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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Main Authors: Lidia Diappi, Paola Bolchi, Lorena Franzini
Format: Article
Language:deu
Published: Unité Mixte de Recherche 8504 Géographie-cités 1999-05-01
Series:Cybergeo
Subjects:
Online Access:http://journals.openedition.org/cybergeo/1240
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spelling doaj-ee00cc4e731b42149da1526e29b946142021-10-05T13:16:20ZdeuUnité Mixte de Recherche 8504 Géographie-citésCybergeo1278-33661999-05-0110.4000/cybergeo.1240Urban sustainability : complex interactions and the measurement of riskLidia DiappiPaola BolchiLorena FranziniThis 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.http://journals.openedition.org/cybergeo/1240sustainable cityurban systemneural networksrisk assessmentMilan
collection DOAJ
language deu
format Article
sources DOAJ
author Lidia Diappi
Paola Bolchi
Lorena Franzini
spellingShingle Lidia Diappi
Paola Bolchi
Lorena Franzini
Urban sustainability : complex interactions and the measurement of risk
Cybergeo
sustainable city
urban system
neural networks
risk assessment
Milan
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
series Cybergeo
issn 1278-3366
publishDate 1999-05-01
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.
topic sustainable city
urban system
neural networks
risk assessment
Milan
url http://journals.openedition.org/cybergeo/1240
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AT lorenafranzini urbansustainabilitycomplexinteractionsandthemeasurementofrisk
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