Assessment of social vulnerability to natural hazards in South Korea: case study for typhoon hazard

2017 ◽  
Vol 25 (1) ◽  
pp. 99-116 ◽  
Author(s):  
Yohana Noradika Maharani ◽  
Sungsu Lee
Keyword(s):  
South Korea ◽  
Natural Hazards ◽  
Social Vulnerability

Identifying urban–rural differences in social vulnerability to natural hazards: a case study of China

2021 ◽  
Author(s):  
Yi Ge ◽  
Wen Dou ◽  
Xiaotao Wang ◽  
Yi Chen ◽  
Ziyuan Zhang
Keyword(s):  
Natural Hazards ◽  
Social Vulnerability ◽  
Urban Rural

scholarly journals Assessment of Spatial Distribution Model of Urban-Social Vulnerability in Natural Hazards (A case study of Seven Municipality of Tehran)

2019 ◽  
Vol 6 (3) ◽  
pp. 49-70
Author(s):  
ABOLFAZL MESHKINI ◽  
ali mohammad mansourzadeh ◽  
zeynab shahrokhy far ◽  
شهربانو موسوی ◽  
◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Natural Hazards ◽  
Social Vulnerability ◽  
Distribution Model ◽  
Spatial Distribution Model

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

2016 ◽  
Vol 16 (6) ◽  
pp. 1387-1399 ◽  
Author(s):  
I. Willis ◽  
J. Fitton
Keyword(s):  
Natural Hazards ◽  
Social Vulnerability ◽  
Disaster Risk Reduction ◽  
Census Data ◽  
Disaster Risk ◽  
Flood Risk Management ◽  
Large Uncertainty ◽  
Highly Sensitive ◽  
Source Data

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.

scholarly journals A review of multivariate social vulnerability methodologies; a case study of the River Parrett catchment, Somerset

2016 ◽  
Author(s):  
I. Willis ◽  
J. Fitton
Keyword(s):  
Natural Hazards ◽  
Social Vulnerability ◽  
Disaster Risk Reduction ◽  
Census Data ◽  
Disaster Risk ◽  
Large Uncertainty ◽  
River Catchment ◽  
Highly Sensitive ◽  
Source Data

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), and 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 Parrett river 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 DRR practitioners.

Developing a model of home-based primary care in South Korea: A 1.5-year case study

2020 ◽  
Vol 40 (6) ◽  
pp. 1403-1428
Author(s):  
Chang-O Kim ◽  
Jongwon Hong ◽  
Mihee Cho ◽  
Eunhee Choi ◽  
Soong-nang Jang
Keyword(s):  
Primary Care ◽  
South Korea ◽  
Home Based Primary Care ◽  
Home Based
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