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  • 04.08. Volcanology  (19)
  • 04.06. Seismology  (15)
  • Creep observations and analysis
  • Wiley  (9)
  • Elsevier B.V.  (8)
  • EGU - Copernicus  (6)
  • Copernicus Publications
Collection
Publisher
  • 1
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    Unknown
    Wiley
    In:  Bull., Polar Proj. OP-O3A4, Earth Rheology, Isostasy and Eustasy, London, Wiley, vol. 13, no. 4, pp. 125-134, (ISBN 0080419208)
    Publication Date: 1979
    Keywords: Rheology ; Creep observations and analysis ; Lithosphere
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  • 2
    Publication Date: 2020-11-25
    Description: The equilibrium composition of volcanic gaseswith their magma is often overprinted by interaction with ashallow hydrothermal system. Identifying the magmatic sig-nature of volcanic gases is critical to relate their composi-tion to properties of the magma (temperature,fO2, gas-meltsegregation depth). We report measurements of the chemi-cal composition and flux of the major gas species emittedfrom Turrialba Volcano during March 2013. Measurementswere made of two vents in the summit region, one of whichopened in 2010 and the other in 2012. We determined an av-erage SO2flux of 5.2±1.9 kg s−1using scanning ultravio-let spectroscopy, and molar proportions of H2O, CO2, SO2,HCl, CO and H2gases of 94.16, 4.03, 1.56, 0.23, 0.003 and0.009 % respectively by open-path Fourier transform infrared(FTIR) spectrometry and a multi-species gas-sensing system.Together, these data imply fluxes of 88, 8, 0.44, 5×10−3and1×10−3kg s−1for H2O, CO2, HCl, CO and H2respectively.Although H2S was detected, its concentration could not beresolved. HF was not detected. The chemical signature of thegas from both vents was found to be broadly similar. Follow-ing the opening of the 2010 and 2012 vents we found limitedto negligible interaction of the magmatic gas with the hy-drothermal system has occurred and the gas composition ofthe volcanic plume is broadly representative of equilibriumwith the magma. The time evolution of the gas composition,the continuous emission of large quantities of SO2, and thephysical evolution of the summit area with new vent open-ings and more frequent eruptions all point towards a continu-ous drying of the hydrothermal system at Turrialba’s summitat an apparently increasing rate.
    Description: This research was supported by the RoyalGeographical Society (with IBG) with a Geographical FieldworkGrant. Y. Moussallam and N. Peters were additionally supportedby the Philip Lake funds from the Department of Geography,University of Cambridge. Y. Moussallam acknowledges a researchgrant from Mazamas and support through ERC project #279790.We thank the NERC Field Spectroscopy Facility for the loanof their infrared spectrometer. A. Aiuppa acknowledges supportthrough ERC grant no. 305377 (BRIDGE)
    Description: Published
    Description: 1341–1350
    Description: 4V. Processi pre-eruttivi
    Description: JCR Journal
    Keywords: volcanic degassing ; Multi-GAS ; UV spectroscopy ; FTIR ; 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 3
    Publication Date: 2021-01-19
    Description: Excessive numerical diffusion is one of the major limitations in the representation of long-range transport by chemistry transport models. In the present study, we focus on excessive diffusion in the vertical direction, which has been shown to be a major issue, and we explore three possible ways of addressing this problem: increasing the vertical resolution, using an advection scheme with anti-diffusive properties and more accurately representing the vertical wind. This study was carried out using the CHIMERE chemistry transport model for the 18 March 2012 eruption of Mount Etna, which released about 3 kt of sulfur dioxide into the atmosphere in a plume that was observed by satellite instruments (the Infrared Atmospheric Sounding Interferometer instrument, IASI, and the Ozone Monitoring Instrument, OMI) for several days. The change from the classical Van Leer (1977) scheme to the Després and Lagoutière (1999) anti-diffusive scheme in the vertical direction was shown to provide the largest improvement to model outputs in terms of preserving the thin plume emitted by the volcano. To a lesser extent, the improved representation of the vertical wind field was also shown to reduce plume dispersion. Both of these changes helped to reduce vertical diffusion in the model as much as a brute-force approach (increasing vertical resolution).
