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Where the Streets Have Known Names Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Proposal to Reduce Natural Risks: Analytic Network Process to Evaluate Efficiency of City Planning Strategies

Authors : Roberto De Lotto, Veronica Gazzola, Silvia Gossenberg, Cecilia Morelli di Popolo, Elisabetta Maria Venco

Published in: Computational Science and Its Applications -- ICCSA 2016

Publisher: Springer International Publishing

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Abstract

Natural hazards have greater social and economic impact in urban areas because urbanization and economic development increase people and assets’ concentration in high-risk prone areas: hazards generate risks in relation to population’s exposure and its physical and economic assets.
Advanced urban planning is one of the involved disciplines in the process of human exposure and risks reduction: defining strategic actions, it can reduce losses following natural disasters and, in the same time, ensure a flexible design able to absorb external impacts, to transform and to adapt itself, increasing urban resilience.
The paper defines two possible strategies of intervention in city as risk mitigation methods: Areal Change and Functional Change.
Authors describe the use of scenario planning and Multicriteria evaluation (ANP method) to deepen suitable strategies at urban level. Moreover, authors introduce the first instruments useful for the future application of the presented method: ideal city modeling and evaluation criteria definition.

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Footnotes
1
Disaster is a hazardous event that occurs over a limited time in a defined area.
 
2
Catastrophe is a massive disaster that requires significant expenditure of money and a long time for recovery.
 
3
For each pairwise matrix, it defines: principle normalized eigenvalues; non-weighted supermatrix; weighted supermatrix, limit supermatrix and the alternatives’ ranking.
 
4
Authors choose Pavia (medium sized city located in Northern Italy) to apply the ideal city modeling because it is characterized by the typical elements of European historical cities and it has a database with detailed urban information that authors can easily consult. [30].
 
5
High-density ≥ 6 \( [{{\text{m}^{3} } \mathord{\left/ {\vphantom {{\text{m}^{3} } {\text{m}^{2} }}} \right. \kern-0pt} {\text{m}^{2} }}] \); Medium-density between 2.5 and 6 \( [{{\text{m}^{3} } \mathord{\left/ {\vphantom {{\text{m}^{3} } {\text{m}^{2} }}} \right. \kern-0pt} {\text{m}^{2} }}] \); Low-density ≤ 2.5 \( [{{\text{m}^{3} } \mathord{\left/ {\vphantom {{\text{m}^{3} } {\text{m}^{2} }}} \right. \kern-0pt} {\text{m}^{2} }}] \).
 
6
Data from Pavia Camera di Commercio price list [31].
 
7
Ideals: final normalized judgments in the 0–1 gap; Normals: final normalized judgments related to their sum; Raw: values from priority vector of limit supermatrix.
 
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Metadata
Title
Proposal to Reduce Natural Risks: Analytic Network Process to Evaluate Efficiency of City Planning Strategies
Authors
Roberto De Lotto
Veronica Gazzola
Silvia Gossenberg
Cecilia Morelli di Popolo
Elisabetta Maria Venco
Copyright Year
2016
Book
Computational Science and Its Applications -- ICCSA 2016

Print ISBN: 978-3-319-42088-2

Electronic ISBN: 978-3-319-42089-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-42089-9_46

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