Identification of “Hot Spots” of Inner Areas in Italy: Scan Statistic for Urban Planning Policies

Paola Perchinunno (), Francesco D. d’Ovidio () and Francesco Rotondo ()
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Paola Perchinunno: Università degli Studi di Bari
Francesco D. d’Ovidio: Università degli Studi di Bari
Francesco Rotondo: Politecnico di Bari

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2019, vol. 143, issue 3, No 17, 1299-1317

Abstract: Abstract Italy, like many other European countries, is characterized by the presence of numerous municipalities often placed in areas far from major mobility infrastructures (highways, railways, ports and airports), community services (Health services, Education facilities, Administrative centers) and the main economic flows, that are normally defined as “inner areas”. Inner areas are characterized by process of depopulation, economic deficit, marginalization in National and European policies. The study highlights classification methods able to identify the degree of belonging to the class of inner areas. It defines specific indicators able to estimate the level of membership to the inner areas in a scientific way, showing different territorial scenarios. These approaches have been improved using the SaTScan methodology, a circle-based spatial-scan statistical method. It concerns geo-informatic surveillance used as a scientific base to lead urban regeneration policies. The study presented here demonstrates how investigating the inner areas cannot be limited to studying only the distance from the service supply centres, as done by the Italian Ministry ‘s study, but it is necessary to investigate all components of the phenomenon.

Keywords: Statistical methods; Urban planning; Multivariate statistical indices; Place based development policy; Local self-sustainable development; Fuzzy logic (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11205-018-2005-1

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