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Landslides are damaging and deadly, and they occur in every U.S. state. However, our current ability to understand landslide hazards at the national scale is limited, in part because spatial data on landslide occurrence across the U.S. varies greatly in quality, accessibility, and extent. Landslide inventories are typically collected and maintained by different agencies and institutions, usually within specific jurisdictional boundaries, and often with varied objectives and information attributes or even in disparate formats. The purpose of this data release is to provide an openly accessible, centralized map of existing information on landslide occurrence across the entire U.S. The data release includes digital...
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The datasets for this investigation consist of microtremor array data collected at: 1) 18 sites in Salt Lake and Utah valleys, Utah, and 2) two sites as part of the Frontier Observatory for Research in Geothermal Energy (FORGE) near Milford, Utah. Each of the 18 sites in the Salt Lake and Utah valleys were acquired with four-sensor arrays with three-component (3C) sensors having flat response from 0.033 Hz to 50 Hz. The data acquired as part of the FORGE investigation used both 3C broadband and 5-Hz geophone sensors. Additional information on these datasets can be found in the supporting documentation provided in this data release as well as in the paper by Zhang and others (2019) that utilized these data.
A revised version of the storm-time disturbance index Dst is calculated using hourly-mean magnetic-observatory data from four standard observatories and collected over the years 1958–2007. The calculation algorithm is a revision of that established by Sugiura et al., and which is now used by the Kyoto World Data Center for routine production of Dst. The most important new development is for the removal of solar-quiet variation. This is done through time and frequency-domain band-stop filtering – selectively removing specific Fourier terms approximating stationary periodic variation driven by the Earth’s rotation, the Moon’s orbit, the Earth’s orbit around the Sun, and their mutual coupling. The resulting non-stationary...


    map background search result map search result map A Bayesian Monte-Carlo Inversion of Spatial Auto-Correlation (SPAC) for Near-Surface Vs Structure Applied to Both Broadband and Geophone Data - Data Release Landslide Inventories across the United States A Bayesian Monte-Carlo Inversion of Spatial Auto-Correlation (SPAC) for Near-Surface Vs Structure Applied to Both Broadband and Geophone Data - Data Release Landslide Inventories across the United States