    Description: Published
    Description: 5707–5723
    Description: 5V. Processi eruttivi e post-eruttivi
    Description: JCR Journal
    Keywords: 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 4
    Publication Date: 2021-01-22
    Description: Spectral analysis has been applied to almost thou-sand seismic events recorded at Vesuvius volcano (Naples,southern Italy) in 2018 with the aim to test a new tool fora fast event classification. We computed two spectral pa-rameters, central frequency and shape factor, from the spec-tral moments of order 0, 1, and 2, for each event at sevenseismic stations taking the mean among the three compo-nents of ground motion. The analyzed events consist ofvolcano-tectonic earthquakes, low frequency events and un-classified events (landslides, rockfall, thunders, quarry blasts,etc.). Most of them are of low magnitude, and/or low maxi-mum signal amplitude, therefore the signal to noise ratio isvery different between the low noise summit stations andthe higher noise stations installed at low elevation aroundthe volcano. The results of our analysis show that volcano-tectonic earthquakes and low frequency events are easily dis-tinguishable through the spectral moments values, particu-larly at seismic stations closer to the epicenter. On the con-trary, unclassified events show the spectral parameters valuesdistributed in a broad range which overlap both the volcano-tectonic earthquakes and the low frequency events. Since thecomputation of spectral parameters is extremely easy and fastfor a detected event, it may become an effective tool for eventclassification in observatory practice.
    Description: Published
    Description: 67–74
    Description: 1SR TERREMOTI - Sorveglianza Sismica e Allerta Tsunami
    Description: N/A or not JCR
    Keywords: Vesuvius ; Spectral Analisys ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 5
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    Elsevier B.V.
    Publication Date: 2021-02-01
    Description: In supervised classification, we search criteria allowing us to decide whether a sample belongs to a certain class of patterns. The identification of such decision functions is based on examples where we know a priori to which class they belong. The distinction of seismic signals, produced from earthquakes and nuclear explosions, is a classical problem of discrimination using classification with supervision. We move on from observed data—signals originating from known earthquakes and nuclear tests—and search for criteria on how to assign a class to a signal of unknown origin. We begin with Principal Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (FLDA), identifying a linear element separating groups at best. PCA, FLDA, and likelihood-based approaches make use of statistical properties of the groups. Considering only the number of misclassified samples as a cost, we may prefer alternatives, such as the Multilayer Perceptrons (MLPs). The Support Vector Machines (SVMs) use a modified cost function, combining the criterion of the minimum number of misclassified samples with a request of separating the hulls of the groups with a margin as wide as possible. Both SVMs and MLPs overcome the limits of linear discrimination. A famous example for the advantages of the two techniques is the eXclusive OR (XOR) problem, where we wish to form classes of objects having the same parity—even, e.g., (0,0), (1,1) or odd, e.g., (0,1), (1,0). MLPs and SVMs offer effective methods for the identification of nonlinear decision functions, allowing us to resolve classification problems of any complexity provided the data set used during earning is sufficiently large. In Hidden Markov Models (HMMs), we consider observations where their meaning depends on their context. Observations form a causal chain generated by a hidden process. In Bayesian Networks (BNs) we represent conditional (in)dependencies between a set of random variables by a graphical model. In both HMMs and BNs, we aim at identifying models and parameters that explain observations with a highest possible degree of probability.
    Description: Published
    Description: 33-85
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; supervised learning ; Support Vector Machines ; Multilayer Perceptrons ; Hidden Markov Models ; Bayesian Networks ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 6
    Publication Date: 2021-02-01
    Description: Patterns and objects are described by a variety of characteristics, namely features and feature vectors. Features can be numerical, ordinal, and categorical. Patterns can be made up of a number of objects, such as in speech processing. In geophysics, numerical features are the most common ones and we focus on those. The choice of appropriate features requires a priori reasoning about the physical relation between patterns and features. We present strategies for feature identification and procedures suitable for pattern recognition. In time series analysis and image processing, the direct use of raw data is not feasible. Procedures of feature extraction, based on locally encountered characteristics of the data, are applied. Here we present the problem of delineating segments of interest in time series and textures in image processing. In transformations, we “translate” our raw data to a form suitable for learning. In Principal Component Analysis, we rotate the original features to a system of uncorrelated variables, limiting redundancy. Independent Component Analysis follows a similar strategy, transforming our data into variables independent of each other. Fourier transform and wavelet transform are based on the representation of the original data as a series of basis functions—sines and cosines or finite-length wavelets. Redundancy reduction is achieved considering the contributions of the single basis functions. Even though a large number of features help to solve a classification problem, feature vectors with high dimensions pose severe problems. Besides the computational burden, we encounter problems known under the term “curse of dimensionality.” The curse of dimensionality entails the necessity of feature selection and reduction, which includes a priori considerations as well as redundancy reduction. The significance of features may be evaluated with tests, such as Student’s t or Hotelling's T2, and, in more complex problems, with cross-validation methods.
