HVSR方法用于地震作用下场地效应分析的适用性研究

以美国Garner Valley Downhole Array(GVDA)竖向观测台阵的强震观测记录为基础,利用水平与竖向谱比(Horizontal-to-Vertical Spectral Ratio,HVSR)方法与传统谱比方法研究了多次地震作用下竖向台阵场地的波动传播规律,探讨了该场地HVSR曲线与传递函数(Transfer Function,TF)曲线的差异,综合利用频域求解一维层状场地P、SV波入射情况下场地响应的土层地震反应分析方法和合成理论地震图的波数积分法解释了二者差异可能的原因,在此基础上研究了HVSR方法应用于地震作用下场地效应分析的适用性.研究结论表明:竖向地震动场地效应是HVSR与传递函数产生差异的主要原因,竖向地震动场地效应主要是由竖向地震动中的P波成分引起的.在场地竖向放大可以忽略的频段范围内,HVSR可以作为传递函数研究地震作用下的场地效应.     

Illumination effects on the differenced Normalized Burn Ratio's optimality for assessing fire severity

The influence of illumination effects on the optimality of the dNBR (differenced Normalized Burn Ratio) was evaluated for the case of the 2007 Peloponnese (Greece) wildfires using a pre/post-fire Landsat TM (Thematic Mapper) image couple. Well-illuminated pixels (south and south-east facing slopes) exhibited more optimal displacements in the bi-spectral feature space than more shaded pixels (north and north-west exposed slopes). Moreover, pixels experiencing a small image-to-image difference in illumination obtained a higher optimality than pixels with a relatively large difference in illumination. To correct for illumination effects, the c-correction method and a modified c-correction technique were applied. The resulting median dNBR optimality of uncorrected, c-corrected and modified c-correction data was respectively 0.58, 0.60 and 0.71 (differences significant for p < 0.001). The original c-correction method improved the optimality of badly illuminated pixels while deteriorating the optimality of well-illuminated pixels. In contrast, the modified c-correction technique improved the optimality of all the pixels while retaining the prime characteristic of topographic correction techniques, i.e. detrending the illumination–reflectance relationship. For a minority of the data, for shaded pixels and/or pixels with a high image-to-image difference in illumination, the original c-correction outperformed the modified c-correction technique. In this study conducted in rugged terrain and with a bi-temporal image acquisition scheme that deviated up to two months from the ideal anniversary date scheme the modified c-correction technique resulted in a more reliable change detection.     

2019年6月17日长宁MS6.0地震前地震活动和水位的加卸载响应比异常研究

加卸载响应比（LURR）方法是通过固体潮加卸载过程中的某一物理参数的响应差异探查区域应力场演化。本文将这一方法应用于2019年6月17日四川长宁M_S6.0地震,根据LURR时序演化探查震源区介质的应力状态变化,提取可能的震前异常信息。首先采用贝尼奥夫应变作为响应量计算LURR,通过固体潮在地震断层面的最优滑动方向上引起的库仑破坏应力变化来判断加载还是卸载,结果显示LURR值自2018年年初开始快速增加并在2018年年中达到峰值,此后异常持续至地震。在此基础上对该地区的大地形变和地下井水位资料进行了LURR分析,发现水富水平摆倾斜仪的东西和南北分量在LURR出现异常的同期发生明显偏转,而地震周边的地下井水位高值变化过程与长宁地震也有较好的对应关系。研究表明在长宁地震发生前,存在地震活动和地下水位的LURR异常,且异常时间与水富倾斜同步,暗示震源区介质存在明显的应力积累过程。     

岩石力学参数对裂缝发育程度的影响

弹性模量(E)、泊松比(μ)及密度(ρ)是岩石的重要力学参数, 当其他条件一致时, 在一定程度上影响着裂缝的发育。以塔里木盆地某气田为研究区, 在造缝期古应力场分析的基础上, 利用储层裂缝数值模拟技术, 计算得到储层裂缝孔隙度; 再以裂缝孔隙度为指标, 分析岩石力学参数对裂缝发育程度的影响。研究结果表明, 裂缝孔隙度随弹性模量的增加而增大, 同等应力条件下, 弹性模量越大, 裂缝孔隙度越高, 破裂程度越大; 泊松比小于0.2时, 裂缝孔隙度随泊松比增加而逐渐下降; 泊松比超过0.2后, 裂缝孔隙度随泊松比增加而逐渐增大; 岩石密度对裂缝孔隙度的影响不大, 基本上可以忽略。      

