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Multifractality in Seismicity Spatial Distributions: Significance and Possible Precursory Applications as Found for Two Cases in Different Tectonic Environments

机译:地震空间分布中的多重分形:在不同构造环境中发现两种情况的意义和可能的前兆应用

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摘要

We explore fractal properties of two observed seismicity distributions prior to the 2003 M_w 7. 4 Colima, Mexico and 1992 M_w 7. 3 Landers, USA earthquakes, together with several mathematical fractal distributions and two non-fractal ones, in order to estimate minimum reliable sample sizes, determine whether fractality for observed seismicity is essentially different from random uniform distributions, and explore the possibility of extracting premonitory information from fractal characteristics of seismicity before large earthquakes. Sample sizes above 800 events for whole catalogs appear to be sufficient to maintain ordered multifractality and to yield dimension estimates that vary smoothly and reliably. Fractal estimates appear to be best for whole catalogs that include aftershocks. The fractal characteristics of spatial distributions of seismicity are essentially different from those of the uniform random distribution, which is the null hypothesis of a non-fractal distribution with minimum information. The fractal dimensions and afractality measures of seismicity distributions change with time and show distinctive behaviors associated with foreshocks and main events, although these behaviors are different for each example. Results suggest the possibility of a priori identification of foreshocks to large earthquakes. A combination of fractal dimension and afractality measures over time may be helpful in large earthquake premonitory studies.
机译:为了估计最小可靠度,我们探索了2003年M_w7。墨西哥科利马4和墨西哥1992 M_w7。3兰德斯地震之前观测到的两个地震活动分布的分形特性,以及几个数学分形分布和两个非分形地震分布。样本大小,确定观测到的地震活动性的分形性是否与随机均匀分布基本不同,并探索从大地震之前的地震活动性的分形特征中提取前期信息的可能性。整个目录的800个以上事件的样本量似乎足以维持有序的多重分形并产生平稳可靠地变化的维度估计。分形估计对于包括余震的整个目录似乎是最好的。地震活动性的空间分布的分形特征与均匀随机分布的分形特征本质上是不同的,后者是具有最少信息的非分形分布的零假设。地震分布的分形维数和分形度度量随时间变化,并显示出与前震和主要事件相关的独特行为,尽管每个示例的行为不同。结果表明,有可能先验识别大地震的前震。分形维数和随时间变化的分形量度的组合可能有助于大型地震监测研究。

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