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2 results for “Sedimentary structure”
Sedimentary structure discrimination with hyperspectral imaging in sediment cores
<p>The LDB17_P11Ax (IGSN: TOAE0000000243); Datation Age 1040 +/- 30 to 2017 CE by core correlation, 14C, lamina counting) core from the Bourget Lake (France) was analyzed in 2018 by hyperspectral imaging. We studied the potential of hyperspectral sensor to image a sediment cores and created machine learning models. The hyperspectral images were acquired in order to develop quantitative (estimating particle size and loss on ignition) and qualitative (detection of instantaneous events or lamina) methods.<br> All these methods allow to reconstruct the past environment and climate at high resolution (pixel size: 50-250 microns) and without destroying the sample for archiving for future analysis.<br> These images have been valorized in publications for the detection of instantaneous events with hyperspectral and combined with XRF data, for the combination of the two images into a composite image.<br> image (.hdr, .dat, .jpg)</p>
Smoothed basin velocity structure model of the Kanto Sedimentary Basin (Takemura et al., 2015)
<p><strong>Model description</strong></p> <p>We constructed sedimentary <em>S</em>-wave velocity structure model of the Northern Kanto region using 190 local <em>S</em>-wave velocity structures. In the uploaded files of Takemura2015_V0..dat and Takemura2015_Alpha.dat, longitudes, latitudes and values of <span class="math-tex">\(V_0\)</span> (and <span class="math-tex">\(\alpha\)</span>) at 190 local points are listed. Our model of the sedimentary basin was described by two parameters of a simple velocity gradient function (Ravve and Koren 2006). The depth gradient function is described as</p> <p><span class="math-tex">\(V_S(z)=V_0+\Delta V\left[1-\exp\left(-\frac{\alpha z}{\Delta V}\right)\right]\)</span></p> <p>where <span class="math-tex">\(V_0\)</span> is the <em>S</em>-wave velocity at the surface (<em>z</em> =&thinsp;0), <span class="math-tex">\(\Delta V\)</span> is <em>S</em>-wave velocity of the bedrock (3.2 km/s), and <span class="math-tex">\(\alpha\)</span> is the positive constant that determines the velocity-depth gradient.</p> <p><strong>3D sedimentary model construction </strong></p> <p>After applying GMT surface to each parameter, spatial variations of both two parameters were obtained. Using obtained spatial distributions of <span class="math-tex">\(V_0\)</span> and <span class="math-tex">\(\alpha\)</span> and the depth gradient function, 3D sedimentary velocity structure of the Northern Kanto region could be constructed. </p> <p><strong>Citation</strong></p> <p>Takemura, S., Akatsu, M., Masuda, K., Kajikawa, K., & Yoshimoto, K., (2015), Long-period ground motions in a laterally inhomogeneous large sedimentary basin: observations and model simulations of long-period surface waves in the northern Kanto Basin, Japan, Earth, Planets and Space, 67:33, <a href="https://doi.org/10.1186/s40623-015-0201-7">doi:10.1186/s40623-015-0201-7</a></p>
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