加卸载响应比的新进展

本文对此作简要介绍。主要有下三方面：①预测效果好：2004年发生在中国大陆有资料地区的ML≥15级地震共17次,其中15次落入用加卸载响应比方法于2003年底预测的区域内。②通过大量基础研究(包括数值模拟,岩石力学实验及统计细观损伤力学研究),使加卸载响应比理论(LURR)建立在一个比较牢靠的科学基础上。③LURR有很大的潜力和发展空间。未来的发展空间,除预测天然地震外,还可能对矿震、水库地震、滑坡等自然灾害,甚至其它自然系统以致社会系统的灾变作出预测。     

一种改进的SAR影像边缘检测方法

由于SAR影像具有乘性相干斑噪声,某些对光学影像有较好检测性能的边缘检测算子,对于SAR影像并不适用,因此本文提出了一种将改进后的Ratio算子与Canny算子相组合的新方法。首先采用多种客观评价指标,得出经典方法中的Lee滤波能有效去除噪声,且最大限度保留了梯度信息,适用于边缘检测;然后对边缘检测具有恒虚警特性的Ratio算子进行改进,改进后的算子更利于影像归一化处理;最后利用改进后的Ratio算子与Canny算子组合成新方法。试验结果证明,组合后的新方法显著提高了边缘检测正确率和定位精度,改善了边缘连续性,具有一定的有效性和实用性。     

介质密度反演偏导矩阵的精确计算方法

实现反演偏导矩阵的计算是基于导数最优化反演方法的关键,然而目前的地震反演几乎都是基于Zoeppritz方程近似实现的,使计算精度和适应范围受到限制.本文利用Zoeppritz方程建立了反射系数对地层介质密度比偏导方程,导出了Zoeppritz方程矩阵元对介质密度比的导数.通过求解偏导方程获得了反射系数对介质密度比偏导数的精确计算(考虑了速度中含介质密度的问题).利用数值算例分析了反射系数对介质密度比偏导数的变化特点.本文采用直接解法求解偏导矩阵方程组,获得了快的计算速度和高的计算精度,为实现地层介质密度反演(包括大角度反演)提供了偏导矩阵的计算方法.     

大柴旦地震前后的波速比特征

利用大柴旦地区的5个台站的数字波形资料,计算研究了大柴旦序列波速比随时间的变化特征,分析发现：2009年8月28日大柴旦6.4级地震前,5个台站的波速比都出现了低值异常;该地震后的几次5级以上余震前,部分台的波速比对这些余震有异常反应。大柴旦地震台的波速比值对5级以上地震映震能力较好。     

A new Likelihood Ratio for supervised classification of fully polarimetric SAR data: An application for sea ice type mapping

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the classification of land cover, such as forest canopies, vegetation, sea ice types, and urban areas. In contrast to single or dual polarized SAR systems, full polarimetric SAR systems provide more information about the physical and geometrical properties of the imaged area. This paper proposes a new Bayes risk function which can be minimized to obtain a Likelihood Ratio (LR) for the supervised classification of polarimetric SAR data. The derived Bayes risk function is based on the complex Wishart distribution. Furthermore, a new spatial criterion is incorporated with the LR classification process to produce more homogeneous classes. The application for Arctic sea ice mapping shows that the LR and the proposed spatial criterion are able to provide promising classification results. Comparison with classification results based on the Wishart classifier, the Wishart Likelihood Ratio Test Statistic (WLRTS) proposed by Conradsen et al. (2003) and the Expectation Maximization with Probabilistic Label Relaxation (EMPLR) algorithm are presented. High overall classification accuracy of selected study areas which reaches 97.8% using the LR is obtained. Combining the derived spatial criterion with the LR can improve the overall classification accuracy to reach 99.9%. In this study, fully polarimetric C-band RADARSAT-2 data collected over Franklin Bay, Canadian Arctic, is used.     

Seismic random noise attenuation by time-frequency peak filtering based on joint time-frequency distribution

Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner–Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner–Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest.