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Article(id=1322506628730049064, tenantId=1146029695717560320, journalId=1281212831689347082, issueId=1322506501562937604, articleNumber=null, orderNo=null, doi=10.14075/j.jgg.2025.02.025, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1738684800000, receivedDateStr=2025-02-05, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793239751273, onlineDateStr=2026-10-29, pubDate=1765728000000, pubDateStr=2025-12-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793239751273, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793239751273, creator=13701087609, updateTime=1793239751273, updator=13701087609, issue=Issue{id=1322506501562937604, tenantId=1146029695717560320, journalId=1281212831689347082, year='2025', volume='45', issue='12', pageStart='1211', pageEnd='1316', issueExtLink='null', onlineDate='null', pubDate='1765728000000', pubDateStr='2025-12-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793239720954, creator='13701087609', updateTime=1793239720954, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=1260, endPage=1265, ext={EN=ArticleExt(id=1322506629094953513, articleId=1322506628730049064, tenantId=1146029695717560320, journalId=1281212831689347082, language=EN, title=Extraction of Thermal Infrared Anomalies of the Dingri MS6.8 Earthquake Based on the Weighted Averaging Method, columnId=null, journalTitle=Journal of Geodesy and Geodynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

We analyzed the Dingri MS6.8 earthquake as a case study. A multivariate dataset comprising land surface temperature, net surface solar radiation, and other variables in the study area was constructed. After decomposing the time series of each variable, the generalized extreme studentized deviate(GESD) algorithm was applied to extract anomaly signals. The weighted averaging method was then employed to integrate multi-variable anomaly extraction results. The results indicate that the thermal infrared anomalies in the half-year period before the Dingri MS6.8 earthquake exhibited a cyclic change pattern of "emergence-enhancement-weakening". The Dingri MS6.8 earthquake occurred 100 days after the maximum value of the anomalies appeared, and the main direction of the anomalies was NW-SE, forming an approximately 45° angle with the Dengmo Co fault, which is the seismogenic structure of this earthquake.

, authors=Ainiwaer YIERPAN1, Yisimayili AISA1, *, Anhe ZHANG1, Bahedawulieti HU'ANNIXI1, authorsList=Ainiwaer YIERPAN, Yisimayili AISA, Anhe ZHANG, Bahedawulieti HU'ANNIXI, authorCompany=null, correspAuthors=Yisimayili AISA, authorNote=

YIERPAN Ainiwaer, assistant engineer, majors in earthquake analysis and forecast, E-mail:

, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322506634392359480, articleId=1322506628730049064, tenantId=1146029695717560320, journalId=1281212831689347082, language=CN, title=基于加权平均法提取定日MS6.8地震热红外异常, columnId=1322506193558422163, journalTitle=大地测量与地球动力学, columnName=地震地质, runingTitle=null, highlight=null, articleAbstract=

以定日MS6.8地震为例，构建研究区地表温度、表面净太阳辐射等多变量数据集，对各变量数据集进行时间序列分解后，利用GESD(generalized extreme studentized deviate)算法提取异常信息，最后使用加权平均法集成多变量的异常提取结果并进行分析。结果表明，定日MS6.8地震震前半年的热红外异常呈现“出现-增强-减弱”的周期性变化特征；定日MS6.8地震发生在异常出现最大值后的第100天，且异常的主方向为NW-SE，与此次地震的发震构造登么错断裂约呈45°夹角。

, authors=伊尔潘·艾尼瓦尔1, 艾萨·伊斯马伊力1, *, 张桉赫1, 胡安尼西·巴合达吾列提1, authorsList=伊尔潘·艾尼瓦尔, 艾萨·伊斯马伊力, 张桉赫, 胡安尼西·巴合达吾列提, authorCompany=null, correspAuthors=艾萨·伊斯马伊力, authorNote=

伊尔潘·艾尼瓦尔，助理工程师，主要从事地震分析预报研究，E-mail:

, correspAuthorsNote=

艾萨·伊斯马伊力，高级工程师，主要从事地震电磁学与地震预测预报研究, E-mail:

AISA Yisimayili, senior engineer, majors in seismoelectromagnetism and earthquake forecast, E-mail:

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YIERPAN Ainiwaer, assistant engineer, majors in earthquake analysis and forecast, E-mail:

