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14 pages, 11419 KiB  
Article
Large-Depth Ground-Penetrating Radar for Investigating Active Faults: The Case of the 2017 Casamicciola Fault System, Ischia Island (Italy)
by Valeria Paoletti, Donato D’Antonio, Giuseppe De Natale, Claudia Troise and Rosa Nappi
Appl. Sci. 2024, 14(15), 6460; https://doi.org/10.3390/app14156460 - 24 Jul 2024
Viewed by 702
Abstract
We conducted large-depth Ground-Penetrating Radar investigations of the seismogenic Casamicciola fault system at the volcanic island of Ischia, with the aim of constraining the source characteristics of this active and capable fault system. On 21 August 2017, a shallow (hypocentral depth of 1.2 [...] Read more.
We conducted large-depth Ground-Penetrating Radar investigations of the seismogenic Casamicciola fault system at the volcanic island of Ischia, with the aim of constraining the source characteristics of this active and capable fault system. On 21 August 2017, a shallow (hypocentral depth of 1.2 km), moderate (Md = 4.0) earthquake hit the island, causing severe damage and two fatalities. This was the first damaging earthquake recorded on the volcanic island of Ischia from the beginning of the instrumental era. Our survey was performed using the Loza low-frequency (15–25 MHz) GPR system calibrated by TDEM results. The data highlighted variations in the electromagnetic signal due to the presence of contacts, i.e., faults down to a depth larger than 100 m below the surface. These signal variations match with the position of the synthetic and antithetic active fault system bordering the Casamicciola Holocene graben. Our study highlights the importance of employing large-depth Ground-Penetrating Radar geophysical techniques for investigating active fault systems not only in their shallower parts, but also down to a few hundred meters’ depth, providing a contribution to the knowledge of seismic hazard studies on the island of Ischia and elsewhere. Full article
(This article belongs to the Special Issue New Challenges in Seismic Hazard Assessment)
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Figure 1

Figure 1
<p>Location of our geophysical survey, Ischia Island (Italy): ISH1, ISH2, ISH3, ISH4 are the GPR profiles (black lines); TDEM1-7 are the time-domain electromagnetic measurements (black squares) across the synthetic and antithetic active faults system of Holocene Casamicciola graben (red lines, marks on down-thrown side). Geology and active faults are from Vezzoli (1988) [<a href="#B10-applsci-14-06460" class="html-bibr">10</a>] and Tibaldi and Vezzoli (1998) [<a href="#B11-applsci-14-06460" class="html-bibr">11</a>]. The co-seismic ruptures of the 2017 earthquake (yellow lines) are from Nappi et al. (2018) [<a href="#B3-applsci-14-06460" class="html-bibr">3</a>]. The 21 August 2017 mainshock (the yellow large star) is from <a href="https://terremoti.ov.ingv.it/gossip/ischia/2017/index.html" target="_blank">https://terremoti.ov.ingv.it/gossip/ischia/2017/index.html</a> (accessed 1 July 2024) [<a href="#B12-applsci-14-06460" class="html-bibr">12</a>]; historical earthquakes (red circles) are from Selva et al. (2021) [<a href="#B13-applsci-14-06460" class="html-bibr">13</a>].</p>
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<p>Acquisition of GPR data by the Loza system at Ischia Island.</p>
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<p>Row data measured along profiles ISH1, ISH2 (25 MHz and 100 MHz), ISH3 (25 MHz), and ISH4 (25 MHz) with relative average A-scan. Note that the 100 MHz section is represented with exaggeration of the vertical scale [<a href="#B29-applsci-14-06460" class="html-bibr">29</a>].</p>
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<p>Processed data for the ISH1 LDGPR profile (15 MHz). Here and in <a href="#applsci-14-06460-f005" class="html-fig">Figure 5</a>, <a href="#applsci-14-06460-f006" class="html-fig">Figure 6</a> and <a href="#applsci-14-06460-f007" class="html-fig">Figure 7</a>, the dark blue-line rectangles highlight the variations of the electromagnetic response recorded along profiles due to the presence of geological structures such as faults. The solid white lines show the layers detected by LDGPR data. The light-blue and black lines identify the electro-layers (with different resistivity) from our TDEM data and previous TDEM data (Nardone et al., 2023 [<a href="#B29-applsci-14-06460" class="html-bibr">29</a>]), respectively.</p>
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<p>Processed data for the ISH2 LDGPR profile (25 MHz). Refer to the caption of <a href="#applsci-14-06460-f004" class="html-fig">Figure 4</a> for explanation [<a href="#B29-applsci-14-06460" class="html-bibr">29</a>].</p>
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<p>Processed data for the ISH3 LDGPR profile (25 MHz). Refer to the caption of <a href="#applsci-14-06460-f004" class="html-fig">Figure 4</a> for explanation [<a href="#B29-applsci-14-06460" class="html-bibr">29</a>].</p>
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<p>Processed data for the ISH4 LDGPR profile (25 MHz). Refer to the caption of <a href="#applsci-14-06460-f004" class="html-fig">Figure 4</a> for explanation [<a href="#B29-applsci-14-06460" class="html-bibr">29</a>].</p>
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<p>Q-factor computed on a portion of the ISH2 section acquired using a 100 MHz antenna. The Q-factor outcome is overlaid on row data (transparent) and shows a sub-vertical contact dipping towards the north.</p>
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<p>Outcome of our LDGPR survey: the white lines are the surface projections of faults found by the LDGPR survey. The blue box includes the portion of the ISH2 profile studied by Q-factor analysis (<a href="#applsci-14-06460-f008" class="html-fig">Figure 8</a>). Active faults are from Vezzoli (1998) [<a href="#B10-applsci-14-06460" class="html-bibr">10</a>] and Tibaldi and Vezzoli (1998) [<a href="#B11-applsci-14-06460" class="html-bibr">11</a>]. The co-seismic ruptures of the 2017 earthquake are from Nappi et al. (2018) [<a href="#B3-applsci-14-06460" class="html-bibr">3</a>]. The 21 August 2017 mainshock (yellow star) is from <a href="https://terremoti.ov.ingv.it/gossip/ischia/2017/index.html" target="_blank">https://terremoti.ov.ingv.it/gossip/ischia/2017/index.html</a>, accessed on 13 July 2024 [<a href="#B12-applsci-14-06460" class="html-bibr">12</a>].</p>
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35 pages, 19581 KiB  
Article
Improving the Accuracy of Digital Terrain Models Using Drone-Based LiDAR for the Morpho-Structural Analysis of Active Calderas: The Case of Ischia Island, Italy
by Argelia Silva-Fragoso, Gianluca Norini, Rosa Nappi, Gianluca Groppelli and Alessandro Maria Michetti
Remote Sens. 2024, 16(11), 1899; https://doi.org/10.3390/rs16111899 - 25 May 2024
Cited by 1 | Viewed by 1207
Abstract
Over the past two decades, the airborne Light Detection and Ranging (LiDAR) system has become a useful tool for acquiring high-resolution topographic data, especially in active tectonics studies. Analyzing Digital Terrain Models (DTMs) from LiDAR exposes morpho-structural elements, aiding in the understanding of [...] Read more.
