摘要
为了研究强震中波红外热辐射异常变化特征,以风云卫星中波红外资料为基础数据,应用小波变换和功率谱估计方法对6次6.5-7.0级强震进行分析.结果表明：6次强震前3个月内均存在明显的中波红异常变化,功率谱异常偏离年均值和标准差值较大,其异常幅度可达8倍,持续时间为50-105天.异常变化特征具有强震短期预测指标意义,同时可对即将投入实用的高分辨率静止卫星中波红外资料在地震预测中的应用提供重要参考.
In this study,we investigated the medium-wave infrared anomaly characteristics prior to the occurrence of strong earthquakes.We use wavelet transformation and relative power spectrum estimation methods to analyze medium-wave infrared data from an FY stationary meteorological satellite prior to the occurrence of six strong earthquakes with magnitudes of 6.5~7.0.The results show that obvious medium-wave infrared anomalies occurred within three months of the six strong earthquakes.In addition,the relative power spectrum value greatly deviated from the annual average and standard deviation in a 50~105day period.The anomalies of the XinyuanHejing and Lushan earthquakes appeared in a brief period prior to the two earthquakes and continued until they had stopped.In the brief period before the earthquakes,the power spectrum anomaly values increased by a factor of more than eight.The main evolution and peak of the anomalies of the remaining four earthquakes all appeared prior to the earthquakes and their power spectrum anomaly values also increased by a factor of more than eight.The corresponding areas where the anomaly values reached their peaks ranged from several thousands to tens of thousands of square kilometers,and the corresponding periods ranged from 11 to 32days.The relative power spectrum value deviates from the annual average and standard deviation and the period of deviation is more than 50 days.All these characteristics can be easily recognized and used to expediently predict earthquakes.Moreover,the use of high-resolution medium-wave infrared data from key earthquake hazardous areas can provide a reference for seismic prediction.
出处
《地震工程学报》
CSCD
北大核心
2016年第6期977-984,共8页
China Earthquake Engineering Journal
基金
基金项目:高分遥感地震监测与应急应用示范系统(一期)(31~Y30B09~9001~13/15)
关键词
强震
中波红外
异常特征
strong earthquakes
medium-wave infrared
anomaly characteristics
