Item talk:Q272141

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Revision as of 02:06, 22 August 2024 by Sky (talk | contribs) (Created page with "{ "USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70203350", "url": "ht...")
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   "abstract": "Seismologists have recently begun utilizing low-cost nodal sensors in dense deployments to sample the seismic wavefield at unprecedented spatial resolution. Earthquake Early Warning Systems (EEWS) and other monitoring networks (e.g. wastewater injection) would additionally benefit from network densification; however, current nodal systems lack power systems and/or real-time data transmission required for these applications. A candidate sensor for these networks may instead be a low-cost, all-in-one package such as the OSOP Raspberry Shake 4D (RS-4D). The RS-4D includes a vertical component geophone, 3-component accelerometer, digitizer, and near real-time miniSEED data transmission, and costs only a few hundred dollars per unit. Here, we step through instrument testing of three RS-4Ds at the Albuquerque Seismological Laboratory. We find the geophones have sensitivities constrained to within 4% of nominal, but that they have relatively high self-noise levels compared to the broadband sensors typically used in seismic networks. To demonstrate the impact this would have on characterizing nearby events, we estimate local magnitudes of earthquakes in Oklahoma using Trillium Compact broadband sensor data from U.S. Geological Survey (USGS) aftershock deployments as well as 23 Raspberry Shakes operated by hobbyists and private owners within Oklahoma. We find that for ML 2.0-4.0 earthquakes at distances of 20-100 km from seismic stations, the Raspberry Shakes require events of magnitude ~0.3 larger than the broadband sensors in order to reliably estimate ML at a given distance from the epicenter. We conclude that RS-4Ds are suitable for densifying backbone networks designed for studies of local and regional events.",
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