Over the past two decades, the airborne Light Detection and Ranging (LiDAR) system has become a useful tool for acquiring high-resolution topographic data, especially in active tectonics studies. Analyzing Digital Terrain Models (DTMs) from LiDAR exposes morpho-structural elements, aiding in the understanding of fault zones, among other applications. Despite its effectiveness, challenges persist in regions with rapid deformation, dense vegetation, and human impact. We propose an adapted workflow transitioning from the conventional airborne LiDAR system to the usage of drone-based LiDAR technology for higher-resolution data acquisition. Additionally, drones offer a more cost-effective solution, both in an initial investment and ongoing operational expenses. Our goal is to demonstrate how drone-based LiDAR enhances the identification of active deformation features, particularly for earthquake-induced surface faulting. To evaluate the potential of our technique, we conducted a drone-based LiDAR survey in the Casamicciola Terme area, north of Ischia Island, Italy, known for the occurrence of destructive shallow earthquakes, including the 2017 Md = 4 event. We assessed the quality of our acquired DTM by comparing it with existing elevation datasets for the same area. We discuss the advantages and limitations of each DTM product in relation to our results, particularly when applied to fault mapping. By analyzing derivative DTM products, we identified the fault scarps within the Casamicciola Holocene Graben (CHG) and mapped its structural geometry in detail. The analysis of both linear and areal geomorphic features allowed us to identify the primary factors influencing the current morphological arrangement of the CHG area. Our detailed map depicts a nested graben formed by two main structures (the Maio and Sentinella faults) and minor internal faults (the Purgatorio and Nizzola faults). High-resolution DEMs acquired by drone-based LiDAR facilitated detailed studies of the geomorphology and fault activity. A similar approach can be applied in regions where the evidence of high slip-rate faults is difficult to identify due to vegetation cover and inaccessibility. Full article
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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Figure 1

Figure 1
<p>Location of study area. For the purpose of this work, we indicate only the Quaternary volcanic units and the faults with Quaternary activity reported by Sbrana et al. (2021) [<a href="#B26-remotesensing-16-01899" class="html-bibr">26</a>], Aucelli et al. (2022) [<a href="#B27-remotesensing-16-01899" class="html-bibr">27</a>], Natale et al. (2019) [<a href="#B28-remotesensing-16-01899" class="html-bibr">28</a>], and Chiocci et al. (2023) [<a href="#B29-remotesensing-16-01899" class="html-bibr">29</a>].</p>
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<p>Geology of Ischia Island. The geological units are grouped according to the volcanic evolution of the area (Tibaldi and Vezzoli, 1998, and Sbrana et al., 2018) [<a href="#B30-remotesensing-16-01899" class="html-bibr">30</a>,<a href="#B31-remotesensing-16-01899" class="html-bibr">31</a>]. The fault structures outside the study area (black dotted square) are based on Vezzoli (1988); Nappi et al. (2010), and Sbrana et al. (2018) [<a href="#B31-remotesensing-16-01899" class="html-bibr">31</a>,<a href="#B32-remotesensing-16-01899" class="html-bibr">32</a>,<a href="#B33-remotesensing-16-01899" class="html-bibr">33</a>]. The 2017 epicentral location (blue star) is taken from De Novellis et al. (2018) [<a href="#B34-remotesensing-16-01899" class="html-bibr">34</a>], and the historical earthquakes from Selva et al. (2021) [<a href="#B35-remotesensing-16-01899" class="html-bibr">35</a>]. We show the resulting fault structures for the Casamicciola Holocene Graben (CHG) described in this work (indicated with a blue arrow).</p>
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<p>Study area. (<b>A</b>) Area covered by drone-based LiDAR survey. Each rectangle shows the area covered by a single strip. (<b>B</b>) Scarp partially covered by Mediterranean vegetation (Maquis scrubland) characterizes vegetated land coverage. (<b>C</b>) View to the northern flank of Mt. Epomeo; the picture displays the densely vegetated coverage.</p>
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<p>Structural survey using UAV LiDAR flowchart for carrying out drone-based LiDAR survey. The general workflow consists of five main processes: (1) point cloud data collection, (2) PPK correction, and cloud calculation, (3) LiDAR strip adjustment, (4) point cloud filtering, and (5) morpho-structural analysis.</p>
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<p>Profiles of LiDAR point cloud data. (<b>A</b>) The LiDAR data revealed the presence of a canyon in the Purgatorio area formed by a N-dipping fault structure parallel to the synthetic fault structures at the base of Mt. Epomeo. The vegetation in this area masks completely the presence of the structure. (<b>B</b>) Profiles 1 and 2 show the penetration of the LiDAR sensor to capture elevation data from bare earth below the vegetation. The morphological expression is hidden in the DSM (<b>C</b>), and exposed in the DTM (<b>D</b>). (<b>E</b>) Identification of scarp covered by dense vegetation between Campomanno and Bagni sites. (<b>F</b>) The ground points show the presence of a hill. The location of this profile is shown in the DSM (<b>G</b>) and in the DTM (<b>H</b>). The dotted yellow lines in (<b>A</b>,<b>E</b>) show an approximation of the profile location.</p>
