SUMMARY The spatial correlation of earthquake ground motion intensity can be measured from strong motion data; however, the data used in past studies is sparsely sampled in space, and only the interstation distance was considered as a correlation variable. These limitations mean that we have only weak constraints on the true correlation structure of ground motion and that potentially important aspects of spatial correlation are unconstrained. In this study, we combine a large-N seismic array and graph analytics to explore this issue at a local scale using small local and regional earthquakes. Our result suggests site conditions, and how they interact with the incident seismic wavefield, strongly condition the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements, either through nodal deployments, or perhaps distributed acoustic sensing measurements, of seismic wavefields. Aftershock sequences of major earthquakes would provide particularly data-rich targets of opportunity.

中文翻译：

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地震地震动空间相关性的网络分析：以圣哈辛托地震节点阵列为例

小结 地震地震动强度的空间相关性可以从强震数据中测得；然而，过去研究中使用的数据在空间上是稀疏采样的，仅将站间距离视为相关变量。这些限制意味着我们对地震动的真实相关结构只有较弱的约束，并且空间相关的潜在重要方面不受约束。在这项研究中，我们结合了大 N 地震阵列和图形分析，使用小型局部和区域地震在局部范围内探索这个问题。我们的结果表明场地条件，以及它们如何与入射地震波场相互作用，强烈地影响了地面运动的空间相关性。在表征地震动空间变异性方面的未来进展将需要密集波场测量，或者通过节点部署，或者可能通过地震波场的分布式声学传感测量。大地震的余震序列将提供特别丰富的数据机会目标。