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Data Processing and Modeling on Volcanic and Seismic Areas

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 16599

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Special Issue Editors

Dr. Alessandro Bonforte

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Guest Editor

Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania – Osservatorio Etneo, Piazza Roma, 2, 95125 Catania, Italy
Interests: ground deformation; volcano geodesy; volcano-tectonics; volcanology; active tectonics
Special Issues, Collections and Topics in MDPI journals

Dr. Flavio Cannavò

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Guest Editor

Istituto Nazionale di Geofisica e Vulcanologia (INGV), Osservatorio Etneo, Piazza Roma 2, 95123 Catania, Italy
Interests: time series analysis; signal processing; data modelling; inverse problems; pattern recognition; machine learning; volcano geodesy; volcano modelling

Special Issue Information

Dear Colleagues,

The recent growth of multi-sensor monitoring networks and satellites with the exponential increase of the amount of spatiotemporal data has revealed an increasingly compelling need to develop data processing, analysis, and modeling tools capable of handling large amounts of data and synthesizing the useful information.
Data processing, analysis, and modeling techniques may allow the identification of significant information to be integrated into volcanic/seismological monitoring systems. The new developed technology is expected to improve operational hazard detection, alerting, and management capabilities.
Technological evolution, as well as the increasing availability of new sensors and platforms and freely available data, pose a new challenge to the scientific community for developing new tools and methods able to integrate and process different information. Emergencies and crises evidence how the rapid response in processing all the available information is also crucial in helping decision makers to mitigate the risk to the exposed population. Prompt data analysis requires a variety of tools, such as event detection, phenomenon recognition and classification, hazard assessment, and episode forecast.
This Special Issue intends to collect new ideas and contributions at the frontier between the fields of data handling, processing, and modeling for volcanic and seismic systems. The primary aspects of any contribution should be novelty and originality.

Specific topics of interest for this Special Issue include, but are not limited to:

Modeling volcano and earthquake deformation;
Spatiotemporal data analysis;
Tools for the diagnosis of unrest patterns using statistical analytics and current advancement of machine learning techniques;
Automatic procedures for data processing, standardization, and rapid integration into a centralized monitoring platform;
Anomaly detection and precursor recognition in data.

Dr. Alessandro Bonforte
Dr. Flavio Cannavò
Guest Editors

Manuscript Submission Information

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Keywords

data management
data handling
archiving
processing
modelling
big data
time series
integration
forecasting
machine learning
data fusion

Published Papers (7 papers)

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Editorial

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3 pages, 192 KiB

Open AccessEditorial

Special Issue “Data Processing and Modeling on Volcanic and Seismic Areas”

by Alessandro Bonforte and Flavio Cannavò

Appl. Sci. 2021, 11(22), 10759; https://doi.org/10.3390/app112210759 - 15 Nov 2021

Viewed by 987

Abstract

Volcanology, seismology and Earth Sciences in general, like all quantitative sciences, are increasingly dependent on the quantity and quality of data acquired [...] Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

Research

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19 pages, 33330 KiB

Open AccessFeature PaperArticle

Combining High- and Low-Rate Geodetic Data Analysis for Unveiling Rapid Magma Transfer Feeding a Sequence of Violent Summit Paroxysms at Etna in Late 2015

by Alessandro Bonforte, Flavio Cannavò, Salvatore Gambino and Francesco Guglielmino

Appl. Sci. 2021, 11(10), 4630; https://doi.org/10.3390/app11104630 - 19 May 2021

Cited by 6 | Viewed by 2517

Abstract

We propose a multi-temporal-scale analysis of ground deformation data using both high-rate tilt and GNSS measurements and the DInSAR and daily GNSS solutions in order to investigate a sequence of four paroxysmal episodes of the Voragine crater occurring in December 2015 at Mt. Etna (Italy). The analysis aimed at inferring the magma sources feeding a sequence of very violent eruptions, in order to understand the dynamics and to image the shallow feeding system of the volcano that enabled such a rapid magma accumulation and discharge. The high-rate data allowed us to constrain the sources responsible for the fast and violent dynamics of each paroxysm, while the cumulated deformation measured by DInSAR and daily GNSS solutions, over a period of 12 days encompassing the entire eruptive sequence, also showed the deeper part of the source involved in the considered period, where magma was stored. We defined the dynamics and rates of the magma transfer, with a middle-depth storage of gas-rich magma that charges, more or less continuously, a shallower level where magma stops temporarily, accumulating pressure due to the gas exsolution. This machine-gun-like mechanism could represent a general conceptual model for similar events at Etna and at all volcanoes. Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

