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Analysis of spatial and temporal characteristics of major natural disasters in China from 2008 to 2021 based on mining news database

Author

Listed:
  • Chenchen Yang

    (Anhui Agricultural University
    Central South University)

  • Han Zhang

    (Anhui Agricultural University)

  • Xunhua Li

    (Central South University)

  • Zongyi He

    (Wuhan University)

  • Junli Li

    (Anhui Agricultural University)

Abstract

Globally, China is among the countries most severely affected by natural disasters. Understanding the spatial and temporal distribution characteristics of natural hazard events on a spatial and temporal scale can help understand natural hazard risks more comprehensively. However, there remains a lack of research on spatiotemporal clustering relationship analysis of multi-hazard natural disasters and the co-occurrence relationship between different natural hazard events and spatial locations. In this study, we obtained the geographic text of natural disaster events in China from 2008 to 2021 mined from news, extracted the spatiotemporal information of natural disaster types and situations, and introduced the theory of spatiotemporal scanning statistics and co-occurrence network relationships. The results showed that (1) information on the location, time, and intensity of attention to disaster events contained in news data is highly correlated with the actual occurrence of disasters. The spatial and temporal characteristics of disasters differ among regions, and 15 natural disasters have high-risk clustering areas with log-likelihood ratio values up to 1016.77 and relative risk values up to 46.95. Seasonal differences exist in the occurrences of different natural disasters, with most occurring frequently from May to August. (2) The association rules mining disaster events show that distinct co-occurrence relationships between several hazards are present, and the confidence level of the most frequent item number sets was above 95%. Regardless of meteorological, hydrological, and geological hazards, these interconnected regions were geographically close, and most regions in the spatial association centers of natural hazards were closely connected, showing a pattern of multiple low-frequency regions linked to one high-frequency region, with the strongest connection in southern China, with a frequency of 360, and the weakest connection in Northeast and Northwest China, with a frequency of only single digits. This study can provide a reference for relevant departments to identify natural disaster risks in different regions, formulate disaster risk zoning, and improve their disaster prevention and control capabilities.

Suggested Citation

  • Chenchen Yang & Han Zhang & Xunhua Li & Zongyi He & Junli Li, 2023. "Analysis of spatial and temporal characteristics of major natural disasters in China from 2008 to 2021 based on mining news database," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(3), pages 1881-1916, September.
    • Handle: RePEc:spr:nathaz:v:118:y:2023:i:3:d:10.1007_s11069-023-06097-5
    DOI: 10.1007/s11069-023-06097-5
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    1. Han Woo Park, 2018. "YouTubers’ networking activities during the 2016 South Korea earthquake," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(3), pages 1057-1068, May.
    2. Martin Kulldorff, 2001. "Prospective time periodic geographical disease surveillance using a scan statistic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 61-72.
    3. Shuolin Geng & Qi Zhou & Mingjie Li & Dianxing Song & Yanjun Wen, 2021. "Spatial–temporal differences in disaster perception and response among new media users and the influence factors: a case study of the Shouguang Flood in Shandong province," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 2241-2262, January.
    4. Hiroki Noguchi & Takuma Nishizawa & Masaaki Fuse, 2021. "A method to characterize the social cascading damage processes of disasters using media information," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(1), pages 231-247, May.
    5. Junli Li & Wenjun Wu & Xinxin Ye & Hao Jiang & Ruijie Gan & Heli Wu & Jinglei He & Yuelin Jiang, 2019. "Innovative trend analysis of main agriculture natural hazards in China during 1989–2014," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(3), pages 677-720, February.
    6. Myles R. Allen & William J. Ingram, 2002. "Constraints on future changes in climate and the hydrologic cycle," Nature, Nature, vol. 419(6903), pages 224-232, September.
    7. Robert Eyre & Flavia De Luca & Filippo Simini, 2020. "Social media usage reveals recovery of small businesses after natural hazard events," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    8. Li, Xianghua & Wang, Zhen & Gao, Chao & Shi, Lei, 2017. "Reasoning human emotional responses from large-scale social and public media," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 182-193.
    9. Pierre Desrochers, 2001. "Cities and Industrial Symbiosis: Some Historical Perspectives and Policy Implications," Journal of Industrial Ecology, Yale University, vol. 5(4), pages 29-44, October.
    10. Clarissa C David & Jonathan Corpus Ong & Erika Fille T Legara, 2016. "Tweeting Supertyphoon Haiyan: Evolving Functions of Twitter during and after a Disaster Event," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-19, March.
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