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  • 1
    Publication Date: 2017-06-28
    Description: In this article, we describe a neural network method for the fast discrimination between local earthquakes and regional and teleseismic earthquakes using seismic records from a single station. Neural networks are data-driven nonlinear classifiers that learn from experience and can model real-world complex relationships. For the discrimination task, we implement a two-layer feed-forward multilayer perceptron (MLP). MLP is a supervised technique that accomplishes the learning process using a preclassified dataset for the training phase. The dataset includes 70 teleseisms, 79 regional earthquakes, and 103 local earthquakes. The seismic events are recorded at a single station, equipped with a short-period sensor. We parameterize the seismograms in the frequency domain, using the linear predictive coding (LPC). This technique is mostly used in audio signal processing for efficiently encoding frequency features of digital signals in a compressed form. The obtained spectral features, or LPC coefficients, are the input to the neural model. We carry out several tests by shortening from 4 to 1 s the time-window duration used for the LPC analysis. The proposed algorithm achieves a correct classification of 98.5% and 97.7% in discriminating local versus regional and local versus teleseismic earthquakes, respectively, on a 1-s time window. These results indicate that our discrimination algorithm can be profitably exploited in automatic analyses of seismic data that require fast responses, such as seismological monitoring systems and earthquake early warning systems.
    Print ISSN: 0895-0695
    Electronic ISSN: 1938-2057
    Topics: Geosciences
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  • 2
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  • 4
    Publication Date: 2009-05-01
    Print ISSN: 0895-0695
    Electronic ISSN: 1938-2057
    Topics: Geosciences
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  • 5
    Publication Date: 2006-08-01
    Description: In this article we report on the implementation of an automatic system for discriminating landslide seismic signals on Stromboli island (southern Italy). This is a critical point for monitoring the evolution of this volcanic island, where at the end of 2002 a violent tsunami occurred, triggered by a big landslide. We have devised a supervised neural system to discriminate among landslide, explosion-quake, and volcanic microtremor signals. We first preprocess the data to obtain a compact representation of the seismic records. Both spectral features and amplitude-versus-time information have been extracted from the data to characterize the different types of events. As a second step, we have set up a supervised classification system, trained using a subset of data (the training set) and tested on another data set (the test set) not used during the training stage. The automatic system that we have realized is able to correctly classify 99% of the events in the test set for both explosion-quake/landslide and explosion-quake/microtremor couples of classes, 96% for landslide/microtremor discrimination, and 97% for three-class discrimination (landslides/explosion - quakes/microtremor). Finally, to determine the intrinsic structure of the data and to test the efficiency of our parametrization strategy, we have analyzed the preprocessed data using an unsupervised neural method. We apply this method to the entire dataset composed of landslide, microtremor, and explosion-quake signals. The unsupervised method is able to distinguish three clusters corresponding to the three classes of signals classified by the analysts, demonstrating that the parametrization technique characterizes the different classes of data appropriately.
    Print ISSN: 0037-1106
    Electronic ISSN: 1943-3573
    Topics: Geosciences , Physics
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  • 6
    Publication Date: 2008-10-01
    Description: We have implemented a method based on an unsupervised neural network to cluster the waveforms of very-long-period (VLP) events associated with explosive activity at the Stromboli volcano (southern Italy). Stromboli has several active vents in the summit area producing together more than 200 explosions/day. We applied this method to investigate the relationship between each vent and its associated VLP explosive waveform. We selected 147 VLP events recorded between November and December 2005, when digital infrared camera recordings were available. From a visual inspection of the infrared camera images, we classified the VLPs on the basis of which vent produced each explosion. We then applied the self-organizing map (SOM), an unsupervised neural technique widely applied in data exploratory analysis, to cluster the VLPs on the basis of their waveform similarity. Our analysis demonstrates that the most recurrent VLP waveforms are usually generated by the same vent. Some exceptions occurred, however, in which different waveforms are associated with the same vent, as well as different vents generating similar waveforms. This suggests that the geometry of the upper conduit-vent system plays a role in shaping the recurring VLP events, whereas occasional modest changes in the source process dynamics produce the observed exceptions.
    Print ISSN: 0037-1106
    Electronic ISSN: 1943-3573
    Topics: Geosciences , Physics
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  • 7
    Publication Date: 2020-12-07
    Description: Stromboli is a volcanic island that is part of the Aeolian arch in the Mediterranean Sea (Italy). It is one of the most active volcanoes in Europe. Its moderate, but persistent, explosive activity makes it an ideal site for studies into the seismogenic processes in volcanic areas (Auger et al. 2006; Chouet et al. 2003; Chouet et al. 2008; D’Auria and Martini 2008; Del Pezzo et al. 1992; Esposito et al. 2008; Jaupart and Vergniolle 1989; Martini et al. 2007); it also attracts a lot of tourists. In the past, this combination of tourism and volcanic activity was not considered to be dangerous, but over the past few decades, Stromboli has produced stronger explosions that have in some cases injured people visiting the summit area. Moreover, in the recent history of Stromboli, two effusive eruptions have occurred that were accompanied by dangerous phenomena such as tsunami and vulcanian explosions. The first of these effusive eruptions (on 28 December 2002) produced a lava flow on the Sciara del Fuoco side, which is the northwest flank of the island. Two days later, a landslide occurred on this flank, which resulted in the propagation of a 10-m tsunami wave around the coasts of the island. These events demonstrate that Stromboli can be dangerous, even if its activity is not very energetic. Indeed, the Sciara del Fuoco structure is a weakness zone of the volcanic edifice that fractures when the explosive activity increases, giving rise to this effusive activity (Martini et al. 2007). Moreover, during the past two effusive eruptions, vulcanian explosions were associated with the end stages of the effusive phases. These damaged the village of Ginostra and caused fires in the vegetation. For these reasons, in January 2003, the Istituto Nazionale di Geofisica e Vulcanologia (INGV; the Italian National Institute of Geophysics and Volcanology) started to install a broadband seismic network that is designed to monitor Stromboli’s volcanic activity. This nature of the activity requires broadband instruments because the eruptive processes generate signals that span a wide range of frequencies (Chouet et al. 2003; Neuberg et al. 1994). At present, the typical seismic signals that are being recorded on Stromboli are: volcanic tremors with frequencies of 1–6 Hz; explosion quakes that include components with different frequency contents, ranging from some tens of seconds up to 10 Hz; long-period (LP) earthquakes with frequencies of 1–6 Hz; volcano-tectonic (VT) earthquakes with a frequency band of 1–20 Hz; and landslide signals with frequencies of 1–10 Hz. In particular, very long period (VLP) events with frequencies of 0.02–1 Hz are associated with the Strombolian explosions and represent the lower frequency content of the explosion quakes. Furthermore, the network records regional and teleseismic events.
    Description: Published
    Description: 435-439
    Description: 1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
    Description: JCR Journal
    Description: reserved
    Keywords: Broadband Seismic Network ; Stromboli Volcano ; 04. Solid Earth::04.06. Seismology::04.06.10. Instruments and techniques ; 04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
    Publication Date: 2020-11-30
    Description: Mt. Vesuvius (southern Italy) is one of the volcanoes that poses the greatest risk in the world because of its highly explosive eruptive style and its proximity to densely populated areas. The urbanization around Mt. Vesuvius began in ancient times, and the impact of eruptions on human activities has been severe. This is testified to by the ruins of Pompeii, which are covered by the products of the plinian eruption that took place in A.D. 79 (Sigurdsson et al. 1985), and more recently by the published reports of the eruptions that occurred from 1631 to 1944. For these reasons, Mt. Vesuvius was also one of the first volcanoes to be equipped with monitoring instruments. Pioneering instrumental observations began just before the second half of the 1800s, when the Vesuvius Observatory was founded in 1841 (Imbò 1949). At that time, Vesuvius was very active (Ricciardi 2009), and its effusive and explosive eruptions often caused damage to the surrounding areas. At the same time, it was a famous tourist attraction that drew travelers from all over the world (Gasparini and Musella 1991). Since the middle of the 1800s, at least 12 eruptions have occurred that have been superimposed on persistent intra-crater activity that has been characterized by Strombolian explosions and by the formation of small lava lakes. The last eruption occurred on 18 March 1944 and marked a change in the status of Mt. Vesuvius, as it entered a closed-conduit phase that persists today. Following this last eruption, a change occurred in the 1960s, as documented by an increase in the occurrence rate of earthquakes. Since 1972, the monitoring of Mt. Vesuvius has improved over time and become more systematic, so that there is a remarkable dataset relating to the current phase of quiescence. Over more than a century and a half of observations, many monitoring instruments have been used for Mt. Vesuvius, including early seismometers, several of which are now kept in the Museum of Volcanology of the Vesuvius Observatory. The present monitoring system is based on seismological, geodetical geodetical, and geochemical observations performed using an instrumental network that was designed on the basis of the current state of the volcano while also taking into account the likely scenario of future unrest.
    Description: Published
    Description: 625-634
    Description: 1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
    Description: JCR Journal
    Description: reserved
    Keywords: Seismological Monitoring ; Mount Vesuvius ; 04. Solid Earth::04.06. Seismology::04.06.05. Historical seismology ; 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology ; 04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
    Publication Date: 2020-11-30
    Description: On February 27, 2007, the Stromboli volcano, which has usually been characterized by moderate explosive activity, started an effusive eruption with a small lava flow down the NW flank. The permanent broadband network installed on the island allowed the revealing of anomalies in the seismicity before the effusive eruption and for the phenomena to be followed over time, thus obtaining meaningful information about the eruption dynamics. During the effusive phase, a major explosion occurred on March 15, 2007. On that occasion, two strainmeters deployed on the volcano in the previous year recorded a strain increment before the blast. After this explosion, which further destabilized the upper part of the edifice, swarms of Long-Period (LP) and hybrid events were recorded. The characteristics and locations of these events suggest that they were associated with the fracturing processes that affected the summit area of the cone. During the effusive phase, changes in the Very Long Period (VLP) event location were recorded. This type of events accompanied the change in the eruptive style, providing information about the magmatic conduit involved in their seismogenetic processes. The effusive phase stopped on April 2, 2007, and the typical Strombolian activity restarted some months later.
    Description: JCR Journal
    Description: open
    Keywords: Stromboli ; volcano monitoring ; volcano seismicity ; 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 10
    Publication Date: 2017-04-04
    Description: This paper reports on the unsupervised analysis of seismic signals recorded by four stations situated on the Vesuvius area in Naples, Italy. The dataset under examination is composed of earthquakes and false events like thunders, quarry blasts and man-made undersea explosions. The goal is to use these specific data for comparing the performance of three projection methods that are well known to be able to exploit structures and organizes data, providing a framework for understanding and interpreting the relationships between data items, and suggesting simple descriptions of these relationships. The three unsupervised techniques under examination are: Principal Component Analysis (PCA), which is linear, Self-Organizing Map (SOM) and Curvilinear Component Analysis (CCA), which are nonlinear. The results show that, among the above techniques, SOM can better visualize the complex set of high-dimensional data allowing to discover their intrinsic clusters structure and eventually discriminate the earthquakes from the false events either natural (thunder) or artificial (quarry blast and undersea explosions).
    Description: Unpublished
    Description: PARIS
    Description: open
    Keywords: seismic signals ; unsupervised clustering techniques ; 05. General::05.01. Computational geophysics::05.01.02. Cellular automata, fuzzy logic, genetic alghoritms, neural networks
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Conference paper
    Format: 435161 bytes
    Format: application/pdf
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