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<p>Scatter plots depicting the correlation between the extracted drone-based LiDAR with 20 cm resolution and the available DEMs for the study area. (<b>A</b>) DEM obtained from an airborne LiDAR sensor available in the Geoportale Nazionale Italiano. (<b>B</b>) DEM obtained from a spaceborne LiDAR sensor as a part of the GEDI program. (<b>C</b>) DEM obtained from a Shuttle Radar Topography Mission with one arc of resolution. (<b>D</b>) EU-DEM v1.0 combines SRTM and ASTER data. (<b>E</b>) DEM belongs to tTINItaly program. We assumed that there was an offset between both observations as y = x + offset (expressed in centimeters). In general, all the comparisons show a very strong correlation coefficient R<sup>2</sup> &gt; 0.99.</p>
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<p>Comparison between shaded relief maps generated from the drone-based LiDAR DEMand the DEM datasets available for the study area. Panels A and B show different scales. (<b>A</b>) Shaded relief map from drone-based LiDAR (20 cm). (<b>B</b>,<b>C</b>) Shaded relief from 2 m-resolution airborne-based LiDAR DEM. (<b>D</b>) Shaded relief map from spaceborne-based LiDAR DEM at 30 m resolution. (<b>E</b>) Shaded relief map at 30 m resolution derived from SRTM DEM. (<b>F</b>) Shaded relief map at 25 m resolution extracted from European DEM v1.0. (<b>G</b>) Shaded relief map at 10 m resolution derived from TINItaly DEM.</p>
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<p>Relative comparison between airborne-based LiDAR DEM with 2 m resolution and drone-based LiDAR DEM with 20 cm resolution. The panel in the corner shows a scatter plot of the RMSE distribution according to the slope values.</p>
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<p>Morphological analysis based on derived products from drone LiDAR DEM. (<b>A</b>) Distribution of volcanic and epiclastic deposits, (<b>B</b>) slope map, (<b>C</b>) aspect map. All the maps are superimposed on a shaded image (sunlight from the northwest). For panels (<b>A</b>–<b>C</b>), the black dotted line indicates the area of study covered by the drone LiDAR system; data outside correspond with products derived from the airborne LiDAR DEM at 2 m resolution. In each panel, the morphological domains are shown. The location of these maps is shown in <a href="#remotesensing-16-01899-f002" class="html-fig">Figure 2</a>.</p>
Full article ">Figure 9 Cont.
<p>Morphological analysis based on derived products from drone LiDAR DEM. (<b>A</b>) Distribution of volcanic and epiclastic deposits, (<b>B</b>) slope map, (<b>C</b>) aspect map. All the maps are superimposed on a shaded image (sunlight from the northwest). For panels (<b>A</b>–<b>C</b>), the black dotted line indicates the area of study covered by the drone LiDAR system; data outside correspond with products derived from the airborne LiDAR DEM at 2 m resolution. In each panel, the morphological domains are shown. The location of these maps is shown in <a href="#remotesensing-16-01899-f002" class="html-fig">Figure 2</a>.</p>
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<p>Scarp profiles and morphometric analysis. Same colors indicate portion of same scarp in different profiles. Locations are indicated in <a href="#remotesensing-16-01899-f009" class="html-fig">Figure 9</a>B,C. Before the extraction of the topographic and slope profiles, the original DTM at 20 cm resolution was filtered to analyze only the data frequency representative of natural landforms. Further details of this process are shown in <a href="#remotesensing-16-01899-f011" class="html-fig">Figure 11</a> and discussed in <a href="#sec5dot2-remotesensing-16-01899" class="html-sec">Section 5.2</a>.</p>
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<p>Effect of smoothing filtering. (<b>A</b>) A topographic profile showing the terrain details and anthropic features’ influence (upper), and a topographic profile after a focal statistic moving window of 10 × 10 m. (<b>B</b>) The slope profiles show how the different filters display the slope information at different scales.</p>
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<p>A volcano–tectonic map of the Casamicciola Holocene Graben area on a shaded relief image derived from the 20 cm-resolution DEM (illuminated from the NW). The area covered by the drone-based LiDAR survey is limited by the dotted black lines; the remnant belongs to the 2 m-resolution DEM available on the Geoportale Nazionale Italiano. The historical earthquakes were taken from Selva et al. (2021) [<a href="#B31-remotesensing-16-01899" class="html-bibr">31</a>] and references therein. The earthquakes are reported in Mw, except the seismic event of 2017, reported in Md. We use Mw obtained from macroseismic data for historical events following Selva et al. (2021) [<a href="#B31-remotesensing-16-01899" class="html-bibr">31</a>]. The topographic profiles are displayed in <a href="#remotesensing-16-01899-f013" class="html-fig">Figure 13</a>. The focal mechanism of the 2017 earthquake is taken from De Novellis et al. (2018) [<a href="#B34-remotesensing-16-01899" class="html-bibr">34</a>].</p>
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<p>Topographic profiles across the studied area. The location of the historical earthquakes approximated. Traces of the topographic profiles are shown in <a href="#remotesensing-16-01899-f012" class="html-fig">Figure 12</a>.</p>
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28 pages, 12542 KiB  
Article
Infrastructure Impact Assessment through Multi-Hazard Analysis at Different Scales: The 26 November 2022 Flood Event on the Island of Ischia and Debris Management
by Sergio Cappucci, Maurizio Pollino, Maria Giuseppina Farrace, Lorenzo Della Morte and Valerio Baiocchi
Land 2024, 13(4), 500; https://doi.org/10.3390/land13040500 - 11 Apr 2024
Cited by 1 | Viewed by 1209
Abstract
A multi-hazard analysis (seismic, landslide, flood) is conducted to verify the impact on the road network. The ENEA CIPCast platform is an innovative Decision Support System (DSS) that is used to implement the analyses using GIS. Using analytical and geoprocessing tools, the hazards [...] Read more.
