Adaptive Disaster Risk Assessment (e-bog) af Pena, Neiler Medina
Pena, Neiler Medina (forfatter)

Adaptive Disaster Risk Assessment e-bog

802,25 DKK (inkl. moms 1002,81 DKK)
Climate change, combined with the rapid and often unplanned urbanisation trends, is associated with a rising trend in the frequency and severity of disasters triggered by natural hazards. In order to face the impacts of such threats, it is necessary to have an appropriate Disaster Risk Assessment (DRA). Traditional DRA approaches for disaster risk reduction (DRR) have focused mainly on the haza...
E-bog 802,25 DKK
Forfattere Pena, Neiler Medina (forfatter)
Forlag CRC Press
Udgivet 8 oktober 2021
Længde 312 sider
Genrer KNBW
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781000542820
Climate change, combined with the rapid and often unplanned urbanisation trends, is associated with a rising trend in the frequency and severity of disasters triggered by natural hazards. In order to face the impacts of such threats, it is necessary to have an appropriate Disaster Risk Assessment (DRA). Traditional DRA approaches for disaster risk reduction (DRR) have focused mainly on the hazard component of risk, with little attention to the vulnerability and the exposure components. To address this issue, this dissertation's main objective is to develop and test a disaster risk modelling framework that incorporates socioeconomic vulnerability and the adaptive nature of exposure associated with human behaviour in extreme hydro-meteorological events in the context of SIDS. To achieve the objective, an Adaptive Disaster Risk Assessment (ADRA) framework is proposed. ADRA uses an index-based approach (PeVI) to assess the socioeconomic vulnerability using three components: susceptibility, lack of coping capacities, and lack of adaptation. Furthermore, ADRA explicitly incorporates the exposure component using two approaches; first, a logistic regression model was built using the actual evacuation rates observed during Hurricane Irma, and second, an Agent-based model is used to simulate how households change their exposure levels in relation to different sources of information