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Article

A Method for Assessing Flood Vulnerability Based on Vulnerability Curves and Online Data of Residential Buildings—A Case Study of Shanghai

1
School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
2
Shanghai Emergency Management and Chemicals Registration Center, Shanghai 200020, China
3
Resource and Environment College, Anhui Science and Technology University, Chuzhou 233100, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Petr Rapant
Water 2022, 14(18), 2840; https://doi.org/10.3390/w14182840
Received: 1 August 2022 / Revised: 1 September 2022 / Accepted: 7 September 2022 / Published: 12 September 2022
(This article belongs to the Special Issue Advance in Flood Risk Management and Assessment Research)
Flood vulnerability is the key to understanding and assessing flood risk. However, analyzing flood vulnerability requires sophisticated data, which is usually not available in reality. With the widespread use of big data in cities today, it is possible to quickly obtain building parameters in cities on a large scale, thus offering the possibility to study the risk flooding poses to urban buildings. To fill this research gap, taking Shanghai as an example, this study developed a new research framework to assess urban vulnerability based on vulnerability curves and online data of residential buildings. First, detailed information about residential buildings was prepared via web crawlers. Second, the cleaned residential building information fed a support vector machine (SVM) algorithm to classify the buildings into four flood vulnerability levels that represented the vulnerability curves of the four building types. Third, the buildings of different levels were given vulnerability scores by accumulating the depth–damage ratios across the possible range of flood depth. Further, combined with the unit price of houses, flood risk was assessed for residential buildings. The results showed that the F1-score for the classification of buildings was about 80%. The flood vulnerability scores were higher in both the urban center and the surrounding areas and lower between them. Since 1990, the majority of residential buildings in Shanghai have switched from masonry–concrete structures to steel–concrete structures, greatly reducing the vulnerability to floods. The risk assessment showed decreasing risk trend from the center outward, with the highest risk at the junction of the Huangpu, Jing’an and Xuhui districts. Therefore, this framework can not only identify the flood vulnerability patterns but also provide a clue for revealing the flood risk of residential buildings. With real estate data becoming increasingly accessible, this method can be widely applied to other cities to facilitate flood vulnerability and risk assessment. View Full-Text
Keywords: building structure; vulnerability curve; support vector machines; flood risk; damage assessment building structure; vulnerability curve; support vector machines; flood risk; damage assessment
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MDPI and ACS Style

Li, Z.; Wang, L.; Shen, J.; Ma, Q.; Du, S. A Method for Assessing Flood Vulnerability Based on Vulnerability Curves and Online Data of Residential Buildings—A Case Study of Shanghai. Water 2022, 14, 2840. https://doi.org/10.3390/w14182840

AMA Style

Li Z, Wang L, Shen J, Ma Q, Du S. A Method for Assessing Flood Vulnerability Based on Vulnerability Curves and Online Data of Residential Buildings—A Case Study of Shanghai. Water. 2022; 14(18):2840. https://doi.org/10.3390/w14182840

Chicago/Turabian Style

Li, Zhuoxun, Liangxu Wang, Ju Shen, Qiang Ma, and Shiqiang Du. 2022. "A Method for Assessing Flood Vulnerability Based on Vulnerability Curves and Online Data of Residential Buildings—A Case Study of Shanghai" Water 14, no. 18: 2840. https://doi.org/10.3390/w14182840

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