Social and economic vulnerability of coastal communities to sea-level rise and extreme flooding

Felsenstein, Daniel; Lichter, Michal

doi:10.1007/s11069-013-0929-y

Cited by 88 publications

(43 citation statements)

References 37 publications

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“…A number of vulnerability indices integrate elements of social vulnerability with physical vulnerability in the context of specific coastal hazards, for example, hurricanes and storm surge (Rygel et al 2006;Bjarnadottir et al 2011), tsunamis (Wood et al 2010), marine oil spills (Santos et al 2013), coastal erosion (McLaughlin andCooper 2010), loss of coastal wetlands due to urbanization (Huang et al 2012), and coastal flooding and sea-level rise (Wu et al 2002;Balica et al 2012;Felsenstein and Lichter 2014).…”

Section: Vulnerability and Risk Indicatorsmentioning

confidence: 99%

“…Some studies have developed vulnerability indicators at neighborhood or smaller spatial scales, such as census blocks (e.g., Wood et al 2010;Oulahen et al 2015). Felsenstein and Lichter (2014) aggregated household-level data to the community level, which enabled an analysis of intracommunity differentials across subpopulations in the hazard zones. McLaughlin and Cooper (2010) explored coastal vulnerability indices at national, local, and site levels; they noted that index development should consider spatial scales appropriate to the hazard, to data availability, and to management decisions.…”

Section: Vulnerability and Risk Indicatorsmentioning

confidence: 99%

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Using vulnerability indicators to develop resilience networks: a similarity approach

et al. 2015

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This paper proposes a new approach to developing and utilizing vulnerability indicators, which is based on the concept of similarity. Methods for assessing the disaster vulnerability of communities through quantitative indices are established in research and practice. They are typically used to identify which cities or other spatial units are most susceptible to losses from storms, floods, and other hazards; however, their utility for taking action to reduce vulnerability has been found to be limited. In contrast, the method developed here quantifies vulnerability profiles for purposes of identifying places that are similarly vulnerable. Such an approach can facilitate sharing of knowledge, resources, and successful practices that are relevant to a particular community's circumstances. The approach is demonstrated in a preliminary application to coastal communities in British Columbia, Canada.

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Section: Vulnerability and Risk Indicatorsmentioning

confidence: 99%

Section: Vulnerability and Risk Indicatorsmentioning

confidence: 99%

Using vulnerability indicators to develop resilience networks: a similarity approach

et al. 2015

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“…snow, and snowfall), provided by the Korean Ministry of the Interior and Safety (MOIS). Not only precipitation, but also the frequency of natural disasters, are significant natural environment aspects affecting the degree of disaster damage [2,29,34,[48][49][50]. The third indicator was the extent of open space, meaning the green tract of land as a percentage of total land.…”

Section: Independent Variablesmentioning

confidence: 99%

Examining Vulnerability Factors to Natural Disasters with a Spatial Autoregressive Model: The Case of South Korea

Jeong

Yoon

2018

Sustainability

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Socially and economically marginalized people and environmentally vulnerable areas are disproportionately affected by natural hazards. Identifying populations and places vulnerable to disasters is important for disaster management, and crucial for mitigating their economic consequences. From the fields of geography, emergency management, and urban planning, several approaches and methodologies have been used to identify significant vulnerability factors affecting the incidence and impact of disasters. This study performs a regression analysis to examine several factors associated with disaster damage in 230 local communities in South Korea, using ten vulnerability indicators for social, economic, and environmental aspects, and a single indicator for disaster characteristics. A Lagrange Multiplier diagnostic test-based spatial autoregressive model (SAM) was applied to assess the potential spatial autocorrelation in the ordinary least squares (OLS) residuals. This study compared the OLS regression results with those of a spatial autoregressive model, for both presence of spatial autocorrelation, and model performance. The conclusion of this study is that Korean communities with a higher vulnerability to disasters, as a result of their socioeconomic and environmental characteristics, are more likely to experience economic losses from natural disasters.

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“…Based on a literature review (Tapsell et al 2002;Cutter et al 2003;Fekete 2009;Felsenstein and Lichter 2014); we selected in total 11 variables (Table 5) to assess the social vulnerability of residents in East Attica. The variables mainly focus to the two aspects of (1) local embeddedness, such as family and friends living in the communities, members of local associations or local social networks and (2) socio-economic characteristics, such as employment rate or educational background, with particular focus on the consequences and impacts of the current social and economic crises in Greece.…”

Section: Social Vulnerabilitymentioning

confidence: 99%

Multi-vulnerability analysis for flash flood risk management

et al. 2016

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Vulnerability assessment implies a quantitative evaluation of the individual vulnerability components such as elements at risk, their physical exposure and social characteristics. Current approaches in vulnerability research are driven by a divide between social scientists who tend to view vulnerability as representing a set of socio-economic factors, and scientists who view vulnerability in terms of the degree of loss to an element at risk. To close this gap, a multi-dimensional vulnerability analysis has been undertaken focusing on flash flood hazards in Greece. To represent physical vulnerability, an empirical relation between the process intensity and the degree of loss was established. With respect to social vulnerability, an assessment was undertaken by means of empirical data collection based on a door-to-door survey. In general, both physical and social vulnerability was comparable low, which is interpreted as a result from (a) specific building regulations in Greece as well as general design principles leading to less structural susceptibility of elements at risk exposed, and (b) a relatively low economic loss leading to less social vulnerability of citizens exposed. It is shown that a combination of different perspectives of vulnerability will lead to a better understanding of perceptions of actors regarding their vulnerabilities and capacities.

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Social and economic vulnerability of coastal communities to sea-level rise and extreme flooding

Cited by 88 publications

References 37 publications

Using vulnerability indicators to develop resilience networks: a similarity approach

Using vulnerability indicators to develop resilience networks: a similarity approach

Examining Vulnerability Factors to Natural Disasters with a Spatial Autoregressive Model: The Case of South Korea

Multi-vulnerability analysis for flash flood risk management

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