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Data

Realtime monitoring, station, and other various seismic data available for download. Access to data products to view and download.

Filter Total Items: 206

Data Release for Additional Period and Site Class Data for the 2018 National Seismic Hazard Model for the Conterminous United States (ver. 1.1, February 2020)

The updated 2018 National Seismic Hazard Model includes new ground motion models, aleatory uncertainty, and soil amplification factors for the central and eastern U.S. and incorporates basin depths from local seismic velocity models in four western U.S. (WUS) urban areas. These additions allow us, for the first time, to calculate probabilistic seismic hazard curves for an expanded set of spectral

Database for the Central United States Velocity Model, v1.3

We have developed a new three-dimensional seismic velocity model of the central United States (CUSVM) that includes the New Madrid Seismic Zone (NMSZ) and covers parts of Arkansas, Mississippi, Alabama, Illinois, Missouri, Kentucky, and Tennessee. The model represents a compilation of decades of crustal research consisting of seismic, aeromagnetic, and gravity profiles; geologic mapping; geophysic

Data from Theodolite Measurements of Creep Rates on San Francisco Bay Region Faults, California (ver. 2.2, July 2023)

The data comprise an archive of repeated surveyed measurements to monitor surface fault creep (a form of gradual tectonic movement) occurring along active faults in the San Francisco Bay region for use by the scientific research community. Additional description of these data and the methods used to collect them is provided at: https://pubs.usgs.gov/of/2009/1119/. The primary data are angle measur

Data for "Serpentinite-rich Gouge in a Creeping Segment of the Bartlett Springs Fault, Northern California: Comparison with SAFOD and Implications for Seismic Hazard"

This report presents the mineral chemistry dataset that was used in a published study of serpentinite-rich gouge from an actively creeping trace of the Bartlett Springs Fault in northern California. The fault gouge consists of porphyroclasts of antigorite serpentinite, talc, chlorite, and tremolite-actinolite in a sheared matrix of the same materials. The compositions of spinels in the serpentinit

Waveform Data and Metadata used to National Earthquake Information Center Deep-Learning Models

These data were used to train the Machine Learning models supporting the USGS software release "NEIC Machine Learning Applications Software" (https://doi.org/10.5066/P9ICQPUR), and its companion publication in Seismological Research Letters "Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center" (https://doi.org/XXXXX). These data are

Voice and data telecommunications restoration curves for 15 counties affected by the April 18, 2018, M7.0 HayWired earthquake scenario mainshock

These data are a series of telecommunications voice and data restoration percentages for 17 counties affected by the HayWired earthquake scenario, a magnitude 7.0 earthquake occurring on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. These data for telecommunications demand served are derived from residual network capacity based on potential hazard information (

Data Release for the 2016 East Bay Seismic Imaging Investigation of the Hayward Fault Zone

In October 2016, we acquired an approximately 15-km-long seismic profile along a linear transect across the East Bay region of the San Francisco Bay area. Our goal was to image previously unknown strands of the Hayward Fault zone and to better delineate the structure and geometry of the main trace of the Hayward Fault. Our profile started near the southern border of San Leandro, California at the

Field reconnaissance of ground failure triggered by shaking during the 2018 M7.1 Anchorage, Alaska, earthquake

These data present geolocated photographs, GPS tracks, and field-mapped ground failures collected during the USGS reconnaissance of ground failures following the 2018 M7.1 Anchorage Earthquake.

Initial Observations of Landslides triggered by the 2018 Anchorage, Alaska earthquake

This data release provides the locations of 43 landslides that occurred during the 2018 Anchorage, Alaska earthquake mapped from high-resolution lidar (1-m). Lidar data can be accessed via the Alaska Division of Geological and Geophysical Surveys elevation portal (https://elevation.alaska.gov). Each landslide is represented as a point corresponding to the approximate location of the mid-point of t

Summary of proposed changes to geologic inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0

This data release documents proposed updates to geologic inputs (faults) for the upcoming 2023 National Seismic Hazard Model (NSHM). This version (1.0) conveys differences between 2014 NSHM fault sources and those recently released in the earthquake geology inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 data release by Hatem et al. (2021). A notable difference between t

Displacement and strain field from the 2019 Ridgecrest earthquakes derived from analysis of WorldView optical satellite imagery (ver. 2.0, May 2021)

This Data Release contains co-seismic horizontal and vertical displacements of the 2019 Ridgecrest earthquakes derived from sub-pixel cross correlation of WorldView satellite optical imagery. Additionally, the dataset contains the 2-dimensionsal (2D) and 3-dimensional (3D) surface strain fields, inverted from the surface displacements. Associated publication: Barnhart, W.D., Gold, R.D., Hollingsw

Data Release for the 2018 Update of the U.S. National Seismic Hazard Model: Where, Why, and How Much Probabilistic Ground Motion Maps Changed

This dataset presents where, why, and how much probabilistic ground motions have changed with the 2018 update of the National Seismic Hazard Model (NSHM) for the conterminous U.S. (CONUS) vs. the 2014 NSHM. In the central and eastern U.S., hazard changes are the result of updated ground motion models (further broken down by median and epistemic uncertainty, aleatory variability, and site effects m