Measuring shrinkage and its effects appears as a fundamental issue in cities’ research. Also, shrinkage is a spatial phenomenon defined by data and information based on space dimension relying on a spatial information. The wide use of geo-information is a useful aid to extend common statistic analyses integrating data collected at different levels, comparing data at a municipal level to data referring at census area level (particularly useful for detailed analyses at a neighbourhood scale). Such analyses are particularly suitable for medium and large cities shrinkage analyses, where different neighbourhoods could have different levels of shrinkage and could need distinct strategies to face such phenomenon. Another methodological problem is the interrelation with other spatial units and nearby cities, which can have an influence on urban labour market, economic development, migration flows and housing market. Thereby, the definition of an appropriate regional context is of crucial importance. After an introduction about a comparison between common statistic analyses and geo-statistical methods, with a short literature review, the paper includes an empirical section describing the case of de-industrialized Taranto city, measuring the major indicators of shrinkage, with data referring to census area level, trying to understand if there are shrinking neighbourhoods in the city of Taranto and what is the appropriate regional shrinking context. Then, the paper continues with a section in which the theoretical knowledge is evaluated comparing theory strongholds to main features of shrinkage exemplified by the case of Taranto, trying to contribute to a better understanding of the questions addressed, highlighting the unresolved problems to address some conclusions about still open research challenges.

A Geostatistical Approach to Measure Shrinking Cities: The Case of Taranto

MURGANTE, BENIAMINO;
2013-01-01

Abstract

Measuring shrinkage and its effects appears as a fundamental issue in cities’ research. Also, shrinkage is a spatial phenomenon defined by data and information based on space dimension relying on a spatial information. The wide use of geo-information is a useful aid to extend common statistic analyses integrating data collected at different levels, comparing data at a municipal level to data referring at census area level (particularly useful for detailed analyses at a neighbourhood scale). Such analyses are particularly suitable for medium and large cities shrinkage analyses, where different neighbourhoods could have different levels of shrinkage and could need distinct strategies to face such phenomenon. Another methodological problem is the interrelation with other spatial units and nearby cities, which can have an influence on urban labour market, economic development, migration flows and housing market. Thereby, the definition of an appropriate regional context is of crucial importance. After an introduction about a comparison between common statistic analyses and geo-statistical methods, with a short literature review, the paper includes an empirical section describing the case of de-industrialized Taranto city, measuring the major indicators of shrinkage, with data referring to census area level, trying to understand if there are shrinking neighbourhoods in the city of Taranto and what is the appropriate regional shrinking context. Then, the paper continues with a section in which the theoretical knowledge is evaluated comparing theory strongholds to main features of shrinkage exemplified by the case of Taranto, trying to contribute to a better understanding of the questions addressed, highlighting the unresolved problems to address some conclusions about still open research challenges.
2013
9788847027503
9788847027510
File in questo prodotto:
File Dimensione Formato  
taranto.pdf

accesso aperto

Tipologia: Documento in Post-print
Licenza: DRM non definito
Dimensione 1.15 MB
Formato Adobe PDF
1.15 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/36061
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact