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    <title>DSpace Community: 04.06. Seismology</title>
    <link>http://hdl.handle.net/2122/238</link>
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        <rdf:li resource="http://hdl.handle.net/2122/4181" />
        <rdf:li resource="http://hdl.handle.net/2122/4162" />
        <rdf:li resource="http://hdl.handle.net/2122/4159" />
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    <title>The Community's search engine</title>
    <description>Search the Channel</description>
    <name>search</name>
    <link>http://www.earth-prints.org/simple-search</link>
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  <item rdf:about="http://hdl.handle.net/2122/4181">
    <title>Suboceanic Rayleigh Waves in the 1755 Lisbon Earthquake</title>
    <link>http://hdl.handle.net/2122/4181</link>
    <description>Title: Suboceanic Rayleigh Waves in the 1755 Lisbon Earthquake
&lt;br/&gt;
&lt;br/&gt;Authors: Vuan, A.; INOGS, Trieste; Rovelli, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia; Mele, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia; Priolo, E.; INOGS, Trieste
&lt;br/&gt;
&lt;br/&gt;Editors: Mendes-Victor, L. A.; Sousa Oliveira, C. S.; Azevedo, J.; Ribeiro, A.
&lt;br/&gt;
&lt;br/&gt;Abstract: Moderate-magnitude shallow earthquakes in the Atlantic Ocean, hundreds of kilometres southwest of Lisbon, can generate efficient suboceanic Rayleigh waves (SRW) that are well recorded in Portugal. Here we compare moderate-size earthquakes recorded by seismic stations in Portugal with the Tyrrhenian Sea earthquakes recorded in peninsular Italy where SRW were recently observed. In spite of a different behaviour of high frequencies due to the different tectonic setting of the two areas, similar results are found in the intermediate-period range, suggesting that this effect, if extrapolated to a magnitude larger than 8, could be devastating at regional distance in terms of ground motion amplitude and duration. Through 1D models, we explore the hypothesis that the high level of destruction and the long duration of shaking felt during the Great 1755 Lisbon earthquake were caused by SRW. In this preliminary study, we check the role of critical model parameters. We find that duration and amplitude are largest when the average thickness of the water layer is 2 km and shear-wave velocity of the ocean floor is close to the speed of sound in the water. Both conditions are realistic for a source in the Atlantic Ocean, few hundreds of kilometres southwest of Lisbon. Moreover, the propagation of SRW at regional distances accounts for durations of more than ten minutes as the effect of a single large earthquake.</description>
  </item>
  <item rdf:about="http://hdl.handle.net/2122/4162">
    <title>Hydrothermal origin for sustained Long-Period (LP) activity at Campi Flegrei Volcanic Complex, Italy</title>
    <link>http://hdl.handle.net/2122/4162</link>
    <description>Title: Hydrothermal origin for sustained Long-Period (LP) activity at Campi Flegrei Volcanic Complex, Italy
&lt;br/&gt;
&lt;br/&gt;Authors: Cusano, P.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione OV, Napoli, Italia; Petrosino, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione OV, Napoli, Italia; Saccorotti, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Pisa, Pisa, Italia
&lt;br/&gt;
&lt;br/&gt;Abstract: We present a detailed analysis of the source properties of Long-Period (LP) signals recorded at Campi Flegrei&#xD;
Caldera (Italy) during the last (2005–2006) mini-uplift episode. Moment Tensor inversion via full-waveform&#xD;
modelling of broad-band seismograms indicates a crack-like source with a significant volumetric component.&#xD;
From auto-regressive modelling of the signal's tail we evaluate the dominant frequency and the attenuation&#xD;
factor of the oscillating source. Considering the acoustic properties of a fluid-filled crack, these values are&#xD;
consistent with the resonant oscillations of a crack filled by a water–gas mixture at variable gas–volume&#xD;
fraction. For these fluids, the crack size would be on the order of 40–420 m, a size range which is consistent&#xD;
with the spatial spreading of LP hypocenters. Analysis of temporally-correlated time series of seismological&#xD;
