{"title":"Analysis of the spatial distribution and future trends of coal mine accidents: A case study of coal mine accidents in China from 2005–2022","authors":"He Yinnan , Qin Ruxiang","doi":"10.1016/j.spasta.2024.100851","DOIUrl":null,"url":null,"abstract":"<div><p>A scientific grasp of the macro law of coal mining accidents can contribute to strengthening their prevention and control and guaranteeing a stable energy supply. In this study, 2,269 investigation reports of China's coal mining accidents from 2005 to 2022 were adopted as the basic data source, and GIS spatial analysis and rescaled range analysis methods were utilized to comprehensively reveal the spatial-temporal distribution features, and evolutionary patterns of coal mining accidents in China. The findings indicate that the numbers of gas explosion, permeability, outburst, suffocation and roof fall accidents has rapidly declined. The coverage area of coal mining accidents has gradually moved toward western of China. However, the center of the area covered by coal mining accidents during the study period was mainly concentrated in Shanxi and Henan Provinces. Besides, the number of deaths resulting from coal mining accidents across the country has gradually decreased, while the time series exhibited high continuity, with future changes consistent with past changes. The average cycle period of the coal mining accident sequence was 5 years. Through the systematic analysis of coal mine accidents conducted in this research, the law of accident occurrence was more comprehensively revealed, providing a reference and basis for the government and enterprises to implement precise preventive measures.</p></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial Statistics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211675324000423","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
A scientific grasp of the macro law of coal mining accidents can contribute to strengthening their prevention and control and guaranteeing a stable energy supply. In this study, 2,269 investigation reports of China's coal mining accidents from 2005 to 2022 were adopted as the basic data source, and GIS spatial analysis and rescaled range analysis methods were utilized to comprehensively reveal the spatial-temporal distribution features, and evolutionary patterns of coal mining accidents in China. The findings indicate that the numbers of gas explosion, permeability, outburst, suffocation and roof fall accidents has rapidly declined. The coverage area of coal mining accidents has gradually moved toward western of China. However, the center of the area covered by coal mining accidents during the study period was mainly concentrated in Shanxi and Henan Provinces. Besides, the number of deaths resulting from coal mining accidents across the country has gradually decreased, while the time series exhibited high continuity, with future changes consistent with past changes. The average cycle period of the coal mining accident sequence was 5 years. Through the systematic analysis of coal mine accidents conducted in this research, the law of accident occurrence was more comprehensively revealed, providing a reference and basis for the government and enterprises to implement precise preventive measures.
期刊介绍：
Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies without methodological development are not acceptable for publication.
Spatial statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of dependence structures, and drawing of valid inference from a limited set of spatio-temporal data.
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