Advancing Local Distance Discrimination of Explosions and Earthquakes With Joint P/S and ML‐MC Classification

Abstract

Classification of local‐distance, low‐magnitude seismic events is challenging because signals can be numerous and difficult to characterize with approaches developed for larger magnitude events observed at greater distances. Yet, accurate classification is important to studies of earthquake processes and detection of potential underground nuclear tests. Here, we combine two classification metrics: the three‐component ratio of high‐frequency P/S amplitudes and the difference between local and coda duration magnitudes (ML‐MC). The metrics use different parts of the high‐frequency wavefield and exhibit complementary sensitivity for classification of M ∼ 0.5–4 natural earthquakes and borehole explosions, which are the best analog for underground nuclear explosions. Using means from bootstrap resampling across four diverse geologic settings, joint classification achieves >94.4% true positives and ≥8 seismographs within 200 km of the source. This high performance is obtained without local site corrections, indicating that the method may be transportable for local event classification.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 24, 2021
Source ID
10.1029/2021gl095721

Entities

People

  • Brandon Schmandt
  • Keith D. Koper
  • Monique M. Holt
  • Ruijia Wang

Organizations

  • Air Force Research Laboratory
  • National Science Foundation
  • Southern University of Science and Technology
  • University of Illinois at Chicago
  • University of New Mexico
  • University of Utah

Tags

Readers

  • Computer Vision.
  • Seismology