Visual analytics of aftershock point cloud data in complex fault systems

Wang, Chisheng; Ke, Junzhuo; Jiang, Jincheng; Lu, Min; Xiu, Wenqun; Liu, Peng; Li, Qingquan

Aftershock point cloud data provide direct evidence for the characteristics of underground faults. However, there has been a dearth of studies using state-of-the-art visual analytics methods to explore the data. In this paper, we present a novel interactive visual analysis approach for visualizing the aftershock point cloud. Our method employs a variety of interactive operations, rapid visual computing functions, flexible display modes, and various filtering approaches to present and explore the desired information for the fault geometry and aftershock dynamics. The case study conducted for the 2016 Central Italy earthquake sequence shows that the proposed approach can facilitate the discovery of the geometry of the four main fault segments and three secondary fault segments. It can also clearly reveal the spatiotemporal evolution of the aftershocks, helping to find the fluid-driven mechanism of this sequence. An open-source prototype system based on the approach is also developed and is freely available.

Zitieren

Zitierform:

Wang, Chisheng / Ke, Junzhuo / Jiang, Jincheng / et al: Visual analytics of aftershock point cloud data in complex fault systems. 2019. Copernicus Publications.

Rechte

Rechteinhaber: Chisheng Wang et al.

Nutzung und Vervielfältigung:

Export