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Block model of passive seismic shear velocity and airborne electromagnetic resistivity in the Geyer area, Erzgebirge, Germany

Ryberg, Trond; Kirsch, Moritz; Haberland, Christian; Tolosana Delgado, Raimon; Viezzoli, Andrea; Gloaguen, Richard


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{
  "title": "Block model of passive seismic shear velocity and airborne electromagnetic resistivity in the Geyer area, Erzgebirge, Germany", 
  "id": "1222", 
  "DOI": "10.14278/rodare.1222", 
  "author": [
    {
      "family": "Ryberg, Trond"
    }, 
    {
      "family": "Kirsch, Moritz"
    }, 
    {
      "family": "Haberland, Christian"
    }, 
    {
      "family": "Tolosana Delgado, Raimon"
    }, 
    {
      "family": "Viezzoli, Andrea"
    }, 
    {
      "family": "Gloaguen, Richard"
    }
  ], 
  "note": "Instruments for the seismic network were provided by the Geophysical Instrument Pool Potsdam (GIPP, GFZ), grant GIPP202010.", 
  "publisher": "Rodare", 
  "abstract": "<p>As a means of investigating the structure of the geological subsurface and delineating Sn-W-Li greisen-hosted&nbsp;mineral deposits in the Geyer-Ehrenfriedersdorf area, Central&nbsp;Erzgebirge, Germany, we collected an ambient noise dataset which was supplemented and analysed together with&nbsp;airborne time-domain&nbsp;electromagnetic data. The here presented dataset is a combined three-dimensional block model containing the following parameters:</p>\n\n<p>(X), (Y), (Z) &ndash; Coordinates of the block model center nodes in ETRS89 UTM33N coordinates.</p>\n\n<p>(PS_vel) &ndash; Shear wave velocity&nbsp;based on ambient noise data from a dense &quot;LARGE-N&quot; network comprising 400 low-power, short-period seismic stations tomographically inverted&nbsp;based on Bayesian statistics.</p>\n\n<p>(logVTEM_res) &ndash; Logarithm of resistivity based on airborne time-domain electromagnetic data acquired using the Geotech Versatile Time Domain (VTEM&trade; ET) system&nbsp;and inverted using a&nbsp;layered earth approach.</p>\n\n<p>(class_K-means) &ndash;&nbsp;Class labels of a spatially constrained clustering using&nbsp;K-means with 26 immediate neighbours&nbsp;performed on the bivariate velocity-resistivity 3D dataset.</p>", 
  "type": "dataset", 
  "issued": {
    "date-parts": [
      [
        2021, 
        10, 
        21
      ]
    ]
  }, 
  "language": "eng", 
  "version": "1.0"
}
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