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通过电网聚合的移动位置数据对受灾人口流动性的分析:2017年济州州地震,中国
Zezhi Lin1,2, Rui Mao1, Huaiqun Zhao1
1School of National Safety and Emergency Management, Beijing Normal University, Beijing, China.
PloS one
|October 29, 2025
概括
对汇总的移动数据的实证直角函数 (EOF) 分析揭示了Jiuzhaigou地震后的人口外流并确定了疏散路线. 这种方法有效地绘制了灾害影响和人口流动模式.
科学领域:
- 灾害研究研究.
- 地理空间分析是什么?
- 人类流动性的研究研究.
背景情况:
- 个人手机位置数据对于灾害影响评估至关重要,但中国的隐私法规将数据限制在1平方公里的电网上.
- 从聚合的网格数据分析人口移动,由于缺乏个体轨迹信息,因此存在挑战.
- 像BBAC_I集群这样的现有方法可以识别时间趋势,但不能确定特定的冲击区域或疏散方向.
研究的目的:
- 在灾难研究中开发一种分析人口移动模式的方法,使用空间聚合的移动数据.
- 应用经验直角函数 (EOF) 方法来确定2017年济州地震后的人口外流和疏散路线.
- 证明EOF分析优于集群方法的优势,以推断灾害引起的人口动态.
主要方法:
- 实证直角函数 (EOF) 分析应用于灾后手机数据,以1平方公里的分辨率汇总.
- 分析前两个EOF模式 (EOF1和EOF2) 以及它们的主要组件,以解释人口分布变化.
- 根据EOF2.2揭示的空间异常和时间人口转移,确定疏散路线.
主要成果:
- EOF1表明,地震后,Jiuzhaigou山谷的人口流出持续.
- EOF2确定了沿着特定道路的人口增加和Jiuzhaigou山谷的人口减少,这表明了不同的人口再分配模式.
- 据推断,有两个主要的疏散路线:一个是从 Chuanzhusi 镇向西北,另一个是通过 Shuanghe 镇从 Jiuzhaigou 谷向东南.
结论:
- 经验直角函数 (EOF) 分析有效地利用汇总的移动数据来描述人口移动,并确定灾难期间的关键冲击区域.
- EOF分析克服了聚类方法的局限性,通过揭示特定的疏散模式和方向,即使没有个别轨迹数据.
- 该研究强调了EOF在通过移动数据的地理空间分析来增强灾难应对和管理策略方面的潜力.
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