Climate change is one of the most complex issues of the 21st century, and even though there is general consensus about the urgency of taking action at the city level, the planning and implementation of adaptation measures is advancing slowly. The lack of data and information to support the planning process is often mentioned as a factor hampering the adaptation processes in cities. In this paper, we developed and tested a methodology for heat stress vulnerability and risk assessment at the neighborhood scale to support designers, planners, and decision makers in developing and implementing adaptation strategies and measures at the local level. The methodology combines high-resolution spatial information and crowdsourcing geospatial data to develop sensitivity, adaptive capacity, vulnerability, exposure, and risk indicators. The methodology is then tested on the urban fabric of the city of Padova, Italy. Our results show that dierent vulnerability and risk values correspond to dierent typologies of urban areas. Furthermore, the possibility of combining high-resolution information provided by the indicators and land use categories is of great importance to support the adaptation planning process. We also argue that the methodology is flexible enough to be applied in dierent contexts.

Mapping Heat Stress Vulnerability and Risk Assessment at the Neighborhood Scale to Drive Urban Adaptation Planning

Denis Maragno
Methodology
;
Michele Dalla Fontana;Francesco Musco
Supervision
2020-01-01

Abstract

Climate change is one of the most complex issues of the 21st century, and even though there is general consensus about the urgency of taking action at the city level, the planning and implementation of adaptation measures is advancing slowly. The lack of data and information to support the planning process is often mentioned as a factor hampering the adaptation processes in cities. In this paper, we developed and tested a methodology for heat stress vulnerability and risk assessment at the neighborhood scale to support designers, planners, and decision makers in developing and implementing adaptation strategies and measures at the local level. The methodology combines high-resolution spatial information and crowdsourcing geospatial data to develop sensitivity, adaptive capacity, vulnerability, exposure, and risk indicators. The methodology is then tested on the urban fabric of the city of Padova, Italy. Our results show that dierent vulnerability and risk values correspond to dierent typologies of urban areas. Furthermore, the possibility of combining high-resolution information provided by the indicators and land use categories is of great importance to support the adaptation planning process. We also argue that the methodology is flexible enough to be applied in dierent contexts.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11578/281179
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