Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China
While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/12/10/2784 |
| _version_ | 1797551661811499008 |
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| author | Wenping Xu Lingli Xiang David Proverbs |
| author_facet | Wenping Xu Lingli Xiang David Proverbs |
| author_sort | Wenping Xu |
| collection | DOAJ |
| description | While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources. |
| first_indexed | 2024-03-10T15:49:15Z |
| format | Article |
| id | doaj.art-e6c2dd87990c44cbaed5348b4c861cec |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T15:49:15Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-e6c2dd87990c44cbaed5348b4c861cec2023-11-20T16:13:51ZengMDPI AGWater2073-44412020-10-011210278410.3390/w12102784Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in ChinaWenping Xu0Lingli Xiang1David Proverbs2Evergrande School of Management, Wuhan University of Science and Technology, Wuhan 430065, ChinaEvergrande School of Management, Wuhan University of Science and Technology, Wuhan 430065, ChinaFaculty of Computing, Engineering and the Built Environment, Birmingham City University, Birmingham B4 7BD, UKWhile various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources.https://www.mdpi.com/2073-4441/12/10/2784community resiliencetransient communitiesAHP-BP modelurban floods |
| spellingShingle | Wenping Xu Lingli Xiang David Proverbs Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China Water community resilience transient communities AHP-BP model urban floods |
| title | Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China |
| title_full | Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China |
| title_fullStr | Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China |
| title_full_unstemmed | Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China |
| title_short | Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China |
| title_sort | assessing community resilience to urban flooding in multiple types of the transient population in china |
| topic | community resilience transient communities AHP-BP model urban floods |
| url | https://www.mdpi.com/2073-4441/12/10/2784 |
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