Geology Reports⌕ Search
Home/Archive/USGS

USGS · 70265000

Automated, near real-time ground-motion processing at the U.S. Geological Survey

Eric M. Thompson·Mike Hearne·Brad T. Aagaard·J.M. Rekoske·Charles Worden·Morgan P. Moschetti·Heather Elizabeth Hunsinger·Gabe C. Ferragut·Grace Alexandra Parker·James Andrew Smith·Kyle Ken Smith·Albert R. Kottke
View original source ↗Export metadata ↓

Abstract

We describe automated ground‐motion processing software named gmprocess that has been developed at the U.S. Geological Survey (USGS) in support of near‐real‐time earthquake hazard products. Because of the open‐source development process, this software has benefitted from the involvement and contributions of a broad community and has been used for a wider range of applications than was initially envisioned. Here, we give an overview and introduction to the software, including how it has leveraged other open‐source libraries. We highlight some key features that gmprocess provides, compare response spectra calculated with the automated processing approach of gmprocess to the response spectra provided by the Next Generation Attenuation projects, and summarize projects that have utilized gmprocess. These use‐cases demonstrate that this software development effort has been successfully leveraged in earthquake research activities both within and outside the USGS.

Explore related subjects

Seismological Research LettersArticle

Keep this discovery

BibTeXRIS

Eric M. Thompson, Mike Hearne, Brad T. Aagaard, J.M. Rekoske, Charles Worden, Morgan P. Moschetti, Heather Elizabeth Hunsinger, Gabe C. Ferragut, Grace Alexandra Parker, James Andrew Smith, Kyle Ken Smith, Albert R. Kottke. 2024-08-16. Automated, near real-time ground-motion processing at the U.S. Geological Survey. https://doi.org/10.1785/0220240021

Cite the original work for its findings. Save a collection to share your selection of sources.

Discover connections

Article subjectSeismological Research Letters subject

Connections use source metadata and explicit phrase matches, not verified experimental comparisons.

KEEP EXPLORING

Related USGS reports

USGS2024

Distinguishing natural sources from anthropogenic events in seismic data

As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).

Seismological Research Letters↗
USGS2026

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters↗