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YIERPAN Ainiwaer, assistant engineer, majors in earthquake analysis and forecast, E-mail:

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伊尔潘·艾尼瓦尔，助理工程师，主要从事地震分析预报研究，E-mail:

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伊尔潘·艾尼瓦尔，助理工程师，主要从事地震分析预报研究，E-mail:

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基于加权平均法提取定日MS6.8地震热红外异常
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伊尔潘·艾尼瓦尔 1 , 艾萨·伊斯马伊力 1, * , 张桉赫 1 , 胡安尼西·巴合达吾列提 1
大地测量与地球动力学 | 地震地质 2025,45(12): 1260-1265
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大地测量与地球动力学 |地震地质 2025 , 45 (12) : 1260 -1265
基于加权平均法提取定日MS6.8地震热红外异常
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伊尔潘·艾尼瓦尔1 , 艾萨·伊斯马伊力1, * , 张桉赫1, 胡安尼西·巴合达吾列提1
作者信息
  • 1 新疆维吾尔自治区地震局, 乌鲁木齐市科学二街338号, 830011
通讯作者:

艾萨·伊斯马伊力，高级工程师，主要从事地震电磁学与地震预测预报研究, E-mail:

AISA Yisimayili, senior engineer, majors in seismoelectromagnetism and earthquake forecast, E-mail:

作者简介:

伊尔潘·艾尼瓦尔，助理工程师，主要从事地震分析预报研究，E-mail:

Extraction of Thermal Infrared Anomalies of the Dingri MS6.8 Earthquake Based on the Weighted Averaging Method
Ainiwaer YIERPAN1 , Yisimayili AISA1, * , Anhe ZHANG1, Bahedawulieti HU'ANNIXI1
Affiliations
  • 1 Earthquake Agency of Xinjiang Uygur Autonomous Region, 338 Second-Kexue Street, Urumqi 830011, China

    • YIERPAN Ainiwaer, assistant engineer, majors in earthquake analysis and forecast, E-mail:

出版时间: 2025-12-15 doi: 10.14075/j.jgg.2025.02.025
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摘要
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以定日MS6.8地震为例，构建研究区地表温度、表面净太阳辐射等多变量数据集，对各变量数据集进行时间序列分解后，利用GESD(generalized extreme studentized deviate)算法提取异常信息，最后使用加权平均法集成多变量的异常提取结果并进行分析。结果表明，定日MS6.8地震震前半年的热红外异常呈现“出现-增强-减弱”的周期性变化特征；定日MS6.8地震发生在异常出现最大值后的第100天，且异常的主方向为NW-SE，与此次地震的发震构造登么错断裂约呈45°夹角。

定日MS6.8地震  /  热红外异常  /  GESD算法  /  加权平均法

We analyzed the Dingri MS6.8 earthquake as a case study. A multivariate dataset comprising land surface temperature, net surface solar radiation, and other variables in the study area was constructed. After decomposing the time series of each variable, the generalized extreme studentized deviate(GESD) algorithm was applied to extract anomaly signals. The weighted averaging method was then employed to integrate multi-variable anomaly extraction results. The results indicate that the thermal infrared anomalies in the half-year period before the Dingri MS6.8 earthquake exhibited a cyclic change pattern of "emergence-enhancement-weakening". The Dingri MS6.8 earthquake occurred 100 days after the maximum value of the anomalies appeared, and the main direction of the anomalies was NW-SE, forming an approximately 45° angle with the Dengmo Co fault, which is the seismogenic structure of this earthquake.

