Climate change risk reduction requires cities to undertake urgent decisions. One of the principal obstacles that hinders effective decision making is insufficient spatial knowledge frameworks. Cities climate adaptation planning must become strategic to rethink and transform urban fabrics holistically. Contemporary urban planning should merge future threats with older and unsolved criticalities, like social inequities, urban conflicts and “drosscapes”. Retrofitting planning processes and redefining urban objectives requires the development of innovative spatial information frameworks. This paper proposes a combination of approaches to overcome knowledge production limits and to support climate adaptation planning. The research was undertaken in collaboration with the Metropolitan City of Venice and the Municipality of Venice, and required the production of a multi-risk climate atlas to support their future spatial planning efforts. The developed tool is a Spatial Decision Support System (SDSS), which aids adaptation actions and the coordination of strategies. The model recognises and assesses two climate impacts: Urban Heat Island and Flooding, representing the Metropolitan City of Venice (CMVE) as a case study in complexity. The model is composed from multiple assessment methodologies and maps both vulnerability and risk. The atlas links the morphological and functional conditions of urban fabrics and land use that triggers climate impacts. The atlas takes the exposure assessment of urban assets into account, using this parameter to describe local economies and social services, and map the uneven distribution of impacts. The resulting tool is therefore a replicable and scalable mapping assessment able to mediate between metropolitan and local level planning systems.

Multi-Risk Climate Mapping for the Adaptation of the Venice Metropolitan Area

Maragno, Denis
Writing – Original Draft Preparation
;
Dall’Omo, Carlo Federico;Pozzer, Gianfranco
Formal Analysis
;
Musco, Francesco
Supervision
2021-01-01

Abstract

Climate change risk reduction requires cities to undertake urgent decisions. One of the principal obstacles that hinders effective decision making is insufficient spatial knowledge frameworks. Cities climate adaptation planning must become strategic to rethink and transform urban fabrics holistically. Contemporary urban planning should merge future threats with older and unsolved criticalities, like social inequities, urban conflicts and “drosscapes”. Retrofitting planning processes and redefining urban objectives requires the development of innovative spatial information frameworks. This paper proposes a combination of approaches to overcome knowledge production limits and to support climate adaptation planning. The research was undertaken in collaboration with the Metropolitan City of Venice and the Municipality of Venice, and required the production of a multi-risk climate atlas to support their future spatial planning efforts. The developed tool is a Spatial Decision Support System (SDSS), which aids adaptation actions and the coordination of strategies. The model recognises and assesses two climate impacts: Urban Heat Island and Flooding, representing the Metropolitan City of Venice (CMVE) as a case study in complexity. The model is composed from multiple assessment methodologies and maps both vulnerability and risk. The atlas links the morphological and functional conditions of urban fabrics and land use that triggers climate impacts. The atlas takes the exposure assessment of urban assets into account, using this parameter to describe local economies and social services, and map the uneven distribution of impacts. The resulting tool is therefore a replicable and scalable mapping assessment able to mediate between metropolitan and local level planning systems.
2021
Inglese
13
3
1
32
32
Internazionale
https://www.mdpi.com/2071-1050/13/3/1334
Esperti anonimi
climate multi-risk assessment; climate adaptation planning; Metropolitan City of Venice; GIScience
Article number 1334
no
open
1. Contributo su Rivista::1.1 Articolo su Rivista
info:eu-repo/semantics/article
262
Maragno, Denis; Dall’Omo, Carlo Federico; Pozzer, Gianfranco; Musco, Francesco
4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11578/296847
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