体育与科学

低空体育旅游作为“低空运动+旅游”深度融合的新形态，是体育经济发展的新亮点，但频发的安全事件严重制约低空体育旅游的健康发展。本文利用季节强度指数、地理集中指数、不平衡指数、标准差椭圆等研究方法，分析2015—2024年中国低空体育旅游安全事件时空分布特征，阐释低空体育旅游安全事件的空间聚集规律和发展态势，同时运用Apriori算法，通过分析安全事件因素属性的关联性，探索安全事件的关键致因。结果表明：(1)低空体育旅游安全事件数量呈现“M”型渐进式上升趋势，每年4月、5月和10月是安全事件的高发期，具有显著的季节性波动和集中性突发特征；(2)低空体育旅游安全事件主要分布于经济发展水平高或低空体育旅游资源丰富的地区，发生区域不均衡，呈现“小集聚、大分散”的空间分布格局，不利于区域风险防控与应急处置；(3)低空体育旅游安全事件共有5大类因素属性、59小类具体属性指标，通过SPSS Modeler软件得出事件关联的频繁项集共19个，获得以事件等级为关联前项的27条强关联规则数据，人员操作失误、机械/设备故障、天气意外、非法飞行和地面保障不完善是中国低空体育旅游各级安全事件的关键致因。本文认为，应通过建设系统化安全发展政策、科学化法律规范体系、精细化安全管理制度、数智化安全保障系统、职业化安全培训体系等方式提升低空体育旅游安全保障水平。

Low-altitude sports tourism, as a new form of deep integration of “low-altitude sports and tourism”, is a new highlight of sports economy development. However, frequent safety accidents seriously restrict the safe and healthy development of low-altitude sports tourism. In this paper, seasonal intensity index, geographical concentration index, imbalance index, standard deviation ellipse, and other research methods are used to analyze the spatial and temporal distribution characteristics of low-altitude sports tourism safety incidents in China from 2015 to 2024, and explain the spatial aggregation law and development trend of low-altitude sports tourism safety incidents. The application uses network graph and Apriori algorithm for data mining to find the correlation between security incidents through the combination of frequent factors. The results show that:(1) The number of low-altitude sports tourism safety incidents in China presents an “M” shaped gradual upward trend, and the time distribution has significant seasonal fluctuations. April, May and October are the most frequent periods of safety incidents;(2) safety incidents in low-altitude sports tourism are mainly concentrated in areas with high economic development or abundant low-altitude sports tourism resources. The occurrence is unevenly distributed, showing a spatial pattern of “small clusters, large dispersion”, which is not conducive to regional regulation for risk prevention and emergency response;(3) there are 5 categories of factor attributes and 59 sub-categories of specific attribute indicators for domestic low-altitude sports tourism safety incidents. SPSS Modeler software is used to obtain a total of 19 frequent item sets of event association, and 27 strong association rule data with event level as the first item are obtained. Personnel operational errors, mechanical/equipment failures, unexpected weather, illegal flights, and inadequate ground support are key triggering factors of low-altitude sports tourism safety incidents at all classes in China. This paper argues that safety protection in low-altitude sports tourism should be improved through systematic safety development policies, scientific legal regulatory framework, refined safety management systems, intelligent safety assurance systems, and professional safety training programs.