Dingri MS6.8 earthquake  /  thermal infrared anomaly  /  GESD algorithm  /  weighted averaging method
伊尔潘·艾尼瓦尔, 艾萨·伊斯马伊力, 张桉赫, 胡安尼西·巴合达吾列提. 基于加权平均法提取定日MS6.8地震热红外异常. 大地测量与地球动力学, 2025 , 45 (12) : 1260 -1265 . DOI: 10.14075/j.jgg.2025.02.025
Ainiwaer YIERPAN, Yisimayili AISA, Anhe ZHANG, Bahedawulieti HU'ANNIXI. Extraction of Thermal Infrared Anomalies of the Dingri MS6.8 Earthquake Based on the Weighted Averaging Method[J]. Journal of Geodesy and Geodynamics, 2025 , 45 (12) : 1260 -1265 . DOI: 10.14075/j.jgg.2025.02.025
正文
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准确提取地震前的热红外异常信息对地震预测具有重要的科学意义。国内外学者通过大量震例研究提出了相对功率谱[1-2]、RST[3-4]、偏移指数[5]等多种热红外异常提取算法。这些异常提取方法均在大量强震例研究中体现出了较好的异常提取效果，对热红外异常具有敏感性且具备定量呈现异常强度变化的优点，为同类型的研究提供了较好的参考。但现阶段多数研究使用单一类型的热参量数据，无法全面反映地震前的热异常模式。部分研究尝试使用多个变量的异常信息进行综合分析，但缺乏对不同结果的集成处理。
加权平均作为常见的集成方法之一[6]，可应用于多种变量异常信息的集成分析。本文以西藏定日MS6.8地震为例，使用加权平均法对地表温度、表面净太阳辐射、表面净热辐射、2 m高度气温、感热通量等多个变量的异常信息进行集成。通过综合不同数据源的信息，旨在更准确地提取和分析地震前的热异常规律，为热红外技术在地震预测中的应用提供新的思路和方法。
1 研究区概况和数据源
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2025-01-07西藏自治区日喀则市定日县(87.45°E，28.50°N)发生MS6.8地震，震源深度10 km。研究区位于青藏高原腹地，平均海拔超过5 km(图 1)。此次地震发震构造是近南北走向的登么错断裂，为申扎-定结断裂带南段规模较大的地堑之一，隶属于藏南拆离系断裂，是青藏高原内部重要的近南北向伸展构造。该区域地震活动性强，多发生正断层型错动[7-8]。
2 研究方法
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2.1 时间序列分解
地表温度、表面净太阳辐射、表面净热辐射等数据具有明显的季节和趋势特征，这些特征可能会对热红外异常信息提取产生一定的干扰，使用时间序列分解去除数据集的季节和趋势项[9]。
$Y_t=T_t+S_t+R_t$
式中，Tt和St为趋势成分和季节性成分，可通过局部加权回归提取；Rt为残差成分，可用原始序列减去Tt和St得到。以上计算过程通过Python编程语言中的Statsmodels库来完成。
2.2 GESD算法
GESD算法即泛化版Grubbs检验，该算法的核心就是比较异常指数Gi与临界值λi之间的大小，当Gi>λi时，该点为异常点[9]。
$G_i=\frac{\left|x_i-\bar{x}\right|}{\sigma}$
$\lambda_i=\frac{(n-1) t_{n-i-1, p}}{\sqrt{(n-i-1)\left(n-i-1+t_{n-i-1, p}^2\right)}}$
式中，${\bar x}$为数据集的均值；σ为标准差；n为离散点的数量；tn-i-1, p为(n-i-1)自由度的t分布双侧尾部概率为p时的值。
2.3 加权平均法
加权平均法通过对不同数据集结果赋予不同的权重值来过滤伪异常信息，从而得出综合的提取结果。皮尔森相关系数可衡量2个变量之间线性关系的强度[10]，若相关系数呈现中等及以上程度相关，说明2组数据具有较好的线性关系。本文将不同变量上提取的异常指数与对应变量数据之间的皮尔森相关系数作为各变量的权重进行加权平均计算，获取最终的结果[6]。
$H(x)=\frac{h_1 w_1+h_2 w_2 \cdots h_4 w_4+h_n w_n}{w_1+w_2 \cdots w_4+w_n}$
式中，hn为不同变量上提取出的异常指数；wn为各变量的权重。
3 结果与分析
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3.1 定日MS6.8地震热异常的空间变化过程
