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[1]ZHENG Chuan,WU Yanmei,JIA Zhaoliang,et al.Rapid Determination of the Direction of the Earthquake-influenced Field in Yunnan Using the Status Information of Communication Base Stations[J].Journal of Seismological Research,2022,45(04):617-625.[doi:10.20015/j.cnki.ISSN1000-0666.2022.0062]

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Rapid Determination of the Direction of the Earthquake-influenced Field in Yunnan Using the Status Information of Communication Base Stations

Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume: 45 Number of periods: 2022 04 Page number: 617-625 Column: Public date: 2022-08-20

Title:: Rapid Determination of the Direction of the Earthquake-influenced Field in Yunnan Using the Status Information of Communication Base Stations

Author(s):: ZHENG Chuan; WU Yanmei; JIA Zhaoliang; CAO Yanbo; XU Ruijie; (Yunnan Earthquake Agency,Kunming 650224,Yunnan,China)

Keywords:: the communication base station; the alarm base station; the Univariate Linear Regression; earthquake-influenced field

CLC:: P315.95

DOI:: 10.20015/j.cnki.ISSN1000-0666.2022.0062

Abstract:: We select the status information of the communication base stations in the earthquake-hit areas of ten M_S≥5.0 earthquakes in Yunnan from 2015 to 2021,and classify these alarm communication base stations according to periods,alarm types,and magnitudes after the earthquake,and use the Univariate Linear Regression method to analyze the status data of these alarm base stations.We perform the linear model regression fitting,and then we determine that the regression direction is the direction of the earthquake-influenced field.The distribution of the fitted influenced field is generally consistent with the distribution of the earthquake intensity area determined by field investigaion.The influenced field direction determined according to the base station giving alarm in 5 minutes after the earhquake is generally applicable.The direction of the influenced field determined by the location information of the deactivated alarm communication base station is closer to the direction of the earthquake intensity area determined by field investigaion.The correlation coefficient R² of the fitted line segment of the alarm base stations data is over 0.75,and the correlation coefficient R² of the fitted line segment of the data from the out-of-service base station is over 0.97.The larger the magnitude of the earthquake,the more the number and the types of alarms of the communication base stations,and the more applicable of the data of the alarm base stations.

References:: 白仙富,戴雨芡,李永强,等.2011.基于余震信息的宏观震中和影响场方向快速判定方法——以云南地区为例[J].地震研究,34(4):525-532.
薄涛,李小军,陈苏,等.2018.基于社交媒体数据的地震烈度快速评估方法[J].地震工程与工程振动,38(5):206-215.
曹彦波,吴艳梅,许瑞杰,等.2017.基于微博舆情数据的震后有感范围提取研究[J].地震研究,40(2):303-310.
冯蔚,刘杰,罗佳宏,等.2015.基于强震和测震数据对鲁甸6.5级地震发震断层方向的研究[J].地震地质,37(1):331-341.
何宗宜,苗静,彭将,等.2015.结合微博数据挖掘的时空特征分析[J].测绘通报,(10):60-64.
胡素平,帅向华.2012.网络地震灾情信息智能处理模型与地震烈度判定方法研究[J].震灾防御技术,7(4):420-430.
李东平,陈海鹏,张凯,等.2019.基于社会视频监控信息源的地震影响范围快速勾画[J].地震研究,42(2):187-195.
李兆隆,吴艳梅,李敏,等.2017.基于互联网信报控制协议的灾情信息获取技术研究与应用[J].地震研究,40(2):311-316.
李志强,袁一凡,李晓丽,等.2008.对汶川地震宏观震中和极震区的认识[J].地震地质,30(3):768-777.
刘经南,方媛,郭迟,等.2014.位置大数据的分析处理研究进展[J].武汉大学学报(信息科学版),39(4):379-385.
聂高众,安基文,邓砚.2012.地震应急灾情服务进展[J].地震地质,34(4):783-789.
任静,阿里木江·亚力昆,李志强,等.2020.2020年1月19日新疆伽师6.4级地震灾害损失快速评估精准性分析[J].震灾防御技术,15(2):349-358.
帅向华,冯蔚,董翔,等.2020.震后分时段地震烈度影响场快速判识方法研究[J].武汉大学学报(信息科学版),45(8):1195-1204.
孙艳萍,张苏平,朱瑞,等.2021.基于余震分析的宏观震中、地震影响场方向和极震区初步修正[J].地震科学进展,51(7):309-314.
汪素云,俞言祥,高阿甲,等.2000.中国分区地震动衰减关系的确定[J].中国地震,16(2):99-106.
王景来,宋志峰.2001.地震灾害快速评估模型[J].地震研究,24(2):162-167.
王晓青,丁香,王龙,等.2009.四川汶川8级大地震灾害损失快速评估研究[J].地震学报,31(2):205-211.
吴艳梅,李兆隆,郑川,等.2019.云南省可定位IP地址数据特征及其在地震有感范围判定中的应用[J].华北地震科学,37(1):1-5.
臧战胜,黄维学,孙国良.2014.通信基站地震破坏等级划分探讨[J].地震工程与工程振动,34(S1):1025-2030.
张方浩,蒋飞蕊,李永强,等.2016.云南地区地震烈度评估模型研究[J].中国地震,32(3):572-583.

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Last Update: 2022-08-01