A multi-hazard analysis (seismic, landslide, flood) is conducted to verify the impact on the road network. The ENEA CIPCast platform is an innovative Decision Support System (DSS) that is used to implement the analyses using GIS. Using analytical and geoprocessing tools, the hazards were assessed and mapped. The overlapping of different geospatial layers allowed the implementation of a specific hazard map for the road network. Multi-hazard values were obtained using an appropriate matrix of single values, which were classified, and then summarized into four classes of values. The analyses were conducted at the regional (Campania region), provincial (Metropolitan City of Naples), and local scales (island of Ischia and municipality of Casamicciola Terme). In particular, the landslide event that struck Ischia island on 26 November 2022 and the municipality of Casamicciola Terme was considered as a case study to determine the impact on the road network, infrastructures, buildings, and jeopardizing inter-municipal connections. The results are mainly visualized through map processing and statistical summaries of the data. The management of the landslide debris, which can contain a multitude of fractions (waste, biomass and vegetation, sludge, soil, and rocks transported downstream by water), was also explored. This is a frontier issue for which international manuals and guidelines, as well as national and emergency acts, have been examined. A specific protocol for the sustainable management of the debris generated by floods and landslides is needed, and discussed in the present paper, to overcome emergencies after catastrophic events. Full article
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Figure 1
<p>Study area.</p>
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<p>Workflow implemented for the CIPCast platform. The multi-tier architecture of CIPCast is divided by Step (from 1. to 4.).</p>
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<p>Workflow of the multi-hazard analysis process (Step 1.) (Pollino et al. (2022) [<a href="#B45-land-13-00500" class="html-bibr">45</a>], modified).</p>
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<p>Description of Step 1.1. of <a href="#land-13-00500-f003" class="html-fig">Figure 3</a>: from a single-hazard map to a multi-hazard map of the Area of Interest (state, region, province, municipality) (Pollino et al. (2022) [<a href="#B45-land-13-00500" class="html-bibr">45</a>], modified).</p>
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<p>Description of Step 1.2. and Step 1.3. of <a href="#land-13-00500-f003" class="html-fig">Figure 3</a>: intersection of the CI under consideration with the multi-hazard map to create an overall CI multi-hazard map for the Area of Interest (state, region, province, municipality) (Pollino et al. (2022) [<a href="#B45-land-13-00500" class="html-bibr">45</a>], modified).</p>
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<p>Elaboration of the multi-hazard map of the road network CI of Ischia (40°45′ N–13°55′ E). The multi-hazard MIV scale is presented using a red scale, by increasing intensity (only values present in the area under examination).</p>
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<p>Elaboration of the areal extension of the 26 November 2022 event of Casamicciola Terme with contour lines (40°45′ N–13°55′ E).</p>
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<p>Elaboration of the 26 November 2022 debris-flow event of Casamicciola Terme: overlapping PAI 2021 flooding map (only hazard classes present in the area under examination) and the event-struck area (40°45′ N–13°55′ E).</p>
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<p>QGIS visualization of the Casamicciola 26 November 2022 debris-flow event: overlapping layers of the struck area, the Ischia and Casamicciola boundaries, and the PAI 2021 flooding map (OSM basemap) with the Casamicciola built-up area (40°45′ N–13°55′ E).</p>
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<p>Elaboration of the debris flow struck area overlapping the multi-hazard map of the overall Casamicciola road network CI. The multi-hazard MIV scale is presented using a red-yellow-green scale, by increasing intensity (only values present in the area under examination).</p>
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<p>Elaboration the portion of the roads within the area struck by the event of Casamicciola Terme (40°45′ N–13°55′ E). The multi-hazard MIV scale is here presented using a red-yellow-green scale, by increasing intensity.</p>
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<p>Visualization of the 26 November 2022 landslide and the Casamicciola road network thematized by hierarchical level using the WebGIS interface of the CIPCast platform (ENEA): e.g., the Casamicciola boundary; the 26 November 2022 event area; the built-up area; and the road network and its multi-hazard values. The struck area is overlapped on the Google Satellite basemap. Legend size has been emphasized (the study area is located at 40°45′ N–13°55′ E).</p>
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<p>Sediment management of the Casamicciola Harbor. The green box represents the dumping area of the dredged sediment (From: Sutera, 2023 [<a href="#B104-land-13-00500" class="html-bibr">104</a>]).</p>
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<p>The debris of the mudflow into the riverbed (<b>a</b>,<b>b</b>), along the road network (<b>c</b>–<b>e</b>) down to the Port of Casamicciola (<b>f</b>), after the 26 November 2022 event. Photo of Prof. V. Baiocchi; M.G. Farrace; ANSA (15.e; [<a href="#B125-land-13-00500" class="html-bibr">125</a>]).</p>
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<p>Graphical representation of the debris composition and management (Grey: metals and minerals; Black: tarmac; Brown: lithoids; Green: Vegetation; Purples: vehicle and liquid wastes; Red: hazardous wastes). Among the artistic and architectural heritage, the personal effects are sometimes included.</p>
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14 pages, 7301 KiB  
Article
Geomorphological Evolution of Volcanic Cliffs in Coastal Areas: The Case of Maronti Bay (Ischia Island)
by Luigi Massaro, Giovanni Forte, Melania De Falco and Antonio Santo
Geosciences 2023, 13(10), 313; https://doi.org/10.3390/geosciences13100313 - 17 Oct 2023
Cited by 3 | Viewed by 1996
Abstract
The morphoevolution of coastal areas is due to the interactions of multiple continental and marine processes that define a highly dynamic environment. These processes can occur as rapid catastrophic events (e.g., landslides, storms, and coastal land use) or as slower continuous processes (i.e., [...] Read more.
