Research on the evolution model and characteristics of natural disaster chains in Northwest China
The secondary and derivative effects of natural disasters have significant impacts on the economy and society, making it urgent to research the disaster chains mechanisms. This study utilized web scraping software to collect news reports based on text rules. Through data cleaning, extraction, and en...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2025.2521652 |
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| _version_ | 1849329117009281024 |
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| author | Yongbao Zhang Yao Zhang Yongzhong Sha |
| author_facet | Yongbao Zhang Yao Zhang Yongzhong Sha |
| author_sort | Yongbao Zhang |
| collection | DOAJ |
| description | The secondary and derivative effects of natural disasters have significant impacts on the economy and society, making it urgent to research the disaster chains mechanisms. This study utilized web scraping software to collect news reports based on text rules. Through data cleaning, extraction, and encoding to analyze the evolution model, overall, time, and spatial characteristics of the natural disaster chain in Northwest China. The results indicate that the natural disaster chain in Northwest China can be classified into four evolution models: linear, divergent, centralized, and cross. Different models of disaster chains cause different disaster losses. Rainstorm disasters have the highest concurrency, while low-temperature disasters have the highest continuity. Between 2017 and 2023, there was a trend of increasing and then decreasing numbers of disasters and disaster chains, while the length of disaster chains showed a pattern of decreasing and then increasing. Summer experienced the largest number of disasters and disaster chains, while spring and winter had the longest disaster chain. Gansu and Shanxi are the regions with the highest risk. This study enhances the research findings on disaster chains, which provides decision-making references for disaster risk assessment and emergency management in Northwest China under the framework of big data analysis. |
| format | Article |
| id | doaj-art-aa75480563d349f68daa3d407bcdc6f4 |
| institution | Kabale University |
| issn | 1947-5705 1947-5713 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj-art-aa75480563d349f68daa3d407bcdc6f42025-08-20T03:47:21ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132025-12-0116110.1080/19475705.2025.2521652Research on the evolution model and characteristics of natural disaster chains in Northwest ChinaYongbao Zhang0Yao Zhang1Yongzhong Sha2School of Management, Lanzhou University, Lanzhou, ChinaSchool of Management, Lanzhou University, Lanzhou, ChinaSchool of Management, Lanzhou University, Lanzhou, ChinaThe secondary and derivative effects of natural disasters have significant impacts on the economy and society, making it urgent to research the disaster chains mechanisms. This study utilized web scraping software to collect news reports based on text rules. Through data cleaning, extraction, and encoding to analyze the evolution model, overall, time, and spatial characteristics of the natural disaster chain in Northwest China. The results indicate that the natural disaster chain in Northwest China can be classified into four evolution models: linear, divergent, centralized, and cross. Different models of disaster chains cause different disaster losses. Rainstorm disasters have the highest concurrency, while low-temperature disasters have the highest continuity. Between 2017 and 2023, there was a trend of increasing and then decreasing numbers of disasters and disaster chains, while the length of disaster chains showed a pattern of decreasing and then increasing. Summer experienced the largest number of disasters and disaster chains, while spring and winter had the longest disaster chain. Gansu and Shanxi are the regions with the highest risk. This study enhances the research findings on disaster chains, which provides decision-making references for disaster risk assessment and emergency management in Northwest China under the framework of big data analysis.https://www.tandfonline.com/doi/10.1080/19475705.2025.2521652Natural disastersdisaster chainnews reportevolution modelspatiotemporal characteristics |
| spellingShingle | Yongbao Zhang Yao Zhang Yongzhong Sha Research on the evolution model and characteristics of natural disaster chains in Northwest China Geomatics, Natural Hazards & Risk Natural disasters disaster chain news report evolution model spatiotemporal characteristics |
| title | Research on the evolution model and characteristics of natural disaster chains in Northwest China |
| title_full | Research on the evolution model and characteristics of natural disaster chains in Northwest China |
| title_fullStr | Research on the evolution model and characteristics of natural disaster chains in Northwest China |
| title_full_unstemmed | Research on the evolution model and characteristics of natural disaster chains in Northwest China |
| title_short | Research on the evolution model and characteristics of natural disaster chains in Northwest China |
| title_sort | research on the evolution model and characteristics of natural disaster chains in northwest china |
| topic | Natural disasters disaster chain news report evolution model spatiotemporal characteristics |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2025.2521652 |
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