Journal article

Early identification of an impending rockslide location via a spatially-aided Gaussian mixture model

Shuo Zhou, Howard Bondell, Antoinette Tordesillas, Benjamin IP Rubinstein, James Bailey

Annals of Applied Statistics | Institute of Mathematical Statistics | Published : 2020

Abstract

Movement of soil and rocks in an unstable slope under gravitational forces is an example of a complex system that is highly dynamic in space and time. A typical failure in such systems is a landslide. Fundamental studies of granular media failure combined with a complex network analysis of radar monitoring data show that distinct partitions emerge in the kinematic field in the early stages of the prefailure regime, and these patterns yield clues to the ultimate location of failure. In this study we address this partitioning of constituent units in complex systems by clustering the kinematic data, specifically, with a Gaussian mixture model. In addition, we assume that neighboring units shoul..

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Grants

Awarded by US DoD High Performance Computing Modernization Program (HPCMP)


Funding Acknowledgements

This research is supported by US DoD High Performance Computing Modernization Program (HPCMP) Contract FA5209-18-C-0002.