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Spatiotemporal Variations and Risk Analysis of Chinese Typhoon Disasters

doi: 10.3390/su13042278
Typhoons are a product of air-sea interaction, which are often accompanied by high winds, heavy rains, and storm surges. It is significant to master the characteristics and pattern of typhoon activity for typhoon warning and disaster prevention and mitigation. We used the Kernel Density Estimation (KDE) index as the hazard index; the probability of exceeding, or reaching, return period or exceeding a certain threshold was used to describe the probability of hazard occurrence. The results show that the overall spatial distribution of typhoon hazards conforms to a northeast-southwest zonal distribution, decreasing from the southeast coast to the northwest. Across the six typical provinces of China assessed here, data show that Hainan possesses the highest hazard risk. Hazard index is relatively high, mainly distributed between 0.005 and 0.015, while the probability of exceeding a hazard index greater than 0.015 is 0.15. In light of the four risk levels assessed here, the hazard index that accounts for the largest component of the study area is mainly distributed up to 0.0010, all mild hazard levels. Guangdong, Guangxi, Hainan, Fujian, Zhejiang, and Jiangsu as well as six other provinces and autonomous regions are all areas with high hazard risks. The research results can provide important scientific evidence for the sustainable development of China’s coastal provinces and cities. The outcomes of this study may also provide the scientific basis for the future prevention and mitigation of marine disasters as well as the rationalization of related insurance.
- Chinese Academy of Science (中国科学院) China (People's Republic of)
- Aerospace Information Research Institute China (People's Republic of)
- University of Chinese Academy of Sciences China (People's Republic of)
- Chinese Academy of Sciences (中国科学院) China (People's Republic of)
- Chinese Academy of Science (中国科学院) China (People's Republic of)
China, spatiotemporal pattern, Environmental effects of industries and plants, risk analysis, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, typhoon disaster, GE1-350, kernel density estimation
China, spatiotemporal pattern, Environmental effects of industries and plants, risk analysis, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, typhoon disaster, GE1-350, kernel density estimation
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).16 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
