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

被引:0
|
作者
Paola Perchinunno
Francesco D. d’Ovidio
Francesco Rotondo
机构
[1] Università degli Studi di Bari,Dipartimento di Economia Management e Diritto dell’Impresa (DEMDI)
[2] Università degli Studi di Bari,Dipartimento di Economia e Finanza (DiEF)
[3] Politecnico di Bari,Dipartimento di Ingegneria Civile e Architettura (DICAR)
来源
Social Indicators Research | 2019年 / 143卷
关键词
Statistical methods; Urban planning; Multivariate statistical indices; Place based development policy; Local self-sustainable development; Fuzzy logic;
D O I
暂无
中图分类号
学科分类号
摘要
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.
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页码:1299 / 1317
页数:18
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