Volume 12 Issue 1
Dec.  2021
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Article Contents
Xiangxue Zhang, Juan Nie, Changxiu Cheng, Chengdong Xu, Ling Zhou, Shi Shen, Yuan Pei. Natural and Socioeconomic Factors and Their Interactive Effects on House Collapse Caused by Typhoon Mangkhut[J]. International Journal of Disaster Risk Science, 2021, 12(1): 121-130. doi: 10.1007/s13753-020-00322-6
Citation: Xiangxue Zhang, Juan Nie, Changxiu Cheng, Chengdong Xu, Ling Zhou, Shi Shen, Yuan Pei. Natural and Socioeconomic Factors and Their Interactive Effects on House Collapse Caused by Typhoon Mangkhut[J]. International Journal of Disaster Risk Science, 2021, 12(1): 121-130. doi: 10.1007/s13753-020-00322-6

Natural and Socioeconomic Factors and Their Interactive Effects on House Collapse Caused by Typhoon Mangkhut

doi: 10.1007/s13753-020-00322-6

This study was financially supported by the following Grants: National Key Research and Development Plan of China (2019YFA0606901


  • Available Online: 2021-12-25
  • Publish Date: 2021-12-25
  • Typhoons are an environmental threat that mainly affects coastal regions worldwide. The interactive effects of natural and socioeconomic factors on the losses caused by typhoon disasters need further examination. In this study, GeoDetector was used to quantify the determinant powers of natural and socioeconomic factors and their interactive effects on the rate of house collapse in Guangdong and Guangxi Provinces of southeast China caused by Typhoon Mangkhut in 2018. We further identify the dominant factors that influenced the disaster losses. The local indicators of spatial association method was then introduced to explain the spatial heterogeneity of the disaster losses under the influence of the dominant factor. The results indicate that both natural and socioeconomic factors significantly affected the house collapse rate. The maximum precipitation was the dominant factor, with a q value of 0.21, followed by slope and elevation, with q values of 0.17 and 0.13, respectively. Population density and per capita gross domestic product had q values of 0.15 and 0.13, respectively. Among all of the interactive effects of the influencing factors, the interactive effect of elevation and the ratio of brick-wood houses had the greatest influence (q = 0.63) on the house collapse rate. These results can contribute to the formulation of more specific safety and property protection policies.
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