and geochemical data indicates that climaxing of LP activity was preceded by swarms of volcano-tectonic&#xD;
(VT) events and rapidly followed by a consistent increase of both thermal emissions and gas fluxes recorded&#xD;
at the surface (1 month — 2/3 days, respectively). Following these observations, we propose a conceptual&#xD;
model where VT activity increases permeability of the medium, thus favouring fluid mobility. As a&#xD;
consequence, the hydrothermal system experiences pressure perturbations able to trigger its resonant, LP&#xD;
oscillations.</description>
  </item>
  <item rdf:about="http://hdl.handle.net/2122/4159">
    <title>ShakeMap implementation in Italy</title>
    <link>http://hdl.handle.net/2122/4159</link>
    <description>Title: ShakeMap implementation in Italy
&lt;br/&gt;
&lt;br/&gt;Authors: Michelini, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia; Faenza, L.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia; Lauciani, V.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia; Malagnini, L.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia
&lt;br/&gt;
&lt;br/&gt;Abstract: Since 2005, the Italian Civil Protection (Dipartimento della Protezione Cilvile, DPC)&#xD;
has funded several projects driven toward fast assessment of ground motion shaking&#xD;
in Italy - the final goal being that of organizing the emergency and direct the search&#xD;
and rescue (SAR) teams. To this end, the Istituto Nazionale di Geofisica e&#xD;
Vulcanologia (INGV) has started to determine shakemaps using the USGS-ShakeMap&#xD;
package within 30 minutes from event occurrence and adopting a manually revised&#xD;
location. In this paper we present the INGV implementation of USGS-ShakeMap for&#xD;
earthquakes occurring in Italy and immediately neighboring areas. Emphasis is put on&#xD;
data acquisition, the adopted ground motion predictive relations and the site&#xD;
corrections for the local amplifications of the ground motion.&#xD;
Finally, two examples of shakemaps are shown - the first determined for a recent&#xD;
medium size earthquake, the other for the large Irpinia, 1980, M6.9 event. For both&#xD;
events, the maps are compared to the available macroseismic data.</description>
  </item>
  <item rdf:about="http://hdl.handle.net/2122/4157">
    <title>TREMOrEC: a software utility for automatic classification of volcanic tremor</title>
    <link>http://hdl.handle.net/2122/4157</link>
    <description>Title: TREMOrEC: a software utility for automatic classification of volcanic tremor
&lt;br/&gt;
&lt;br/&gt;Authors: Masotti, M.; Medical Imaging Group, Department of Physics, University of Bologna,Viale Berti-Pichat 6/2, 40127, Bologna, Italy; Campanini, R.; Medical Imaging Group, Department of Physics, University of Bologna,Viale Berti-Pichat 6/2, 40127, Bologna, Italy; Mazzacurati, L.; Department of Computer Science, University of Bologna, Mura Anteo-Zamboni 7, 40127, Bologna, Italy; Falsaperla, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; Langer, H.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; Spampinato, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia
&lt;br/&gt;
&lt;br/&gt;Abstract: We describe a stand-alone software utility named TREMOrEC, which carries out training and test of a Support Vector Machine (SVM) classifier. TREMOrEC is developed in Visual C++ and runs under Microsoft Windows operating systems. Ease of use and short time processing, along with the excellent performance of the SVM classifier, make this tool ideal for volcano monitoring. The development of TREMOrEC is motivated by the successful application of the SVM classifier to volcanic tremor data recorded at Mount Etna in 2001 [Masotti et al,. 2006]. In that application, spectrograms of volcanic tremor were divided according to their recording date into four classes associated with different states of activity, i.e., pre-eruptive, lava fountain, eruptive, or post-eruptive. During the training, SVM learned the a-priori classification. The classifier’s performance was then evaluated on test sets not considered for training. The classification results matched the actual class membership with less than 6% of error.</description>
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