The morphoevolution of coastal areas is due to the interactions of multiple continental and marine processes that define a highly dynamic environment. These processes can occur as rapid catastrophic events (e.g., landslides, storms, and coastal land use) or as slower continuous processes (i.e., wave, tidal, and current actions), creating a multi-hazard scenario. Maronti Bay (Ischia Island, Southern Italy) can be classified as a pocket beach that represents an important tourist and environmental area for the island, although it has been historically affected by slope instability, sea cliff recession, and coastal erosion. In this study, the historical morphoevolution of the shoreline was analysed by means of a dataset of aerial photographs and cartographic information available in the literature over a 25-year period. Furthermore, the role of cliff recession and its impact on the beach was also explored, as in recent years, the stability condition of the area was worsened by the occurrence of a remarkable landslide in 2019. The latter was reactivated following a cloudburst on the 26th of November 2022 that affected the whole Island and was analysed with the Dem of Difference technique. It provided an estimate of the mobilised volumes and showed how the erosion and deposition areas were distributed and modified by wave action. The insights from this research can be valuable in developing mitigation strategies and protective measures to safeguard the surrounding environment and ensure the safety of residents and tourists in this multi-hazard environment. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring of Geomorphological Hazards)
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Figure 1
<p>Aerial photograph of the 26th November 2022 landslide with the affected buildings on the cliff top.</p>
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<p>Topographic map (2015) of Maronti Bay with the location of the study area and the 2020 landslide body.</p>
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<p>Measurement lines (T1–T10) disposed along the cliff and the beach edges for the measurement of their progradation/regression evolution. Example of the 2022 orthophoto.</p>
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<p>Cliff retreat rate (cm yr<sup>−1</sup>) measured on the 10 measurement lines at different time intervals. (<b>a</b>) Cumulative cliff retreat rate for each transect through the time; (<b>b</b>) average cliff retreat rate for each time interval.</p>
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<p>Beach width variation rate (m yr<sup>−1</sup>) measured on the 10 measurement lines at different time intervals. (<b>a</b>) Cumulative beach width variation rate for each transect through the time; (<b>b</b>) average beach width variation rate for each time interval. The positive values indicate progradation, and the negative values indicate regression.</p>
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<p>Orthophotos of the November 2022 landslide area with the landslide perimeter and the results of the DoD analyses between (<b>a</b>) 2009–2022 and (<b>b</b>) 2022–2023 DEMs.</p>
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<p>Absolute cliff and beach width variations from 1998 to 2023.</p>
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<p>Wind direction and intensity recorded at Napoli monitoring station in the 2010–2023 time interval (ISPRA).</p>
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19 pages, 8525 KiB  
Article
Experimental and Numerical Analysis of the Efficacy of a Real Downhole Heat Exchanger
by Muhammad Asad, Vincenzo Guida and Alessandro Mauro
Energies 2023, 16(19), 6783; https://doi.org/10.3390/en16196783 - 23 Sep 2023
Viewed by 898
Abstract
In this paper, a three-dimensional (3D) numerical model based on the finite element method (FEM) is developed to determine the fluid flow and heat transfer phenomena in a real multi-tube downhole heat exchanger (DHE), designed ad hoc for the present application, considering natural [...] Read more.
In this paper, a three-dimensional (3D) numerical model based on the finite element method (FEM) is developed to determine the fluid flow and heat transfer phenomena in a real multi-tube downhole heat exchanger (DHE), designed ad hoc for the present application, considering natural convection inside a geothermal reservoir. The DHE has been effectively installed and tested on the island of Ischia, in southern Italy, and the measurements have been used to validate the model. In particular, the authors analyze experimentally and numerically the behavior of the DHE based on the outlet temperature of the working fluid, thermal power, overall heat transfer coefficient, and efficiency. Furthermore, the influence of the degree of salinity on the performance of the DHE has been studied, observing that it degrades with the increase in the degree of salinity. The results show that the DHE allows to exchange more than 40 kW with the ground, obtaining overall heat transfer coefficient values larger than 450 W/m2 K. At the degree of salinity of 180 ppt, a decrease in the efficiency of the DHE of more than 8% is observed. Full article
(This article belongs to the Section H2: Geothermal)
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<p>Island of Ischia in Southern Italy.</p>
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<p>Downhole heat exchanger before installation in the geothermal well.</p>
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<p>Dry cooler (<b>right</b>) and management and control apparatus (<b>left</b>).</p>
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<p>Illustration of the experimental device installed on the island of Ischia.</p>
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<p>Well casing (<b>left</b>) and filtering tube (<b>right</b>).</p>
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<p>Upper head of DHE.</p>
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<p>Lower head of DHE.</p>
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<p>Installation of the DHE inside the geothermal well.</p>
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<p>Geometry of the DHE.</p>
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<p>Computational domain and boundary conditions.</p>
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<p>Details of the computational grid at the bottom (left) and top (right) of the DHE.</p>
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<p>Mesh sensitivity analysis and computational time for five grids.</p>
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<p>Surface temperature of the DHE.</p>
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<p>Numerical and experimental results in terms of outlet temperature of working fluid and the overall heat transfer coefficient (<span class="html-italic">U</span>).</p>
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<p>Numerical and experimental results in terms of output thermal power and DHE efficiency.</p>
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<p>Outlet temperature and heat transfer coefficient for different degrees of salinity of working fluid.</p>
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<p>Effect of increase in degree of salinity on heat transfer coefficient and output thermal power of DHE.</p>
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15 pages, 1883 KiB  
Article
Enhanced Molecular Networking Shows Microbacterium sp. V1 as a Factory of Antioxidant Proline-Rich Peptides
by Giovanni Andrea Vitale, Silvia Scarpato, Alfonso Mangoni, Maria Valeria D’Auria, Gerardo Della Sala and Donatella de Pascale
Mar. Drugs 2023, 21(4), 256; https://doi.org/10.3390/md21040256 - 21 Apr 2023
Cited by 4 | Viewed by 3177
Abstract
Two linear proline-rich peptides (12), bearing an N-terminal pyroglutamate, were isolated from the marine bacterium Microbacterium sp. V1, associated with the marine sponge Petrosia ficiformis, collected in the volcanic CO2 vents in Ischia Island (South Italy). Peptide [...] Read more.