对研究区2020-01-01—2025-01-09的地表温度、表面净太阳辐射、表面净热辐射等5种变量进行时间序列分解后，利用GESD算法提取各变量异常指数，计算各异常指数与对应变量之间的皮尔森相关系数，利用加权平均法将5种数据集的提取结果进行综合集成。
图 2为研究区各变量异常指数与对应变量之间皮尔森相关系数的空间分布，其中地表温度数据集中的震中东西两侧和西北部察仓-德来断裂附近区域相关系数大于0.4，呈现中等程度的相关性。表面净太阳辐射数据集中，研究区多数区域呈现中等程度相关。表面净热辐射数据集中，在震中附近沿藏南拆离系断裂带和申扎-定结断裂带均有呈现中等程度相关的区域。2 m高度气温数据集中，相关系数相比其他变量较低。感热通量数据集中，震中西北和以东区域呈现中等程度的相关性。总结图 2结果可知，多数变量的相关系数沿活动断裂分布，呈现中等程度及以上相关，相关系数可作为权重用于加权平均计算集成各变量异常指数。
图 3为定日MS6.8地震震前6个月加权平均计算后热红外异常空间分布情况，由图可知，2024-07-01研究区震中以北和西南方向出现的热异常区域均距离震中较远。大约1周后，震中附近热异常明显，且震中以北、西、西南3个方向异常区域增多，2024-07-11—16研究区热异常逐渐减弱。2024-07-21震中西北部再次出现热异常区域，至2024-08-10异常区域明显增加。2024-08-15—09-03研究区热异常活动减弱，2024-09-08震中以南、西出现少量异常区域，往后直至2024-09-28研究区热异常面积达到最大值。2024-10-03—18热异常再次逐渐减弱，2024-10-23—11-02震中以南、东南方向热异常逐渐发展，并在2024-11-07之后逐渐减弱，2024-11-27震中以南沿藏南拆离系断裂带方向出现明显热异常。2024-12-02—22研究区热异常较弱，发震前1周震中西南方向出现异常区域，发震当日震中附近热异常也较为明显，震后减弱。分析研究区热异常的空间分布，本次地震的震前热异常变化大致呈现为“出现-增强-减弱”的交替过程。
图 4为部分时间各变量异常提取结果，从图中可以看出，不同变量显示的异常信息存在一定的差异，利用加权平均法可对不同结果进行集成，得到综合的异常信息。2024-07-16的提取结果中，部分数据集中提取到了距离震中较远的异常信息，通过加权平均后，对应区域未显示异常，说明加权平均法可对异常信息进行一定的筛选。2024-09-28是震前半年异常达到最大值的时间，研究区大部分区域被识别为异常，由图 2可知，表面净太阳辐射的相关系数较高(大于0.3)，加权平均后，异常信息受表面净太阳辐射变量结果影响较大，但也基本符合热异常发生在震中及断裂带附近大尺度区域的观点[5]。2024-11-27地表温度、2 m高度气温数据的提取结果中，震中以北、东北较远位置显示异常，通过加权平均后，距离震中较远的异常像元被去除，异常结果更多地集中在震中以南并具有明显的方向特征。而2025-01-09地表温度和2 m高度气温数据的结果中，震中位置提取到了明显且具有方向特征的异常信息，但在加权平均后信息被弱化。通过查看图 2中对应变量的相关系数结果，发现该区域地表温度和2 m高度气温的相关系数呈不相关或弱相关(相关系数0.1~0.3)，且其他数据集相关系数较大，因此加权平均后异常信息被弱化。
3.2 热异常的方向特征及时间变化特征
为分析此次地震热异常的主方向，以震中为中心，将研究区划分为16个方向区域，分别为N、NNE、NE、NEE、E、SEE、SE、SSE、S、SSW、SW、SWW、W、NWW、NW、NNW。统计各变量震前6个月内不同方向的异常像元数绘制雷达图，如图 5(像元数单位：100个)所示。
统计结果显示，热异常的主方向主要为NW-SE(图 5(f))，与此次地震的发震构造登么错断裂走向大致呈45°夹角，该区域构造力学环境以NNW-SSE向挤压为主，与热异常的主方向近似。除地表温度外的其他变量统计的主方向为NW-SE和NNW-SSE(图 5(b)~5(e))，地表温度为NE-SW(图 5(a))，再次说明不同变量提取到的异常信息具有差异性，加权平均法能对其进行综合集成。
图 6为研究区2024-07-01—2025-01-09加权平均后异常像元数的统计情况。可以看出，研究区热红外异常整体发展趋势近似“出现-增强-消失”的过程，且大致以30 d为周期交替变化。2024-07—08、2024-08—09异常变化幅度相对较弱，2024-09-15—10-10异常变化相对剧烈，2024-09-28达到顶峰。2024-10-15之后，异常依然重复“出现-增强-消失”的变化过程，但幅度较弱。定日MS6.8地震发生在异常达到最大值后的第100天左右，基本符合异常达到最大值后的十几天至半年内是发震可能时段的观点。
4 讨论