    Description: Published
    Description: 3-13
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; objects ; features ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 7
    Publication Date: 2021-03-09
    Description: Mixed‐mode fluid‐filled cracks represent a common means of fluid transport within the Earth's crust. They often show complex propagation paths which may be due to interaction with crustal heterogeneities or heterogeneous crustal stress. Previous experimental and numerical studies focus on the interplay between fluid over-pressure and external stress but neglect the effect of other crack parameters. In this study, we address the role of crack length on the propagation paths in the presence of an external heterogeneous stress field. We make use of numerical simulations of magmatic dike and hydrofracture propagation, carried out using a two‐dimensional boundary element model, and analogue experiments of air‐filled crack propagation into a transparent gelatin block. We use a 3‐D finite element model to compute the stress field acting within the gelatin block and perform a quantitative comparison between 2‐D numerical simulations and experiments. We show that, given the same ratio between external stress and fluid pressure, longer fluid‐filled cracks are less sensitive to the background stress, and we quantify this effect on fluid‐filled crack paths. Combining the magnitude of the external stress, the fluid pressure, and the crack length, we define a new parameter, which characterizes two end member scenarios for the propagation path of a fluid‐filled fracture. Our results have important implications for volcanological studies which aim to address the problem of complex trajectories of magmatic dikes (i.e., to forecast scenarios of new vents opening at volcanoes) but also have implications for studies that address the growth and propagation of natural and induced hydrofractures.
    Description: Published
    Description: 2064–2081
    Description: 2V. Struttura e sistema di alimentazione dei vulcani
    Description: JCR Journal
    Keywords: Magmatic dykes ; hydrofractures ; Numerical symulations ; Analogue experiments ; 04.08. Volcanology ; 05.05. Mathematical geophysics
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
    Publication Date: 2021-01-07
    Description: https://www.sciencedirect.com/science/article/abs/pii/S0012821X20303897
    Description: Published
    Description: 116445
    Description: 2V. Struttura e sistema di alimentazione dei vulcani
    Description: JCR Journal
    Keywords: 3D model ; multi-source ; elastic medium ; ground deformation ; 04. Solid Earth ; 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
    Publication Date: 2021-02-01
    Description: In this chapter, we deal with a posterior analysis of supervised and unsupervised learning techniques. Concerning supervised learning, we discuss methods of cross-validation and assessment of uncertainty of tests by means of the “Receiver Operation Curve” and the “Kappa-Statistics.” We show the importance of appropriate target information. Furthermore, features are critical; when they are not properly chosen, they fail to describe objects in a unique way. A critical attitude is mandatory to validate the success of an application. A high score of success does not automatically mean that a method is truly effective. At the same time, users should not despair when the desired success is not achieved. A posteriori analysis on the reasons for an apparent failure may provide useful insights into the problem. Targets may not be appropriately defined, features can be inadequate, etc. Problems can be often fixed by adjusting a few choices; sometimes a change of strategy may be necessary to improve results. In unsupervised learning, we ask whether the structures revealed in the data are meaningful. Cluster analysis offers rules giving formal answers to this question; however, such rules are not generally applicable. In some cases, a heuristic approach may be necessary.
    Description: Published
    Description: 237-259
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; a posteriori analysis ; supervised learning ; unsupervised learning ; cross validation ; assessment of uncertainty ; Receiver Operation Curve ; Kappa-Statistics ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 10
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    Elsevier B.V.
    Publication Date: 2021-02-01
    Description: Unsupervised learning is based on the definition of an appropriate metrics defining the similarity of patterns. On the basis of the metrics, we form groups or clusters of patterns following various strategies. In partitioning cluster analysis, we form disjoint clusters. Being faced with data, where clusters still exhibit heterogeneities or subclusters, we may adopt the strategy of hierarchical clustering, which leads to the generation of the so-called dendrograms. In the partitioning strategy, we choose a priori the number of clusters we wish to form, whereas in the hierarchical strategy, the number of clusters depends on the resolution we want to have. Density-based clustering considers local structures of a data set. We consider a unit volume in our data space and derive the density of samples within this volume. Moving toward neighboring volumes, we verify whether the number of samples has dropped below a threshold. If this is the case, we identify a heterogeneity, otherwise we join the neighboring volumes to a common cluster. Self-Organizing Maps (SOMs) provide a way of representing multidimensional data in much lower dimensional spaces than the original data set. The process of reducing the dimensionality of vectors is essentially a data compression technique known as vector quantization. The SOM technique creates a network that stores information in a way that it maintains the topological relationships within the patterns of the data set. Each node of the network represents a number of patterns. Assigning a color code to the nodes, the representation of pattern characteristics with high-dimensional feature vectors becomes extremely effective.
    Description: Published
    Description: 87-124
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; unsupervised learning ; cluster analysis ; Density-based clustering ; Self-Organizing Maps ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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