commuter flows. The empirical results also demonstrate that spatial neighborhoods (i.e., contiguity order) did not affect the functional classification of a given territory as derived from spatial clustering. Our approach provides a dynamic and innovative interpretation of metropolitan hierarchy using simplified data derived from population censuses.

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