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  • 1
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    Field data, numerical simulations and probability analyses to assess lava flow hazards at Mount Etna (2013)
    PANGAEA
    In:  Supplement to: Del Negro, Ciro; Cappello, Annalisa; Neri, Marco; Bilotta, Giuseppe; Hérault, Alexis; Ganci, Gaetana (2013): Lava flow hazards at Mount Etna: constraints imposed by eruptive history and numerical simulations. Scientific Reports, 3, 3493, https://doi.org/10.1038/srep03493
    Details
    Publication Date: 2023-01-13
    Description: Improving lava flow hazard assessment is one of the most important and challenging fields of volcanology, and has an immediate and practical impact on society. Here, we present a methodology for the quantitative assessment of lava flow hazards based on a combination of field data, numerical simulations and probability analyses. With the extensive data available on historic eruptions of Mt. Etna, going back over 2000 years, it has been possible to construct two hazard maps, one for flank and the other for summit eruptions, allowing a quantitative analysis of the most likely future courses of lava flows. The effective use of hazard maps of Etna may help in minimizing the damage from volcanic eruptions through correct land use in densely urbanized area with a population of almost one million people. Although this study was conducted on Mt. Etna, the approach used is designed to be applicable to other volcanic areas.
    Keywords: ETNA; Mount Etna, Sicily, Italia
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    3D Lava flow mapping at Etna volcano from Pléiades-derived DEM differences (2019)
    PANGAEA
    In:  Supplement to: Ganci, Gaetana; Cappello, Annalisa; Bilotta, Giuseppe; Hérault, Alexis; Zago, Vito; Del Negro, Ciro (2019): 3D Lava flow mapping of the 17-25 May 2016 Etna eruption using tri-stereo optical satellite data. Annals of Geophysics, 62(2), 1-6, https://doi.org/10.4401/ag-7875
    Details
    Publication Date: 2023-01-30
    Description: We present two 2-meter Digital Elevation Models (DEMs) of Mount Etna obtained from tri-stereo Pléiades images acquired on 24 December 2015 and 18 July 2016. The 3D processing of the Pléiades imagery was performed using the free and open source MicMac photogrammetric library (http://micmac.ensg.eu) developed by the French IGN (Institut Géographique National). The covered area is almost the same for both the DEMs (about 15 × 15 km) and includes the summit area of Etna volcano and almost all the Valle del Bove area. The presented DEMs are not aligned, but after co-registration, the standard deviation of their height difference was found equal to ∼1.6 m (in an area not covered by volcanic deposits emplaced on May 2016). The DEMs are provided as GeoTIFF raster (dem20151224_2m.tiff and dem20160718_2m.tiff), using the WGS84 datum and the UTM projection, zone 33 North (EPSG 32633). Missing areas are due to snow cover, very low texture and/or terrain shadows. Pléiades data were available through the Space Volcano Observatory with Pléiades (SVOP) project coordinated by Pierre Briole (http://volcano.iterre.fr/svo_projects). We are grateful to Olivier Galland, Luc Girod and Christopher Nuth for their assistance with the use of the MicMac software. This work was developed within the framework of the Laboratory for Technological Advance in Volcano Geophysics (TecnoLab) of the INGV in Catania (Italy) and was partially supported from the "Advanced tools and methods for computational fluid-dynamics"(ATHOS) research programme.
    Keywords: digital elevation model; Etna volcano; File format; File name; File size; Pléiades imagery; satellite remote sensing; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    Digital Elevation Model of Mt Etna updated to 18 December 2015 (2019)
    PANGAEA
    In:  Supplement to: Ganci, Gaetana; Cappello, Annalisa; Bilotta, Giuseppe; Hérault, Alexis; Zago, Vito; Del Negro, Ciro (2018): Mapping Volcanic Deposits of the 2011–2015 Etna Eruptive Events Using Satellite Remote Sensing. Frontiers in Earth Science, 6:83, https://doi.org/10.3389/feart.2018.00083
    Details
    Publication Date: 2023-01-30
    Description: We present a Digital Elevation Model (DEM) of Mount Etna obtained from tri-stereo Pléiades data acquired on 18 December 2015. The 3D processing of the tri-stereo Pléiades 1A imagery was performed using the free and open source MicMac photogrammetric library (http://micmac.ensg.eu) developed by the French IGN (Institut Géographique National), and took advantage of Ground Control Points (GCPs) acquired at Mt Etna. The best result obtained is a 4-meter resolution DEM spanning an area of about 16 × 15 km, which covers the summit craters and a portion of the eastern flank of the volcano, including most of the Valle del Bove area. The highest point of 3,367 m is on the south-west rim of the North-East Crater (NEC), while the South-East Crater (SEC) and the New South-East Crater (NSEC) reach an elevation of 3,336 and 3,325 m, respectively. This 2015 DEM was validated against the 1-meter 2005 DEM resulted from digital photogrammetric mapping (Gwinner at al., 2006). The standard deviation of the height difference between the two DEMs in the area not covered by volcanic deposits, emplaced between 2005 and 2015, is 2.95 m. This difference can be partly due to vegetation and/or urbanization. The DEM is provided as GeoTIFF raster (dem_2015_4m.tiff), using the WGS84 datum and the UTM projection, zone 33 North (EPSG 32633). Missing areas are due to snow cover, very low texture and/or terrain shadows. Pléiades data were available through the Space Volcano Observatory with Pléiades (SVOP) project coordinated by Pierre Briole (http://volcano.iterre.fr/svo_projects). We are grateful to Olivier Galland, Luc Girod and Christopher Nuth for their assistance with the use of the MicMac software.This work was developed within the framework of the Laboratory for Technological Advance in Volcano Geophysics (TecnoLab) of the INGV in Catania (Italy) and was partially supported from the "Advanced tools and methods for computational fluid-dynamics"(ATHOS) research programme.