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本研究通过加权平均法对不同数据源的异常信息进行集成，得到了定日MS6.8地震前的热红外异常信息。分析定日MS6.8地震的热红外异常方向，发现此次地震的异常主方向为NW-SE。徐秀登等[11]提出，地壳中的既存断层和大震前岩层破裂均可能为震前地壳中的热能转移提供通道，从而导致地面热红外震兆的出现。铁永波等[12]指出，本次地震发生区域的构造力学环境以NNW-SSE挤压为主，这与本研究统计出的热异常主方向近似。说明强震前的热红外异常主方向可能与区域构造活动的受力方向有一定的空间关联。
张铁宝等[13]研究巴颜喀拉块体中东段MS≥7.0地震红外辐射时序变化特征时指出，该区域的红外异常呈现阶段性的“增强-减弱”变化。本文研究区与巴颜喀拉块体中东段邻近，且本次地震震前的热红外异常也近似呈现周期性的“出现-增强-减弱”变化。阶段性的辐射“增强-减弱”变化可能反映区域应力的变化过程[13]，目前有多种机理[11]解释地震红外异常现象，由于构造环境、地形等因素的影响，地震红外异常可能是多种模式综合作用的结果。
分析部分时间各数据集异常结果(图 4)发现，通过加权平均对多种变量的异常信息进行集成后，可以对一些与震中及断裂带不具有较好空间对应关系的异常像元进行弱化，降低对相关规律总结的干扰。利用加权平均法对多种热参量数据集中提取到的异常结果进行集成，相比单一类型热参量数据的提取结果可提升一定的稳定性。部分数据集提取到的与震中位置具有较好空间对应关系的异常信息，在加权平均后被弱化，主要原因是该位置异常指数与对应变量之间相关系数较低。因此，如何确定合理的权重值，提高异常信息的准确性是今后研究的问题之一。
综上所述，本研究通过对定日MS6.8地震前热红外异常的提取与分析，验证了多变量加权平均在强震热红外异常研究中的可行性。但由于地理、气候和构造环境的复杂性，未来还需结合更多震例研究和集成不同异常提取算法，来优化热红外异常的提取方法。
5 结语
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1) 定日MS6.8地震震前半年的热红外异常呈现周期性的“出现-增强-减弱”变化。
2) 定日MS6.8地震发生在热异常出现最大值后的第100天，且异常的主方向为NW-SE，与此次地震的发震构造登么错断裂约呈45°夹角。
3) 本文提出的对多个变量热异常结果进行加权平均的方法，能有效融合不同变量提取的异常信息，获取综合的结果。相比单一类型变量的异常提取，该方法可在一定程度上提升结果的可靠性。
基金
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  • 新疆地震青年科学基金(202504)
  • 新疆维吾尔自治区自然科学基金(2022D03031)
  • 中国地震局地震科技星火计划(XH24008D)
  • 中国地震局震情跟踪课题(CEA-ZQGZ-202501056)
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2025年第45卷第12期
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doi: 10.14075/j.jgg.2025.02.025
  • 接收时间：2025-02-05
  • 首发时间：2026-10-29
  • 出版时间：2025-12-15
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  • 收稿日期：2025-02-05
基金
Xinjiang Earthquake Youth Science Foundation(202504)
新疆地震青年科学基金(202504)
Naural Science Foundation of Xinjiang Uygur Autonomous Region(2022D03031)
新疆维吾尔自治区自然科学基金(2022D03031)
The Spark Program of Earthquake Technology of CEA(XH24008D)
中国地震局地震科技星火计划(XH24008D)
Seismic Regime Tracking Project of CEA(CEA-ZQGZ-202501056)
中国地震局震情跟踪课题(CEA-ZQGZ-202501056)
作者信息
    1 新疆维吾尔自治区地震局, 乌鲁木齐市科学二街338号, 830011

通讯作者:

艾萨·伊斯马伊力，高级工程师，主要从事地震电磁学与地震预测预报研究, E-mail:

AISA Yisimayili, senior engineer, majors in seismoelectromagnetism and earthquake forecast, E-mail:

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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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