Two linear proline-rich peptides (12), bearing an N-terminal pyroglutamate, were isolated from the marine bacterium Microbacterium sp. V1, associated with the marine sponge Petrosia ficiformis, collected in the volcanic CO2 vents in Ischia Island (South Italy). Peptide production was triggered at low temperature following the one strain many compounds (OSMAC) method. Both peptides were detected together with other peptides (38) via an integrated, untargeted MS/MS-based molecular networking and cheminformatic approach. The planar structure of the peptides was determined by extensive 1D and 2D NMR and HR-MS analysis, and the stereochemistry of the aminoacyl residues was inferred by Marfey’s analysis. Peptides 18 are likely to arise from Microbacterium V1 tailor-made proteolysis of tryptone. Peptides 1 and 2 were shown to display antioxidant properties in the ferric-reducing antioxidant power (FRAP) assay. Full article
(This article belongs to the Section Marine Biotechnology Related to Drug Discovery or Production)
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<p>Overlay of LC-MS chromatograms of crude extracts from pellets (<b>A</b>) and supernatants (<b>B</b>) of <span class="html-italic">Microbacterium</span> sp. V1 cultivated in eight different growth conditions. The intracellular extract of <span class="html-italic">Microbacterium</span> sp. V1 cultivated in LB medium at 15 °C, was shown to contain higher amounts of the mid-polar compounds at <span class="html-italic">m</span>/<span class="html-italic">z</span> 635.34 and 534.29 (circled in pink), eluted at retention times 12.7 and 11.9 min, respectively, and later identified as <b>1</b> and <b>2</b>. LC-MS chromatograms are labeled with the culture medium abbreviation and the bacterial growth temperature.</p>
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<p>The molecular network (MN) of the SPE fractions from the crude extract of <span class="html-italic">Microbacterium</span> sp. V1 cultivated in LB medium at 15 °C. The MN was annotated by MolNetEnhancer. Herein, each node is colored based on its chemical classification as indicated in the color chart, while the node size is directly proportional to the precursor ion intensity. Structures of peptides discussed in this study are included in the MN and linked to the relevant nodes.</p>
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<p>Structures of the proline-rich linear peptides <b>1</b> and <b>2</b>.</p>
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<p>Diagnostic HMBC and ROESY correlations used to elucidate amino acid sequence in compound <b>1</b>. Correlations used to assign carbonyl <sup>13</sup>C signals are noted with red arrows, intra-residual correlations are noted with blue arrows. ROESY correlations are noted with black arrows.</p>
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14 pages, 4882 KiB  
Article
Aseismic Creep, Coseismic Slip, and Postseismic Relaxation on Faults in Volcanic Areas: The Case of Ischia Island
by Nicola Alessandro Pino, Stefano Carlino, Lisa Beccaro and Prospero De Martino
Remote Sens. 2023, 15(7), 1791; https://doi.org/10.3390/rs15071791 - 27 Mar 2023
Cited by 1 | Viewed by 1619
Abstract
We performed a joined multitemporal and multiscale analysis of ground vertical movements around the main seismogenic source of Ischia island (Southern Italy) that, during historical and recent time, generated the most catastrophic earthquakes on the island, in its northern sector (Casamicciola fault). In [...] Read more.
We performed a joined multitemporal and multiscale analysis of ground vertical movements around the main seismogenic source of Ischia island (Southern Italy) that, during historical and recent time, generated the most catastrophic earthquakes on the island, in its northern sector (Casamicciola fault). In particular, we considered InSAR (2015–2019) and ground-levelling data (1987–2010), attempting to better define the source that caused the recent 2017 earthquake and interpret its occurrence in the framework of a long-term behavior of the fault responsible for the major historical earthquakes in Casamicciola. Our results unambiguously constrain the location and the kinematics of the 2017 rupture and further confirm the presence of a relatively large sliding area west of the 2017 surface break. Overall, the studied seismogenic fault reveals a complex dynamic, moving differentially and aseismically in the pre- and post-seismic event, in response to the long-term subsidence of the central sector of the island, dominated by Mt. Epomeo. The fault segment that slipped coseismically also is evidence of post-seismic viscous relaxation. The long-term differential vertical movement on the apparently creeping eastern sector of the Casamicciola fault provides an estimate of the slip rate occurring on the fault (0.82 mm/y−1). The analysis of the time of occurrence and the magnitude of the known historical earthquakes reveals that this rate is consistent with the recurrence of the earthquakes that occurred during at least the past three centuries and suggests that the time to the next seismic event at Casamicciola might be a few decades. More generally, our findings provide evidence of the link between subsidence and earthquakes in volcanic areas indicating, in this case, a high hazard for the island of Ischia. Results might be also useful for characterizing capable faulting in similar volcano-tectonic settings worldwide. Full article
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<p>Digital Terrain Model (source INGV Laboratorio Geomatica) of Ischia Island with indication of: (i) surface fault trace [adapted with permission from [<a href="#B25-remotesensing-15-01791" class="html-bibr">25</a>] (blue line); (ii) levelling benchmarks (red diamonds); (iii) area covered by the 1883 Casamicciola landslide (yellow area); area of maximum coseismic displacement (subsidence) for the 2017 earthquake inferred from DInSAR data [<a href="#B25-remotesensing-15-01791" class="html-bibr">25</a>] (blue area). Inset: couples of points (15; 1 to 30 black points), located along the two sides of the fault, facing each other at distance of ~250 m, for which is calculated the differential vertical displacement for the period January 2015–December 2019. In the inset, fumaroles of Mt. Cito (orange points) and hot thermal springs of Bagni area (blue points) are also shown.</p>
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<p>Differential vertical displacement between couple of points located along the two sides of the CSf. For location of the points see <a href="#remotesensing-15-01791-f001" class="html-fig">Figure 1</a>.</p>
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<p>Post-seismic displacement at couple 25-6, along with the theoretical exponential curve e<sup>−t/τvs</sup> computed for relaxation time τ<sub>vs</sub> = 123 days (t indicates the time from the earthquake).</p>
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<p>Velocity of the vertical ground motion as obtained from the analysis of DInSAR data, for the four time periods indicated in <a href="#remotesensing-15-01791-t001" class="html-table">Table 1</a>. Only the points with velocity larger than the standard deviation σ are shown (σ is reported in <a href="#app1-remotesensing-15-01791" class="html-app">Supplementary Figure S4</a>). The maps displayed in panels (<b>a</b>–<b>d</b>) correspond to the area enclosed in the red rectangle in the map on top.</p>
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<p>Difference of the velocity of the vertical ground motion in the period immediately following the earthquake (POST period; <a href="#remotesensing-15-01791-f004" class="html-fig">Figure 4</a>c) minus the velocity measured in the period preceding the event (PRE period; <a href="#remotesensing-15-01791-f004" class="html-fig">Figure 4</a>b). Only the points with velocity larger than the standard deviation <span class="html-italic">σ</span> are shown (<span class="html-italic">σ</span> is reported in <a href="#app1-remotesensing-15-01791" class="html-app">Supplementary Figure S5</a>).</p>
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<p>Vertical displacement measured at benchmarks along the “Borbonica” levelling line [<a href="#B32-remotesensing-15-01791" class="html-bibr">32</a>], during the surveys from 1987 to 2010. The horizontal axis reports the linear distance from the benchmark 86B. For location of benchmarks see <a href="#remotesensing-15-01791-f001" class="html-fig">Figure 1</a>.</p>
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<p>(<b>a</b>) Time functions describing the historical sequence of earthquakes (dots) that occurred on the CSf, as listed in historical catalogue CPTI15 [<a href="#B23-remotesensing-15-01791" class="html-bibr">23</a>] (<a href="#app1-remotesensing-15-01791" class="html-app">Table S1</a>); (<b>b</b>) time functions excluding the uncertain 1228 earthquake. In both panels, the vertical segments represent the coseismic slip as deduced from empirical relations linking magnitude to the average dislocation [<a href="#B48-remotesensing-15-01791" class="html-bibr">48</a>], while the oblique lines correspond to the long-term theoretical dislocation, as expected from the rate of aseismic slip observed on the creeping segment of the fault.</p>
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21 pages, 1507 KiB  
Article
Water from Nitrodi’s Spring Induces Dermal Fibroblast and Keratinocyte Activation, Thus Promoting Wound Repair in the Skin: An In Vitro Study
by Filomena Napolitano, Loredana Postiglione, Ilaria Mormile, Valentina Barrella, Amato de Paulis, Nunzia Montuori and Francesca Wanda Rossi
Int. J. Mol. Sci. 2023, 24(6), 5357; https://doi.org/10.3390/ijms24065357 - 10 Mar 2023
Cited by 4 | Viewed by 1850
Abstract
The Romans knew of Nitrodi’s spring on the island of Ischia more than 2000 years ago. Although the health benefits attributed to Nitrodi’s water are numerous, the underlying mechanisms are still not understood. In this study, we aim to analyze the physicochemical properties [...] Read more.