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16 pages, 15458 KiB

Open AccessArticle

Imaging Top of Volcanic Mounds Using Seismic Time- and Depth-Domain Data Processing

by Woohyun Son, Snons Cheong, Changyoon Lee and Moohee Kang

Appl. Sci. 2021, 11(9), 4244; https://doi.org/10.3390/app11094244 - 7 May 2021

Cited by 2 | Viewed by 1717

Abstract

A seismic survey identified a basalt flow that could consist of cap rock of CO₂ storage beneath saline aquifer sediment in the Southern Continental Shelf of Korea. To determine the precise depth of the basalt flow, specific depth-domain data processing of migration velocity analysis (MVA) was applied to the seismic survey data. The accurate depth measurement of a target structure provides crucial information when storing and stabilizing injected CO₂ beneath basalt cap rock. Strong reflections of seismic amplitude at the volcanic mounds were adjusted from the time domain to the exact depth domain by the iterated velocity using MVA. The confidence of the updated velocity was verified by the horizontal alignment of seismic events sorted according to their common reflection point (CRP). The depth difference in volcanic mounds before and after MVA application ranged from 32.5 to 60 m along the vertical axis, showing the eruption shape on the strong-amplitude contour map in detail. The eruption shape of the top of volcanic mounds was verified with spatial continuity in 3D geological interpretation. The presented results provide suitable information that can be used to locate drilling sites and to prepare CO₂ injection. The geological model obtained from both time- and depth-domain processing can significantly influence the calculation of the storage volume and can be useful for history matching studies. Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

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19 pages, 5629 KiB

Open AccessFeature PaperArticle

Implementation of Robust Satellite Techniques for Volcanoes on ASTER Data under the Google Earth Engine Platform

by Nicola Genzano, Francesco Marchese, Marco Neri, Nicola Pergola and Valerio Tramutoli

Appl. Sci. 2021, 11(9), 4201; https://doi.org/10.3390/app11094201 - 5 May 2021

Cited by 6 | Viewed by 2656

Abstract

The RST (Robust Satellite Techniques) approach is a multi-temporal scheme of satellite data analysis widely used to investigate and monitor thermal volcanic activity from space through high temporal resolution data from sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In this work, we present the results of the preliminary RST algorithm implementation to thermal infrared (TIR) data, at 90 m spatial resolution, from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Results achieved under the Google Earth Engine (GEE) environment, by analyzing 20 years of satellite observations over three active volcanoes (i.e., Etna, Shishaldin and Shinmoedake) located in different geographic areas, show that the RST-based system, hereafter named RASTer, detected a higher (around 25% more) number of thermal anomalies than the well-established ASTER Volcano Archive (AVA). Despite the availability of a less populated dataset than other sensors, the RST implementation on ASTER data guarantees an efficient identification and mapping of volcanic thermal features even of a low intensity level. To improve the temporal continuity of the active volcanoes monitoring, the possibility of exploiting RASTer is here addressed, in the perspective of an operational multi-satellite observing system. The latter could include mid-high spatial resolution satellite data (e.g., Sentinel-2/MSI, Landsat-8/OLI), as well as those at higher-temporal (lower-spatial) resolution (e.g., EOS/MODIS, Suomi-NPP/VIIRS, Sentinel-3/SLSTR), for which RASTer could provide useful algorithm’s validation and training dataset. Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

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23 pages, 11845 KiB

Open AccessFeature PaperArticle

Copernicus Sentinel-1 MT-InSAR, GNSS and Seismic Monitoring of Deformation Patterns and Trends at the Methana Volcano, Greece

by Theodoros Gatsios, Francesca Cigna, Deodato Tapete, Vassilis Sakkas, Kyriaki Pavlou and Issaak Parcharidis

