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Yongsheng Yang
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4 records found
1
In this study, we collected the data of 172 typhoon storm surge disasters that occurred in China during 1983–2018 to show the temporal and spatial distribution of their frequency and damage. Our results indicated that: (1) there was an increase in the frequency of typhoons storm surge disasters during 1983–2018, and 98% of these disasters occurred from June to October; (2) the damage decreased over time, especially after 1997; (3) the frequency and damage caused by typhoon storm surge disasters were higher in the southern and eastern regions than in the northern regions; (4) Guangdong, Fujian, and Zhejiang experienced the highest disaster occurreneces and damages, and the number of disaster occurrences and damages in these three regions accounted for approximately 57% and 80% of the total disaster occurrences and damages, respectively. Furthermore, we mainly analyzed the spatiotemporal characteristics of typhoon storm surge disasters from three aspects: contributors and damage records of extreme typhoon storm surge disasters, mitigation measures, and tropical cyclone tracks. These findings and analyses can help disaster managers improve their understanding of typhoon storm surge disasters and strengthen protection in disaster hotspots and sensitive months.
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In this study, we collected the data of 172 typhoon storm surge disasters that occurred in China during 1983–2018 to show the temporal and spatial distribution of their frequency and damage. Our results indicated that: (1) there was an increase in the frequency of typhoons storm surge disasters during 1983–2018, and 98% of these disasters occurred from June to October; (2) the damage decreased over time, especially after 1997; (3) the frequency and damage caused by typhoon storm surge disasters were higher in the southern and eastern regions than in the northern regions; (4) Guangdong, Fujian, and Zhejiang experienced the highest disaster occurreneces and damages, and the number of disaster occurrences and damages in these three regions accounted for approximately 57% and 80% of the total disaster occurrences and damages, respectively. Furthermore, we mainly analyzed the spatiotemporal characteristics of typhoon storm surge disasters from three aspects: contributors and damage records of extreme typhoon storm surge disasters, mitigation measures, and tropical cyclone tracks. These findings and analyses can help disaster managers improve their understanding of typhoon storm surge disasters and strengthen protection in disaster hotspots and sensitive months.
Typhoon storm surge disasters have garnered much attention because of their catastrophic damages. We investigated spatiotemporal patterns of typhoon storm surge disasters based on their tropical cyclone track clusters to support disaster mitigation in China. We aggregated 172 typhoon storm surge disasters in the entire cluster. Then, we used the extended Finite-Mixture-Model to categorize these 172 disasters into three clusters according to their track clusters (westward, northward, and westward shift at the coastline). In general, not all temporal distributions of the frequency and damage showed significant trends in the entire cluster and three clusters from 1983–2018. Between 1983‒2000 and 2001‒2018, the average annual frequency increased, and average annual direct economic loss and average annual fatalities decreased in the entire cluster. Although most temporal patterns in the three clusters were similar to those in the entire cluster, a positive growth ratio in the average annual direct economic loss was apparent between 1983‒2000 and 2001‒2018 in Cluster 3. For spatial patterns, southern and eastern regions were more affected by typhoon storm surge disasters than northern regions. In northern regions, Cluster 2 recorded the most disaster occurrences, direct economic losses, and fatalities. Track characteristics and mitigation measures were introduced to help understand disaster spatiotemporal patterns in the entire cluster and three clusters.
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Typhoon storm surge disasters have garnered much attention because of their catastrophic damages. We investigated spatiotemporal patterns of typhoon storm surge disasters based on their tropical cyclone track clusters to support disaster mitigation in China. We aggregated 172 typhoon storm surge disasters in the entire cluster. Then, we used the extended Finite-Mixture-Model to categorize these 172 disasters into three clusters according to their track clusters (westward, northward, and westward shift at the coastline). In general, not all temporal distributions of the frequency and damage showed significant trends in the entire cluster and three clusters from 1983–2018. Between 1983‒2000 and 2001‒2018, the average annual frequency increased, and average annual direct economic loss and average annual fatalities decreased in the entire cluster. Although most temporal patterns in the three clusters were similar to those in the entire cluster, a positive growth ratio in the average annual direct economic loss was apparent between 1983‒2000 and 2001‒2018 in Cluster 3. For spatial patterns, southern and eastern regions were more affected by typhoon storm surge disasters than northern regions. In northern regions, Cluster 2 recorded the most disaster occurrences, direct economic losses, and fatalities. Track characteristics and mitigation measures were introduced to help understand disaster spatiotemporal patterns in the entire cluster and three clusters.
Predicting the spatial distribution of direct economic losses from typhoon storm surge disasters is crucial for supporting emergency response efforts. Using case-based reasoning, we developed a preliminary method for completing predictions about the impact of typhoon storm surge disasters for multiple coastal regions. We proposed retrieval, reuse, and revision algorithms to predict the following effects of a typhoon storm surge disaster: total direct economic losses and their grades, the affected regions, and individual direct economic losses and their grades in each affected region. We tested 33 such disaster cases using the developed method, and the predicted results were as follows. In about 70% of the cases, all recorded affected regions were predicted; the grades of the total direct economic losses were accurate in over 70% of the cases; in 63% of the cases, the grades of direct economic losses in each affected region were partly accurate, and they were all accurate in 30% of the cases. These promising results suggest that the proposed method can support disaster managers to respond adequately to typhoon storm surge disasters for multiple coastal regions.
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Predicting the spatial distribution of direct economic losses from typhoon storm surge disasters is crucial for supporting emergency response efforts. Using case-based reasoning, we developed a preliminary method for completing predictions about the impact of typhoon storm surge disasters for multiple coastal regions. We proposed retrieval, reuse, and revision algorithms to predict the following effects of a typhoon storm surge disaster: total direct economic losses and their grades, the affected regions, and individual direct economic losses and their grades in each affected region. We tested 33 such disaster cases using the developed method, and the predicted results were as follows. In about 70% of the cases, all recorded affected regions were predicted; the grades of the total direct economic losses were accurate in over 70% of the cases; in 63% of the cases, the grades of direct economic losses in each affected region were partly accurate, and they were all accurate in 30% of the cases. These promising results suggest that the proposed method can support disaster managers to respond adequately to typhoon storm surge disasters for multiple coastal regions.
In China, storm surge disasters cause severe damages in coastal regions. One of the most critical tasks is to predict affected regions and their relative damage levels to support decision-making. This study develops a two-stage retrieval model to search the most similar past disaster case to complete prediction. Based on spatial attributes of cases, the top-ranking past cases with a similar location to the target case are selected. Among these past cases, the most similar past case is selected by disaster attribute similarities. Three typical storm surge case studies have been used and implemented into this proposed model, and the results show that all the most affected regions can be predicted. The proposed model simplifies the prediction process and updates results quickly. This study provides valuable information for the government to make real-time response plans.
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In China, storm surge disasters cause severe damages in coastal regions. One of the most critical tasks is to predict affected regions and their relative damage levels to support decision-making. This study develops a two-stage retrieval model to search the most similar past disaster case to complete prediction. Based on spatial attributes of cases, the top-ranking past cases with a similar location to the target case are selected. Among these past cases, the most similar past case is selected by disaster attribute similarities. Three typical storm surge case studies have been used and implemented into this proposed model, and the results show that all the most affected regions can be predicted. The proposed model simplifies the prediction process and updates results quickly. This study provides valuable information for the government to make real-time response plans.