基于LST年趋势背景场的地震热异常提取算法

doi:10.3969/j.issn.0253-4967.2016.03.014

地震地质 ›› 2016, Vol. 38 ›› Issue (3): 680-695.DOI: 10.3969/j.issn.0253-4967.2016.03.014

基于LST年趋势背景场的地震热异常提取算法

宋冬梅¹, 臧琳^1,2, 单新建³, 袁媛⁴, 崔建勇¹, 邵红梅⁵, 沈晨⁵, 时洪涛^1,2

1 中国石油大学(华东)地球科学与技术学院, 青岛 266580;
2 中国石油大学(华东)研究生院, 青岛 266580;
3 中国地震局地质研究所, 北京 100029;
4 上海市地震局, 上海 200062;
5 中国石油大学(华东)理学院, 青岛 266580

收稿日期:2016-02-04 修回日期:2016-06-07 出版日期:2016-09-20 发布日期:2016-10-15
通讯作者: 臧琳,女,硕士研究生,E-mail:18765920116@163.com
作者简介:宋冬梅,女,1973年生,2003年于中国科学院沈阳应用生态研究所获理学博士学位,副教授,研究方向为地震热红外异常信息提取,电话:0532-86985091,E-mail:songdongmei1973@126.com。
基金资助:
地震动力学国家重点实验室开放基金（LED2012B02）与上海市科学技术委员会项目（14231202600）共同资助

A STUDY ON THE ALGORITHM FOR EXTRACTING EARTHQUAKE THERMAL INFRARED ANOMALIES BASED ON THE YEARLY TREND OF LST

SONG Dong-mei¹, ZANG Lin^1,2, SHAN Xin-jian³, YUAN Yuan⁴, CUI Jian-yong¹, SHAO Hong-mei⁵, SHEN Chen⁵, SHI Hong-tao^1,2

1 School of Geosciences, China University of Petroleum, Qingdao 266580, China;
2 Graduate School, China University of Petroleum, Qingdao 266580, China;
3 Institute of Geology, China Earthquake Administration, Beijing 100029, China;
4 Shanghai Earthquake Administration, Shanghai 200062, China;
5 College of Science, China University of Petroleum, Qingdao 266580, China

Received:2016-02-04 Revised:2016-06-07 Online:2016-09-20 Published:2016-10-15

摘要/Abstract

摘要：

地震发生前普遍存在的热红外辐射异常现象，是当前评估区域发震危险性的重要参数之一。然而，并非所有的地表红外异常都与构造活动或地震有关，如何排除非构造因素对地表热红外辐射的影响，从强噪声背景中提取微弱信号，是当前利用热红外遥感技术研究构造活动的难点。地表温度（LST）背景场是热异常提取的基础，而以往研究中所建立的背景场不能有效反映当年气候变化对其的影响，造成热异常提取精度受限。为此，文中在提取热异常的过程中对背景场进行了改进，结合地表温度时间序列的周期性特征，引入谐波分析，采用傅里叶逼近的方法拟合地表温度离散时序，从中提取其年趋势，建立1个动态的、同时包含局地信息和年际特征的、更加可靠的地表温度背景场；将其引入RST模型，基于“kσ”准则识别地震热异常信息；最终采用异常方向、异常强度和距离指数这3个指标对异常结果进行分析，验证算法的有效性。利用MODIS地表温度产品，基于所提算法对2008年汶川地震进行了再研究，结果表明：1）汶川地震前存在明显的热异常，沿龙门山断裂呈带状分布，持续时间较长；2）发震期无明显的异常现象；3）震后热异常的发生具有循环往复性，但异常幅度和影响范围明显缩小。与传统的空间温度均值RST算法异常提取结果相比，文中方法所提取的热异常在空间分布上与活动断裂带更为吻合，对异常的产生消散过程刻画更加细致，表明以地表温度年趋势作为地震构造热异常提取的背景场更加可靠。

关键词: 地震热异常, 地表温度背景场, 傅里叶逼近, 年趋势, 汶川地震

Abstract:

There are thermal infrared anomalies(TIA)before earthquake, and TIA has become one of the important parameters for assessing regional earthquake risk. However, not all of the surface infrared anomalies are related to tectonic activities or earthquakes. How to eliminate the influence of non-structural factors and extract the weak signals from strong disturbances is the key and difficult point for tectonic activities studies based on the thermal infrared remote sensing techniques. Land surface temperature(LST)background field is the basis for thermal infrared anomalies extraction. However, the established background fields in previous researches cannot eliminate the influence of climate changes, so the accuracy of thermal anomaly extraction is limited. Now an improved method is proposed. Combined with the periodic character of LST time series, harmonic analysis is lead into the process of LST background field establishment. Specifically, the yearly trend of LST is fitted based on Fourier Approximation method. As a new background field, the yearly trend is dynamic, includes the local and the yearly information. Then, based on the rule of "kσ", the earthquake anomalies, calculated by RST with the yearly trend of LST, can be extracted. At last, the effectiveness of the algorithm can be tested by the quantitative analysis of anomalies with anomaly area statistics, anomaly intensity statistics and distance index statistics. The Wenchuan earthquake was discussed again based on the proposed algorithm with MODIS land temperature products in 2008. The results show that, there were obvious pre-earthquake thermal anomalies along the Longmen Mountains faults with a longer time; but there were no anomalies when the earthquake happened; and the post-earthquake thermal anomalies occurred with much smaller amplitudes and scopes. Compared with the results derived from the traditional RST which is based on the spatial average of LST values, the TIA extracted by the new RST, which is based on the yearly trend of LST, is more fit with the active faults, and the process of the anomalies occurring and removing can be described in more detail. Therefore, as the background field to extract earthquake anomalies, the yearly trend of LST is more reliable.

Key words: earthquake thermal anomalies, LST background field, Fourier Approximation, the yearly trend, Wenchuan earthquake

中图分类号:

P315.72⁺8

宋冬梅, 臧琳, 单新建, 袁媛, 崔建勇, 邵红梅, 沈晨, 时洪涛. 基于LST年趋势背景场的地震热异常提取算法[J]. 地震地质, 2016, 38(3): 680-695.

SONG Dong-mei, ZANG Lin, SHAN Xin-jian, YUAN Yuan, CUI Jian-yong, SHAO Hong-mei, SHEN Chen, SHI Hong-tao. A STUDY ON THE ALGORITHM FOR EXTRACTING EARTHQUAKE THERMAL INFRARED ANOMALIES BASED ON THE YEARLY TREND OF LST[J]. SEISMOLOGY AND GEOLOGY, 2016, 38(3): 680-695.

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基于LST年趋势背景场的地震热异常提取算法

A STUDY ON THE ALGORITHM FOR EXTRACTING EARTHQUAKE THERMAL INFRARED ANOMALIES BASED ON THE YEARLY TREND OF LST

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