A method for creating high resolution maps of social vulnerability in the context of environmental hazards

Nelson, Katherine S.; Abkowitz, Mark; Camp, Janey

doi:10.1016/j.apgeog.2015.06.011

Cited by 62 publications

(63 citation statements)

References 23 publications

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“…The HSA enables the vulnerability variables to be divided into groups. However, it did not provide information on the relative significance of variables within each group, making it necessary to subsequently perform a PCA (Cutter et al, 2003(Cutter et al, , 2013Fekete, 2009;Nelson et al, 2015;Hummell et al, 2016). Regarding the weighting method used here, although many authors support the idea of assigning the factors equal weight (Chakraborty et al, 2005), it seems reasonable to suppose that not all factors have the same importance in the construction of the ISVI (Brooks et al, 2005;Eakin and Luers, 2006;Liu and Li, 2016), especially when there may be variations in the number of variables forming each factor and their explained variance.…”

Section: Data Sources and Methodologymentioning

confidence: 99%

“…However, not many studies have focused exclusively on the context of flood risk (Tapsell et al, 2002;Burton and Cutter, 2008;Fekete, 2010;Mollah, 2016), and only a very few of these relate to flash floods (Balteanu et al, 2015;Karagiorgos et al, 2016). Overall, in social vulnerability analysis a separate assessment of vulnerability (Tapsell et al, 2002;Cutter et al, 2003;Nelson et al, 2015) and resilience is made (Cutter et al, , 2010Siebeneck et al, 2015). The approach has usually been based on calculating composite indices from socio-demographic and economic characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…However, the social aspects of vulnerability have often been neglected (Cutter et al, 2003;Hummell et al, 2016), mainly due to the difficulty of quantifying variables that are inherently qualitative (Frazier et al, 2014). Social vulnerability tries to explain how a certain natural hazard produces an unequal impact on exposed populations (Cutter et al, 2003;Nelson et al, 2015). It can be characterized by any socioeconomic and demographic variables that influence a society's preparedness, response and recovery (Birkmann, 2013;Cutter et al, 2013;Terti et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Construction of an integrated social vulnerability index in urban areas prone to flash flooding

Aroca‐Jiménez

Pozo

Garcı́a

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Among the natural hazards, flash flooding is the leading cause of weather-related deaths. Flood risk management (FRM) in this context requires a comprehensive assessment of the social risk component. In this regard, integrated social vulnerability (ISV) can incorporate spatial distribution and contribution and the combined effect of exposure, sensitivity and resilience to total vulnerability, although these components are often disregarded. ISV is defined by the demographic and socio-economic characteristics that condition a population's capacity to cope with, resist and recover from risk and can be expressed as the integrated social vulnerability index (ISVI). This study describes a methodological approach towards constructing the ISVI in urban areas prone to flash flooding in Castilla y León (Castile and León, northern central Spain, 94 223 km 2 , 2 478 376 inhabitants). A hierarchical segmentation analysis (HSA) was performed prior to the principal components analysis (PCA), which helped to overcome the sample size limitation inherent in PCA. ISVI was obtained from weighting vulnerability factors based on the tolerance statistic. In addition, latent class cluster analysis (LCCA) was carried out to identify spatial patterns of vulnerability within the study area. Our results show that the ISVI has high spatial variability. Moreover, the source of vulnerability in each urban area cluster can be identified from LCCA. These findings make it possible to design tailor-made strategies for FRM, thereby increasing the efficiency of plans and policies and helping to reduce the cost of mitigation measures.

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Section: Data Sources and Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Construction of an integrated social vulnerability index in urban areas prone to flash flooding

Aroca‐Jiménez

Pozo

Garcı́a

et al. 2017

Nat. Hazards Earth Syst. Sci.

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“…The data to include are constrained by the indicators relevance to the particular hazard(s) being assessed, and whether data are available and current (census data are often the primary data source). As a result, the number and type of vulnerability indicators used within the construction of social vulnerability indices varies considerably depending on the type of analysis and methods used (Nelson et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…a population's social vulnerability, to target mitigation and adaptation strategies at the areas that are both exposed and with high social vulnerability, i.e. the most at risk populations (Nelson et al, 2015;Rygel et al, 2006;Yoon, 2012). An often used method to quantify social vulnerability is based on the "hazards-of-place" model (Cutter et al, 2006) which is a conceptual understanding of how unsafe conditions interact at the local scale to produce a place vulnerability.…”

Section: Introductionmentioning

confidence: 99%

A review of multivariate social vulnerability methodologies: a case study of the River Parrett catchment, UK

Willis

Fitton

2016

Nat. Hazards Earth Syst. Sci.

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Abstract. In the field of disaster risk reduction (DRR), there exists a proliferation of research into different ways to measure, represent, and ultimately quantify a population's differential social vulnerability to natural hazards. Empirical decisions such as the choice of source data, variable selection, and weighting methodology can lead to large differences in the classification and understanding of the "at risk" population. This study demonstrates how three different quantitative methodologies (based on Cutter et al., 2003;Rygel et al., 2006;Willis et al., 2010) applied to the same England and Wales 2011 census data variables in the geographical setting of the 2013/2014 floods of the River Parrett catchment, UK, lead to notable differences in vulnerability classification. Both the quantification of multivariate census data and resultant spatial patterns of vulnerability are shown to be highly sensitive to the weighting techniques employed in each method. The findings of such research highlight the complexity of quantifying social vulnerability to natural hazards as well as the large uncertainty around communicating such findings to stakeholders in flood risk management and DRR practitioners.

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Intersecting Near-Real Time Fluvial and Pluvial Inundation Estimates with Sociodemographic Vulnerability to Quantify a Household Flood Impact Index

Preisser

Passalacqua

Bixler

et al. 2022

Preprint

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A method for creating high resolution maps of social vulnerability in the context of environmental hazards

Cited by 62 publications

References 23 publications

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

A review of multivariate social vulnerability methodologies: a case study of the River Parrett catchment, UK

Intersecting Near-Real Time Fluvial and Pluvial Inundation Estimates with Sociodemographic Vulnerability to Quantify a Household Flood Impact Index

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