地震前后遥感数据异常分析
发布时间：2018-12-14 05:03
【摘要】：卫星红外遥感数据的震前异常是进行地震预测预警探索的一种有效辅助信息,其相关研究成为近年来的研究热点之一。本文针对已有的震前红外异常研究方法中存在缺乏大量震例验证和多种红外遥感数据综合应用的缺陷,循序渐进地提出三种异常分析算法,并采用实震进行验证。主要研究工作包括：1、针对CUSUM算法能检测统计过程中均值的微小变化,本文提出基于CUSUM算法的射出长波辐射(OLR)数据(1°×1°)地震异常分析算法。首先,以样本观察值数据序列均值为期望的均值近似计算累积和；其次,采用局部平滑方法对累积和进行平滑；第三,利用局部最大值和最小值构造特征曲线；最后采用双阈值控制法进行异常检测。汶川地震和阿根廷地震的实验结果表明,此算法能有效地检测出地震前后的异常,具体表现为：震前,异常度由小及大,在地震前后异常度达到最大,地震结束后,异常度逐渐减小。2、提出基于小波和短时傅里叶变换的平均功率谱地震异常分析算法。算法假设2.5°x2.5°的OLR数据构成为加性模型,采用“db8”小波挖掘隐藏在OLR数据中与地震密切相关的成分,并利用短时傅里叶变换分析其相关的频谱特性,提出特定频率范围的频谱平均值作为地震异常分析的依据。对国内外11个≥7.0的强震进行实验分析,实验结果表明：地震前后异常特征表现为上升-维持-下降的形态。3、针对震前红外异常研究中缺乏多种红外遥感数据综合分析的问题,提出了基于随机漫步的异常分析算法。将分辨率为2.5°x2.5°的OLR数据和NCEP/NCAR再分析资料的表面温度数据、潜在温度数据和压力数据结合起来,综合对8个2008-2013年国内外≥8.0的强震进行实验分析。统计随机漫步结果中大于2倍方差的强度、位置与天数,并进行四种数据对比。实验结果表明,8个地震中每个地震至少都有两种数据存在同步的大于2倍方差的异常,且异常基本都出现在震前2周内。
[Abstract]:The pre-earthquake anomaly of satellite infrared remote sensing data is an effective auxiliary information for earthquake prediction and early warning exploration, and its related research has become one of the research hotspots in recent years. In view of the defects of the existing methods of infrared anomaly research before earthquakes, which lack a large number of seismic examples and comprehensive application of various infrared remote sensing data, three anomaly analysis algorithms are proposed step by step and verified by real earthquakes. The main research work is as follows: 1. Aiming at the small change of mean value in the statistical process detected by CUSUM algorithm, this paper proposes an algorithm for seismic anomaly analysis based on CUSUM algorithm for emitting long wave radiation (OLR) data (1 掳脳 1 掳). Firstly, the cumulative sum is approximately calculated by the mean value of the data sequence of the sample observation value; secondly, the cumulative sum is smoothed by the local smoothing method; thirdly, the characteristic curve is constructed by using the local maximum value and the minimum value. Finally, the double threshold control method is used to detect anomalies. The experimental results of the Wenchuan earthquake and the Argentine earthquake show that the algorithm can effectively detect the anomalies before and after the earthquake. The results show that the anomaly degree changes from small to large before and after the earthquake, and the anomaly degree reaches the maximum before and after the earthquake. The anomaly degree decreases gradually. 2. An average power spectrum seismic anomaly analysis algorithm based on wavelet transform and short time Fourier transform (STFT) is proposed. The algorithm assumes that 2.5 掳x 2.5 掳OLR data is an additive model, uses "db8" wavelet to mine the components closely related to earthquakes in OLR data, and analyzes its related spectral characteristics by using short time Fourier transform (STFT). The average frequency spectrum in a specific frequency range is proposed as the basis for seismic anomaly analysis. The experimental results of 11 strong earthquakes 鈮，
本文编号：2377974
[Abstract]:The pre-earthquake anomaly of satellite infrared remote sensing data is an effective auxiliary information for earthquake prediction and early warning exploration, and its related research has become one of the research hotspots in recent years. In view of the defects of the existing methods of infrared anomaly research before earthquakes, which lack a large number of seismic examples and comprehensive application of various infrared remote sensing data, three anomaly analysis algorithms are proposed step by step and verified by real earthquakes. The main research work is as follows: 1. Aiming at the small change of mean value in the statistical process detected by CUSUM algorithm, this paper proposes an algorithm for seismic anomaly analysis based on CUSUM algorithm for emitting long wave radiation (OLR) data (1 掳脳 1 掳). Firstly, the cumulative sum is approximately calculated by the mean value of the data sequence of the sample observation value; secondly, the cumulative sum is smoothed by the local smoothing method; thirdly, the characteristic curve is constructed by using the local maximum value and the minimum value. Finally, the double threshold control method is used to detect anomalies. The experimental results of the Wenchuan earthquake and the Argentine earthquake show that the algorithm can effectively detect the anomalies before and after the earthquake. The results show that the anomaly degree changes from small to large before and after the earthquake, and the anomaly degree reaches the maximum before and after the earthquake. The anomaly degree decreases gradually. 2. An average power spectrum seismic anomaly analysis algorithm based on wavelet transform and short time Fourier transform (STFT) is proposed. The algorithm assumes that 2.5 掳x 2.5 掳OLR data is an additive model, uses "db8" wavelet to mine the components closely related to earthquakes in OLR data, and analyzes its related spectral characteristics by using short time Fourier transform (STFT). The average frequency spectrum in a specific frequency range is proposed as the basis for seismic anomaly analysis. The experimental results of 11 strong earthquakes 鈮，
本文编号：2377974
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