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  • 1
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    SOM-Based Analysis of Volcanic Rocks: An Application to Somma–Vesuvius and Campi Flegrei Volcanoes (Italy) (2019)
    Springer
    Details
    Publication Date: 2019-12-02
    Description: Algorithms based on artificial intelligence (AI) have had a strong development in recent years in different research fields of earth science such as seismology and volcanology. In particular, they have been applied to the study of the volcanic eruptive products of the recent activity of Mount Etna volcano. This work presents an application of the self-organizing map (SOM) neural networks to perform a clustering analysis on petrographic patterns of rocks of Somma–Vesuvius and Campi Flegrei volcanoes, in the Neapolitan area. The goal is to highlight possible affinity between the magmatic reservoirs of these two volcanic complexes. The SOM is known for its ability to cluster data by using intrinsic similarity measures without any previous information about their distribution. Moreover, it allows an easy understandable data visualization by using a two-dimensional map. The SOM has been tested on a geochemical dataset of 271 samples, consisting of 134 samples of Campi Flegrei eruptions (named CF), 24 samples of Somma–Vesuvius effusive eruptions (VF), 73 samples of Somma–Vesuvius explosive eruptions (VX), and finally 40 samples of “foreign” eruptions (ET), included to verify the neural net classification capability. After a pre-processing phase, applied to have a more appropriate data representation as input for the SOM, each sample has been encoded through a vector of 23 features, containing information about major bulk components, trace elements, and Sr isotopic ratio. The resulting SOM identifies three main clusters, and in particular, the foreign patterns (ET) are well separated from the other ones being mainly grouped in a single node. In conclusion, the obtained results suggest the ability of SOM neural network to associate volcanic rock suites on the basis of their geochemical imprint and can be consistent with the hypothesis that there might be a common magma source beneath the whole Neapolitan area.
    Description: Published
    Description: 55-60
    Description: 3V. Proprietà chimico-fisiche dei magmi e dei prodotti vulcanici
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 2
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    From the detection of monitoring anomalies to the probabilistic forecast of the evolution of volcanic unrest: an entropy-based approach (2024)
    Springer-Nature
    Details
    Publication Date: 2024-01-12
    Description: Owing to the current lack of plausible and exhaustive physical pre-eruptive models, often volcanologists rely on the observation of monitoring anomalies to track the evolution of volcanic unrest episodes. Taking advantage from the work made in the development of Bayesian Event Trees (BET), here we formalize an entropy-based model to translate the observation of anomalies into probability of a specific volcanic event of interest. The model is quite general and it could be used as a stand-alone eruption forecasting tool or to set up conditional probabilities for methodologies like the BET and of the Bayesian Belief Network (BBN). The proposed model has some important features worth noting: (i) it is rooted in a coherent logic, which gives a physical sense to the heuristic information of volcanologists in terms of entropy; (ii) it is fully transparent and can be established in advance of a crisis, making the results reproducible and revisable, providing a transparent audit trail that reduces the overall degree of subjectivity in communication with civil authorities; (iii) it can be embedded in a unified probabilistic framework, which provides an univocal taxonomy of different kinds of uncertainty affecting the forecast and handles these uncertainties in a formal way. Finally, for the sake of example, we apply the procedure to track the evolution of the 1982–1984 phase of unrest at Campi Flegrei.
    Description: Published
    Description: 5
    Description: OSV1: Verso la previsione dei fenomeni vulcanici pericolosi
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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