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

Chenchen Yang, Han Zhang, Xunhua Li, Zongyi He and Junli Li ()
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Chenchen Yang: Anhui Agricultural University
Han Zhang: Anhui Agricultural University
Xunhua Li: Central South University
Zongyi He: Wuhan University
Junli Li: Anhui Agricultural University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 118, issue 3, No 5, 1916 pages

Abstract: 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.

Keywords: Natural hazard events; Spatiotemporal scan statistics; Co-occurrence network; FP-growth algorithm (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06097-5

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