    Keywords: digital elevation model; Etna volcano; File format; File name; File size; Pléiades imagery; satellite remote sensing; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 4 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 4
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    Etna flank lava flows between 1610 and 2008 (2013)
    PANGAEA
    Details
    Publication Date: 2023-02-12
    Keywords: Area; Date; Duration, number of days; ETNA; Identification; Mount Etna, Sicily, Italia; Output rate; Volume of lava
    Type: Dataset
    Format: text/tab-separated-values, 360 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 5
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    Etna summit lava flows between 1955 and 2012 (2013)
    PANGAEA
    Details
    Publication Date: 2023-02-12
    Keywords: Date; Duration, number of days; ETNA; Location; Mount Etna, Sicily, Italia; Output rate; Volume of lava
    Type: Dataset
    Format: text/tab-separated-values, 665 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 6
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    Preliminary validation of lava benchmark tests on the GPUSPH particle engine (2019)
    Istituto Nazionale di Geofisica e Vulcanologia
    Details
    Publication Date: 2020-11-17
    Description: Lava flow modeling is important in many practical applications, such as the simulation of potential hazard scenarios and the planning of risk mitigation measures, as well as in scientific research to improve our understanding of the physical processes governing the dynamics of lava flow emplacement. Existing predictive models of lava flow behavior include various methods and solvers, each with its advantages and disadvantages. Codes differ in their physical implementations, numerical accuracy, and computational efficiency. In order to validate their efficiency and accuracy, several benchmark test cases for computational lava flow modeling have been established. Despite the popularity gained by the Smoothed Particle Hydrodynamics (SPH) method in Computational Fluid Dynamics (CFD), very few validations against lava flows have been successfully conducted. At the Tecnolab of INGVCatania we designed GPUSPH, an implementation of the weakly-compressible SPH method running fully on Graphics Processing Units (GPUs). GPUSPH is a particle engine capable of modeling both Newtonian and non-Newtonian fluids, solving the three-dimensional Navier– Stokes equations, using either a fully explicit integration scheme, or a semi-implicit scheme in the case of highly viscous fluids. Thanks to the full coupling with the thermal equation, and its support for radiation, convection and phase transition, GPUSPH can be used to faithfully simulate lava flows. Here we present the preliminary results obtained with GPUSPH for a benchmark series for computational lava-flow modeling, including analytical, semi-analytical and experimental problems. The results are reported in terms of correctness and performance, highlighting the benefits and the drawbacks deriving from the use of SPH to simulate lava flows.
    Description: Published
    Description: VO224
    Description: 5V. Processi eruttivi e post-eruttivi
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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    PAPER (OA)
  • 7
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    Satellite and Ground Remote Sensing Techniques to Trace the Hidden Growth of a Lava Flow Field: The 2014-15 Effusive Eruption at Fogo Volcano (Cape Verde) (2018)
    Details
    Publication Date: 2021-06-16
    Description: Fogo volcano erupted in 2014–2015 producing an extensive lava flow field in the summit caldera that destroyed two villages, Portela and Bangaeira. The eruption started with powerful explosive activity, lava fountains, and a substantial ash column accompanying the opening of an eruptive fissure. Lava flows spreading from the base of the eruptive fissure produced three arterial lava flows. By a week after the start of the eruption, a master lava tube had already developed within the eruptive fissure and along the arterial flow. In this paper, we analyze the emplacement processes based on observations carried out directly on the lava flow field, remote sensing measurements carried out with a thermal camera, SO2 fluxes, and satellite images, to unravel the key factors leading to the development of lava tubes. These were responsible for the rapid expansion of lava for the ~7.9 km length of the flow field, as well as the destruction of the Portela and Bangaeira villages. The key factors leading to the development of tubes were the low topography and the steady magma supply rate along the arterial lava flow. Comparing time-averaged discharge rates (TADR) obtained from satellite and Supply Rate (SR) derived from SO2 flux data, we estimate the amount and timing of the lava flow field endogenous growth, with the aim of developing a tool that could be used for hazard assessment and risk mitigation at this and other volcanoes.
