Social vulnerability emphasizes the different burdens of disaster losses within and between places.Although China continuously experiences devastating natural disasters,there is a paucity of research specifically addr...Social vulnerability emphasizes the different burdens of disaster losses within and between places.Although China continuously experiences devastating natural disasters,there is a paucity of research specifically addressing the multidimensional nature of social vulnerability.This article presents an initial study on the social vulnerability of the Yangtze River Delta region in China.The goal is to replicate and test the applicability of the place-based Social Vulnerability Index(SoVI~) developed for the United States in a Chinese cultural context.Twenty-nine variables adapted from SoVI~ were collected for each of the 134 analysis units in the study area.Using principal components analysis,six factors were identified from the variable set:employment and poverty,education,poor housing quality,minorities,family size,and housing size—factors similar to those identified for the United States.Factor scores were summed to get the final SoVI~ scores and the most and least vulnerable study units were identified and mapped.The highest social vulnerability is concentrated in the southern portions of the study area—Jingning,Suichang,Yunhe,Lanxi,Pan’an,and Shengsi.The least socially vulnerable areas are concentrated southwest,west,and northwest of Shanghai.Limitations of replication are discussed along with policy-relevant suggestions for vulnerability reduction and risk mitigation in China.展开更多
Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire country.Social vulnerability highlights differences in the human capa...Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire country.Social vulnerability highlights differences in the human capacity to prepare for, respond to, and recover from disasters. It varies over space and time, and among and between social groups, largely due to differences in socioeconomic and demographic characteristics. This article provides a social vulnerability index(SoVI~) replication study for Brazil and shows how SoVI~concepts and indicators were adapted to the country. SoVI~Brazil follows the place-based framework adopted in the Social Vulnerability Index initially developed for the United States. Using a principal component analysis(PCA), 45city-level indicators were reduced to 10 factors that explain about 67 % of the variance in the data. Clearly identified spatial patterns showed a concentration of the most socially vulnerable cities in the North and Northeast regions of Brazil, as well as the social vulnerability of metropolitan areas and state capitals in the South and Southeast regions.The least vulnerable cities are mainly concentrated in the inland regions of the Southeast. Although different factors contribute to the social vulnerability in each city, the overall results confirm the social and economic disparities among Brazilian’s regions and reflect a differential vulnerability to natural hazards at local to regional scales.展开更多
Evacuation is an effective and commonly taken strategy to minimize death and injuries from an incoming hurricane.For decades,interdisciplinary research has contributed to a better understanding of evacuation behavior....Evacuation is an effective and commonly taken strategy to minimize death and injuries from an incoming hurricane.For decades,interdisciplinary research has contributed to a better understanding of evacuation behavior.Evacuation destination choice modeling is an essential step for hurricane evacuation transportation planning.Multiple factors are identified associated with evacuation destination choices,in which long-term social factors have been found essential,yet neglected,in most studies due to difficulty in data collection.This study utilized long-term human movement records retrieved from Twitter to(1)reinforce the importance of social factors in evacuation destination choices,(2)quantify individual-level familiarity measurement and its relationship with an individual’s destination choice,(3)develop a big data approach for aggregated county-level social distance measurement,and(4)demonstrate how gravity models can be improved by including both social distance and physical distance for evacuation destination choice modeling.展开更多
基金This research was supported jointly by the National Key Basic Research Program of China(973 program)(Grant No.2012CB955404)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.41321001)the Integrated Research on Disaster Risk’s(IRDR)International Centre of Excellence(ICoE)in Vulnerability and Resilience Metrics,at the University of South Carolina.
文摘Social vulnerability emphasizes the different burdens of disaster losses within and between places.Although China continuously experiences devastating natural disasters,there is a paucity of research specifically addressing the multidimensional nature of social vulnerability.This article presents an initial study on the social vulnerability of the Yangtze River Delta region in China.The goal is to replicate and test the applicability of the place-based Social Vulnerability Index(SoVI~) developed for the United States in a Chinese cultural context.Twenty-nine variables adapted from SoVI~ were collected for each of the 134 analysis units in the study area.Using principal components analysis,six factors were identified from the variable set:employment and poverty,education,poor housing quality,minorities,family size,and housing size—factors similar to those identified for the United States.Factor scores were summed to get the final SoVI~ scores and the most and least vulnerable study units were identified and mapped.The highest social vulnerability is concentrated in the southern portions of the study area—Jingning,Suichang,Yunhe,Lanxi,Pan’an,and Shengsi.The least socially vulnerable areas are concentrated southwest,west,and northwest of Shanghai.Limitations of replication are discussed along with policy-relevant suggestions for vulnerability reduction and risk mitigation in China.
文摘Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire country.Social vulnerability highlights differences in the human capacity to prepare for, respond to, and recover from disasters. It varies over space and time, and among and between social groups, largely due to differences in socioeconomic and demographic characteristics. This article provides a social vulnerability index(SoVI~) replication study for Brazil and shows how SoVI~concepts and indicators were adapted to the country. SoVI~Brazil follows the place-based framework adopted in the Social Vulnerability Index initially developed for the United States. Using a principal component analysis(PCA), 45city-level indicators were reduced to 10 factors that explain about 67 % of the variance in the data. Clearly identified spatial patterns showed a concentration of the most socially vulnerable cities in the North and Northeast regions of Brazil, as well as the social vulnerability of metropolitan areas and state capitals in the South and Southeast regions.The least vulnerable cities are mainly concentrated in the inland regions of the Southeast. Although different factors contribute to the social vulnerability in each city, the overall results confirm the social and economic disparities among Brazilian’s regions and reflect a differential vulnerability to natural hazards at local to regional scales.
基金The research is supported by Office of the Vice President for Research,University of South Carolina[grant number 13540-19-49772]and National Science Foundation(NSF)[grant number 2028791].
文摘Evacuation is an effective and commonly taken strategy to minimize death and injuries from an incoming hurricane.For decades,interdisciplinary research has contributed to a better understanding of evacuation behavior.Evacuation destination choice modeling is an essential step for hurricane evacuation transportation planning.Multiple factors are identified associated with evacuation destination choices,in which long-term social factors have been found essential,yet neglected,in most studies due to difficulty in data collection.This study utilized long-term human movement records retrieved from Twitter to(1)reinforce the importance of social factors in evacuation destination choices,(2)quantify individual-level familiarity measurement and its relationship with an individual’s destination choice,(3)develop a big data approach for aggregated county-level social distance measurement,and(4)demonstrate how gravity models can be improved by including both social distance and physical distance for evacuation destination choice modeling.
