TY - GEN
T1 - A GIS-Based Social Vulnerability Assessment of Communities in Coastal Areas Exposed to Extreme Flood Events
T2 - Construction Research Congress 2024, CRC 2024
AU - Rouhanizadeh, Behzad
AU - Safapour, Elnaz
AU - Silwal, Anupa
N1 - Publisher Copyright:
© CRC 2024. All rights reserved.
PY - 2024
Y1 - 2024
N2 - According to statistics, the majority of Louisiana's urban coastal area is low-income, out of which a significant percentage is susceptible to issues dealing with hazards and the relevant consequences. On the other hand, the increasing number of hazards along the Mexican Gulf Coast has become a severe concern for governors. In this study, social vulnerability to extreme floods for New Orleans urban area is evaluated through four phases. The indicators of social vulnerability are identified, and using a statistical analysis process the most important indicators are determined. Also, Social Vulnerability Index (SVI) is estimated and mapped, and the flood risk maps are generated. Finally, by merging the SVI map and the flood map, the social vulnerability exposure map is generated. The results revealed that four key factors that account for 78.60% of the variation in the overall dataset include age (31.3%), urbanization (21.5%), employment status (13.7%), and education level (12.1%). The output of this research can help stakeholders and decision-makers lessen impact of extreme flooding on the social life of vulnerable communities living in coastal areas.
AB - According to statistics, the majority of Louisiana's urban coastal area is low-income, out of which a significant percentage is susceptible to issues dealing with hazards and the relevant consequences. On the other hand, the increasing number of hazards along the Mexican Gulf Coast has become a severe concern for governors. In this study, social vulnerability to extreme floods for New Orleans urban area is evaluated through four phases. The indicators of social vulnerability are identified, and using a statistical analysis process the most important indicators are determined. Also, Social Vulnerability Index (SVI) is estimated and mapped, and the flood risk maps are generated. Finally, by merging the SVI map and the flood map, the social vulnerability exposure map is generated. The results revealed that four key factors that account for 78.60% of the variation in the overall dataset include age (31.3%), urbanization (21.5%), employment status (13.7%), and education level (12.1%). The output of this research can help stakeholders and decision-makers lessen impact of extreme flooding on the social life of vulnerable communities living in coastal areas.
UR - http://www.scopus.com/inward/record.url?scp=85188712753&partnerID=8YFLogxK
U2 - 10.1061/9780784485279.061
DO - 10.1061/9780784485279.061
M3 - Conference article
AN - SCOPUS:85188712753
T3 - Construction Research Congress 2024, CRC 2024
SP - 610
EP - 619
BT - Sustainability, Resilience, Infrastructure Systems, and Materials Design in Construction
A2 - Shane, Jennifer S.
A2 - Madson, Katherine M.
A2 - Mo, Yunjeong
A2 - Poleacovschi, Cristina
A2 - Sturgill, Roy E.
PB - American Society of Civil Engineers (ASCE)
Y2 - 20 March 2024 through 23 March 2024
ER -