    Description: This research received no external funding.
    Description: Published
    Description: 1115
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: JCR Journal
    Keywords: Fogo volcano ; lava flow inflation ; lava tubes ; time averaged discharge rate ; magma supply rate ; volcanic hazard ; remote sensing monitoring ; effusive eruption
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
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    Overflows and Pyroclastic Density Currents in March-April 2020 at Stromboli Volcano Detected by Remote Sensing and Seismic Monitoring Data (2020)
    MDPI
    Details
    Publication Date: 2020-09-16
    Description: Between 28 March and 1 April 2020, Stromboli volcano erupted, with overflows from the NE crater rim spreading along the barren Sciara del Fuoco slope and reaching the sea along the NW coast of the island. Poor weather conditions did not allow a detailed observation of the crater zone through the cameras monitoring network, but a clear view of the lower slope and the flows expanding in the area allowed us to characterize the flow features. This evidence was integrated with satellite, GBInSAR, and seismic data, thus enabling a reconstruction of the whole volcanic event, which involved several small collapses of the summit cone and the generation of pyroclastic density currents (PDCs) spreading along the slope and on the sea surface. Satellite monitoring allowed for the mapping of the lava flow field and the quantification of the erupted volume, and GBInSAR continuous measurements detected the crater widening and the deflation of the summit cone caused by the last overflow. The characterization of the seismicity made it possible to identify the signals that are associated with the propagation of PDCs along the volcano flank and, for the first time, to recognize the signal that is produced by the impact of the PDCs on the coast.
    Description: This work has been financially supported by the “Presidenza del Consiglio dei Ministri—Dipartimento della Protezione Civile” (Presidency of the Council of Ministers–Department of Civil Protection) (DPC-UNIFI Agreement 2019–2021; Scientific Responsibility: N.C.); this publication, however, does not necessarily reflect the position and the official policies of the Department. Additional funds for paper publication have been provided by INGV-OE.
    Description: Published
    Description: 3010
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: JCR Journal
    Keywords: Stromboli ; Volcanic hazard ; Volcanic hazard assessment ; Multidisciplinary data integration ; Stromboli Volcano monitoring ; 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
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    Improving cloud detection with imperfect satellite images using an artificial neural network approach (2020)
    Details
    Publication Date: 2020-11-17
    Description: The past few decades have seen an explosion of satellite remote sensing techniques for the monitoring of volcanic thermal features. Here, we propose an artificial neural network approach for improving the cloud detection through imperfect multispectral satellite images analysis. The cloud detection algorithm has been tested on a data set of MSGSEVIRI images acquired over the area of Etna volcano in Sicily (Italy) before and during the 2008 eruption. Results show that this approach is robust in terms of percentage of correctly classified pixels.
    Description: Published
    Description: 1443-1447
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: N/A or not JCR
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
    Location Call Number Limitation Availability
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  • 10
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    Living at the edge of an active volcano: Risk from lava flows on Mt. Etna (2020)
    Geological society of America
    Details
    Publication Date: 2020-09-07
    Description: Lava flows represent the greatest threat by far to exposed population and infrastructure on Mt. Etna, Italy. The increasing exposure of a larger population, which has almost tripled in the area around Mt. Etna during the past 150 years, has resulted from poor assessment of the volcanic hazard and inappropriate land use in vulnerable areas. Here we quantify the lava flow risk on the flanks of Mt. Etna volcano using a Geographic Information System (GIS)-based approach that integrates the hazard with the exposure of elements at stake. The hazard, which shows the long-term probability related to lava flow inundation, is obtained by combining three different kinds of information: the spatiotemporal probability of new flank eruptive vents opening in the future, the event probability associated with classes of expected eruptions, and the overlapping of lava flow paths simulated by the MAGFLOW model. Data including all exposed elements were gathered from institutional web portals and high-resolution satellite imagery and organized in four thematic layers: population, buildings, service networks, and land use. The total exposure is given by a weighted linear combination of the four thematic layers, where weights are calculated using the Analytic Hierarchy Process (AHP). The resulting risk map shows the likely damage caused by a lava flow eruption and allows rapid visualization of the areas subject to the greatest losses if a flank eruption were to occur on Mt. Etna. The highest risk is found in the southeastern flank due to the combination of high hazard and population density.
    Description: Published
    Description: 1615–1625
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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