Appl. Sci. 2020, 10(18), 6445; https://doi.org/10.3390/app10186445 - 16 Sep 2020

Cited by 19 | Viewed by 3797

Abstract

The Methana volcano in Greece belongs to the western part of the Hellenic Volcanic Arc, where the African and Eurasian tectonic plates converge at a rate of approximately 3 cm/year. While volcanic hazard in Methana is considered low, the neotectonic basin constituting the Saronic Gulf area is seismically active and there is evidence of local geothermal activity. Monitoring is therefore crucial to characterize any activity at the volcano that could impact the local population. This study aims to detect surface deformation in the whole Methana peninsula based on a long stack of 99 Sentinel-1 C-band Synthetic Aperture Radar (SAR) images in interferometric wide swath mode acquired in March 2015–August 2019. A Multi-Temporal Interferometric SAR (MT-InSAR) processing approach is exploited using the Interferometric Point Target Analysis (IPTA) method, involving the extraction of a network of targets including both Persistent Scatterers (PS) and Distributed Scatterers (DS) to augment the monitoring capability across the varied land cover of the peninsula. Satellite geodetic data from 2006–2019 Global Positioning System (GPS) benchmark surveying are used to calibrate and validate the MT-InSAR results. Deformation monitoring records from permanent Global Navigation Satellite System (GNSS) stations, two of which were installed within the peninsula in 2004 (METH) and 2019 (MTNA), are also exploited for interpretation of the regional deformation scenario. Geological, topographic, and 2006–2019 seismological data enable better understanding of the ground deformation observed. Line-of-sight displacement velocities of the over 4700 PS and 6200 DS within the peninsula are from −18.1 to +7.5 mm/year. The MT-InSAR data suggest a complex displacement pattern across the volcano edifice, including local-scale land surface processes. In Methana town, ground stability is found on volcanoclasts and limestone for the majority of the urban area footprint while some deformation is observed in the suburban zones. At the Mavri Petra andesitic dome, time series of the exceptionally dense PS/DS network across blocks of agglomerate and cinder reveal seasonal fluctuation (5 mm amplitude) overlapping the long-term stable trend. Given the steepness of the slopes along the eastern flank of the volcano, displacement patterns may indicate mass movements. The GNSS, seismological and MT-InSAR analyses lead to a first account of deformation processes and their temporal evolution over the last years for Methana, thus providing initial information to feed into the volcano baseline hazard assessment and monitoring system. Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

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19 pages, 6752 KiB

Open AccessArticle

Τhe February-March 2019 Seismic Swarm Offshore North Lefkada Island, Greece: Microseismicity Analysis and Geodynamic Implications

by Anastasios Kostoglou, Vasileios Karakostas, Polyzois Bountzis and Eleftheria Papadimitriou

Appl. Sci. 2020, 10(13), 4491; https://doi.org/10.3390/app10134491 - 29 Jun 2020

Cited by 8 | Viewed by 2106

Abstract

A quite energetic seismic excitation consisting of one main and three additional distinctive earthquake clusters that occurred in the transition area between the Kefalonia Transform Fault Zone (KTFZ) and the continental collision between the Adriatic and Aegean microplates is thoroughly studied after the high-precision aftershocks’ relocation. The activated fault segments are in an area where historical and instrumental data have never claimed the occurrence of a catastrophic (M ≥ 6.0) earthquake. The relocated seismicity initially defines an activated structure extending from the northern segment of the Lefkada branch of KTFZ with the same NNE–SSW orientation and dextral strike slip faulting, and then keeping the same sense of motion, its strike becomes NE–SW and its dip direction NW. This provides unprecedented information on the link between the KTFZ and the collision front and sheds more light on the regional geodynamics. The earthquake catalog, which was especially compiled for this study, starts one year before the occurrence of the M_w5.4 main shock, and adequately provides the proper data source for investigating the temporal variation in the b value, which might be used for discriminating foreshock and aftershock behavior. Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

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Review

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23 pages, 4085 KiB

Open AccessReview

The BrIdge voLcanic LIdar—BILLI: A Review of Data Collection and Processing Techniques in the Italian Most Hazardous Volcanic Areas

by Stefano Parracino, Simone Santoro, Luca Fiorani, Marcello Nuvoli, Giovanni Maio and Alessandro Aiuppa

Appl. Sci. 2020, 10(18), 6402; https://doi.org/10.3390/app10186402 - 14 Sep 2020

Cited by 1 | Viewed by 1946

Abstract

Volcanologists have demonstrated that carbon dioxide (CO₂) fluxes are precursors of volcanic eruptions. Controlling volcanic gases and, in particular, the CO₂ flux, is technically challenging, but we can retrieve useful information from magmatic/geological process studies for the mitigation of volcanic hazards including air traffic security. Existing techniques used to probe volcanic gas fluxes have severe limitations such as the requirement of near-vent in situ measurements, which is unsafe for operators and deleterious for equipment. In order to overcome these limitations, a novel range-resolved DIAL-Lidar (Differential Absorption Light Detection and Ranging) has been developed as part of the ERC (European Research Council) Project “BRIDGE”, for sensitive, remote, and safe real-time CO₂ observations. Here, we report on data collection, processing techniques, and the most significant findings of the experimental campaigns carried out at the most hazardous volcanic areas in Italy: Pozzuoli Solfatara (Phlegraen Fields), Stromboli, and Mt. Etna. The BrIdge voLcanic LIdar—BILLI has successfully obtained accurate measurements of in-plume CO₂ concentration and flux. In addition, wind velocity has also been retrieved. It has been shown that the measurements of CO₂ concentration performed by BILLI are comparable to those carried out by volcanologists with other standard techniques, heralding a new era in the observation of long-term volcanic gases. Full article

(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)

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