Urban sustainability : complex interactions and the measurement of risk

This paper focuses on the concept of a sustainable city and its theoretical implications for the urban system. Urban sustainability is based on positive interactions among three different urban sub-systems : social, economic and physical, where social well-being coexists with economic development an...

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Autores principales:	Lidia Diappi, Paola Bolchi, Lorena Franzini
Formato:	article
Lenguaje:	DE EN FR IT PT
Publicado:	Unité Mixte de Recherche 8504 Géographie-cités 1999
Materias:	sustainable city urban system neural networks risk assessment Milan Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/ee00cc4e731b42149da1526e29b94614
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spelling	oai:doaj.org-article:ee00cc4e731b42149da1526e29b946142021-12-02T11:13:00ZUrban sustainability : complex interactions and the measurement of risk1278-336610.4000/cybergeo.1240https://doaj.org/article/ee00cc4e731b42149da1526e29b946141999-05-01T00:00:00Zhttp://journals.openedition.org/cybergeo/1240https://doaj.org/toc/1278-3366This paper focuses on the concept of a sustainable city and its theoretical implications for the urban system. Urban sustainability is based on positive interactions among three different urban sub-systems : social, economic and physical, where social well-being coexists with economic development and environmental quality. This utopian scenario doesn’t appear. Affluent economy is often associated with poverty and criminality, labour variety and urban efficiency coexist with pollution and congestion. The research subject is the analysis of local risk and opportunity conditions, based on the application of a special definition of risk elaborated and made operative with the production of a set of maps representing the multidimensional facets of spatial organisation in urban sustainability. The interactions among the economic/social and environmental systems are complex and unpredictable and present the opportunity for a new methodology of scientific investigation : the connectionistic approach, processed by Self-Reflexive Neural Networks (SRNN). These Networks are a useful instrument of investigation and analogic questioning of the Data Base. Once the SRNN has learned the structure of the weights from the DB, by querying the network with the maximization or minimization of specific groups of attributes, it is possible to read the related properties and to rank the areas. The survey scale assumed by the research is purposefully aimed at the micro-scale and concerns the Municipality of Milan which is spatially divided into 144 zones.Lidia DiappiPaola BolchiLorena FranziniUnité Mixte de Recherche 8504 Géographie-citésarticlesustainable cityurban systemneural networksrisk assessmentMilanGeography (General)G1-922DEENFRITPTCybergeo (1999)
institution	DOAJ
collection	DOAJ
language	DE EN FR IT PT
topic	sustainable city urban system neural networks risk assessment Milan Geography (General) G1-922
spellingShingle	sustainable city urban system neural networks risk assessment Milan Geography (General) G1-922 Lidia Diappi Paola Bolchi Lorena Franzini Urban sustainability : complex interactions and the measurement of risk
description	This paper focuses on the concept of a sustainable city and its theoretical implications for the urban system. Urban sustainability is based on positive interactions among three different urban sub-systems : social, economic and physical, where social well-being coexists with economic development and environmental quality. This utopian scenario doesn’t appear. Affluent economy is often associated with poverty and criminality, labour variety and urban efficiency coexist with pollution and congestion. The research subject is the analysis of local risk and opportunity conditions, based on the application of a special definition of risk elaborated and made operative with the production of a set of maps representing the multidimensional facets of spatial organisation in urban sustainability. The interactions among the economic/social and environmental systems are complex and unpredictable and present the opportunity for a new methodology of scientific investigation : the connectionistic approach, processed by Self-Reflexive Neural Networks (SRNN). These Networks are a useful instrument of investigation and analogic questioning of the Data Base. Once the SRNN has learned the structure of the weights from the DB, by querying the network with the maximization or minimization of specific groups of attributes, it is possible to read the related properties and to rank the areas. The survey scale assumed by the research is purposefully aimed at the micro-scale and concerns the Municipality of Milan which is spatially divided into 144 zones.
format	article
author	Lidia Diappi Paola Bolchi Lorena Franzini
author_facet	Lidia Diappi Paola Bolchi Lorena Franzini
author_sort	Lidia Diappi
title	Urban sustainability : complex interactions and the measurement of risk
title_short	Urban sustainability : complex interactions and the measurement of risk
title_full	Urban sustainability : complex interactions and the measurement of risk
title_fullStr	Urban sustainability : complex interactions and the measurement of risk
title_full_unstemmed	Urban sustainability : complex interactions and the measurement of risk
title_sort	urban sustainability : complex interactions and the measurement of risk
publisher	Unité Mixte de Recherche 8504 Géographie-cités
publishDate	1999
url	https://doaj.org/article/ee00cc4e731b42149da1526e29b94614
work_keys_str_mv	AT lidiadiappi urbansustainabilitycomplexinteractionsandthemeasurementofrisk AT paolabolchi urbansustainabilitycomplexinteractionsandthemeasurementofrisk AT lorenafranzini urbansustainabilitycomplexinteractionsandthemeasurementofrisk
_version_	1718396147528105984

Urban sustainability : complex interactions and the measurement of risk

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