The Romans knew of Nitrodi’s spring on the island of Ischia more than 2000 years ago. Although the health benefits attributed to Nitrodi’s water are numerous, the underlying mechanisms are still not understood. In this study, we aim to analyze the physicochemical properties and biological effects of Nitrodi’s water on human dermal fibroblasts to determine whether the water exerts in vitro effects that could be relevant to skin wound healing. The results obtained from the study indicate that Nitrodi’s water exerts strong promotional effects on dermal fibroblast viability and a significant stimulatory activity on cell migration. Nitrodi’s water induces alpha-SMA expression in dermal fibroblasts, thus promoting their transition to myofibroblast-protein ECM deposition. Furthermore, Nitrodi’s water reduces intracellular reactive oxygen species (ROS), which play an important role in human skin aging and dermal damage. Unsurprisingly, Nitrodi’s water has significant stimulatory effects on the cell proliferation of epidermal keratinocytes and inhibits the basal ROS production but enhances their response to the oxidative stress caused by external stimuli. Our results will contribute to the development of human clinical trials and further in vitro studies to identify inorganic and/or organic compounds responsible for pharmacological effects. Full article
(This article belongs to the Section Molecular Immunology)
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<p>Effects of Nitrodi’s water on BJ cell proliferation. (<b>A</b>) Blot imaging and densitometric analysis. BJ cells, after incubation with PBS, Nitrodi, and fMLF for 5 min at 37 °C in a humidified (5% CO2) incubator, were lysed and subjected to Western blot analysis with anti phospho-ERK (p-ERK) antibody and then with the anti-ERK-2 antibody as a loading control. Histogram shows the levels of p-ERK 2 normalized to ERK value and expressed as a percentage of PBS control (<b>B</b>) Effects of PBS, Nitrodi, and culture medium on BJ cell proliferation. Cells were grown in 96-well plates for 0, 24, 48, and 144 h in the presence of 0.5% BSA (white column) or 10% FCS (black column). Cell viability was tested using the CellTiter 96 Aqueous One Solution Reagent. Cells treated with Nitrodi supplemented with 0.5% BSA or cells treated with culture medium supplemented with 0.5% BSA were compared to cells treated with PBS supplemented with 0.5% BSA at each time point. Cells treated with Nitrodi supplemented with 10% FCS and cells treated with culture medium supplemented with 10% FCS were compared to cells treated with PBS supplemented with 10% FCS at each time point. Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) Effects of a specific inhibitor of the ERK pathway (PD98059) on BJ cell proliferation under starving and growing conditions. Cells were pre-treated with PD98059 and exposed to PBS (as control), Nitrodi’s water (dark grey columns), or culture medium (light grey columns) supplemented with 0.5% BSA or 10% FCS. Cell viability was tested using the CellTiter 96 Aqueous One Solution Reagent at 24 h after the treatments. Results are expressed as a percentage of the control (PBS 0.5% BSA or PBS 10% FCS). Values are mean ± SEM of three experiments. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of Nitrodi’s water on BJ cell migration. (<b>A</b>) Effects of PBS and Nitrodi on BJ cell chemotaxis. BJ cells were treated with PBS (white column) and Nitrodi (black column) and allowed to migrate towards 5% FCS for 24 h at 37 °C in a humidified (5% CO<sub>2</sub>) incubator. Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. The photograph of the membrane used for chemotaxis is shown at the top of the figure. (<b>B</b>) Effects of specific inhibitors of ERKs (PD98059) and Rac1 (NSC23766) on BJ cell chemotaxis. BJ cells were allowed to migrate towards 5% FCS for 24 h at 37 °C in a humidified (5% CO<sub>2</sub>) incubator. The data are expressed as a percentage of migrated cells over PBS (assumed as 100%). Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Effects of PBS, Nitrodi, and Nitrodi in the presence of PD98059 and NSC23766 on BJ cell wound healing. Scratch images were acquired using inverted microscope and 4× magnification. Data were plotted and expressed as a percentage of the length of the wound over T0 (assumed as 100%). Error bars represent standard deviation of the mean of triplicate measurements within one experiment. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001 (<b>D</b>) Western blot and densitometric analyses of α-SMA expression in BJ cells. Relative α-SMA expressions were normalized to the respective value for total β-actin. Histogram shows the levels of α-SMA normalized to β-actin values and expressed as a percentage of PBS control.</p>
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<p>Effects of Nitrodi’s water on ECM deposition and ROS production by BJ cells. (<b>A</b>) Analysis of effects of Nitrodi’s water on BJ cell ECM deposition. ECM proteins vitronectin, fibronectin, and collagen type I were quantified by in situ ELISA. Protein concentration measurements were performed using calibration curves generated by plates coated with purified ECM components at different concentrations. Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) Cells were plated in a 96-well plate and treated with DCFH-DA (2′, 7′-dichlorodihydrofluorescein diacetate). At the end of incubation, cells were treated with PBS alone (white columns) or Nitrodi (black columns). ROS release was measured as dichlorofluorescein (DCF) fluorescence intensity at 5, 15, 30, and 60 min. Results are expressed as the mean fluorescence intensity of DCFH-DA-loaded cells less the values of the mean fluorescence intensity of DCFH-DA-unloaded cells. Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05 (<b>C</b>) Cells were plated in a 96-well plate and incubated with DCFH-DA. At the end of incubation, cells were treated with medium alone (white columns), H<sub>2</sub>O<sub>2</sub> (black columns), or fMLF (grey columns) in presence of PBS or Nitrodi. ROS release was measured as dichlorofluorescein (DCF) fluorescence intensity at 5 and 15 min. Results are expressed as the mean fluorescence intensity of DCFH-DA-loaded cells less the values of the mean fluorescence intensity of DCFH-DA-unloaded cells. Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of Nitrodi’s water on HaCaT cell migration. (<b>A</b>) Effects of PBS and Nitrodi on HaCaT cell chemotaxis. Cells treated with PBS (white column) and Nitrodi (black column) were allowed to migrate in response to 5% FCS for 24 h at 37 °C in a humidified (5% CO<sub>2</sub>) incubator. Error bars represent standard deviation of the mean of triplicate samples within one experiment. ** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Effects of Nitrodi’s water on HaCaT cell wound healing. Scratch images were acquired using inverted microscope and 4× magnification. Data were plotted and expressed as a percentage of the length of wound size over T0 (assumed as 100%). Error bars represent standard deviation of the mean of triplicate measurements within one experiment. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001 (<b>C</b>) In situ Trypan blue staining of HaCaT cells. Photographs show cells treated for 72 h with PBS and Nitrodi’s water. The images were acquired using inverted microscope and 10× magnification. The arrows indicate the unviable cells.</p>
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<p>Effects of Nitrodi’s water on HaCaT cell proliferation. Cells were grown in 96-well plates for 0, 24, 48, and 72 h, in the presence 0.5% BSA (white column) and 10% FCS (black column). Cell viability was tested by CellTiter 96 Aqueous One Solution Reagent. Cells treated with Nitrodi supplemented with 0.5% BSA and cells treated with culture medium supplemented with 0.5% BSA were compared to cells treated with PBS supplemented with 0.5% BSA at each time point. Cells treated with Nitrodi supplemented with 10% FCS and cells treated with culture medium supplemented with 10% FCS were compared to cells treated with PBS supplemented with 10% FCS at each time point. Error bars represent standard deviation of the mean of triplicate samples within one experiment. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of Nitrodi’s water on ROS production by HaCaT cells. (<b>A</b>) Cells were plated in a 96-well plate and treated with DCFH-DA (2′, 7′-dichlorodihydrofluorescein diacetate). At the end of incubation, cells were treated with PBS alone (white columns) or Nitrodi (black columns). ROS release was measured as dichlorofluorescein (DCF) fluorescence intensity at 5, 15, 30, and 60 min. Results are expressed as the mean fluorescence intensity of DCFH-DA-loaded cells less the value of the mean fluorescence intensity of DCFH-DA-unloaded cells. Values are the mean ± SEM of three experiments performed in triplicate. * <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) Cells were plated in a 96-well plate and incubated with DCFH-DA. At the end of incubation, cells were treated with medium alone (white columns), H<sub>2</sub>O<sub>2</sub> (black columns) or fMLF (grey columns) in presence of PBS or Nitrodi. ROS release was measured as dichlorofluorescein (DCF) fluorescence intensity at 5 and 15 min. Results are expressed as the mean fluorescence intensity of DCFH-DA-loaded cells less the value of the mean fluorescence intensity of DCFH-DA-unloaded cells. Values are the mean ± SEM of three experiments performed in triplicate. * <span class="html-italic">p</span> &lt; 0.05.</p>
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22 pages, 3871 KiB  
Review
Quaternary Evolution of Ischia: A Review of Volcanology and Geology
by Gemma Aiello and Mauro Caccavale
Appl. Sci. 2023, 13(6), 3554; https://doi.org/10.3390/app13063554 - 10 Mar 2023
Cited by 1 | Viewed by 1794
Abstract
Ischia shows intriguing and complex geology, which has been deeply investigated. In this paper, a reappraisal of the Quaternary geologic evolution of Ischia based on literature data is advised, concentrating on the volcanology of the island, based on field data and geochemistry, due [...] Read more.
Ischia shows intriguing and complex geology, which has been deeply investigated. In this paper, a reappraisal of the Quaternary geologic evolution of Ischia based on literature data is advised, concentrating on the volcanology of the island, based on field data and geochemistry, due to the happening of active fumarolic systems on the island and the marine geology and geophysics, which are intensively studied in the frame of the CARG Project. The literature studies have been incorporated with the geological interpretation of high-resolution seismic profiles, partly previously published and herein reorganized with the aim to highlight the geologic evolution of the different sectors of the island (northern Ischia, southern Ischia). The outcrop data have shown the deposits of ten explosive eruptions: among them, we focused on the S. Angelo Tephra. The laccolith model has been described in order to explain the resurgence of Ischia starting from 55 ky B.P. Geochemical information has been synthesized to reconstruct the volcano-tectonic development of Ischia during the last 55 ky B.P. Different models of block resurgence of Ischia have been discussed, based on literature studies. These aspects have supplemented the Quaternary geologic evolution of Ischia. While the northern Ischia offshore shows complex stratigraphic relationships between buried volcanic edifices, the southern Ischia offshore has been mainly commanded by erosional activities, progressive next to a dense system of submarine channels, and by the volcano-tectonic activities, which have triggered off the location of the Ischia Debris Avalanche. Full article
(This article belongs to the Special Issue Feature Review Papers in "Earth Sciences and Geography" Section)
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<p>Sketch bathymetric map showing the Ischia-Procida-Phlegrean Fields volcanic complex, which is located over an important ENE-WSW regional structural alignment.</p>
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<p>(<b>a</b>) Geologic map of Ischia Island; (<b>b</b>) composite chrono-stratigraphic sequence of Ischia (modified after [<a href="#B27-applsci-13-03554" class="html-bibr">27</a>]).</p>
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<p>Ischia Digital Elevation Model with the location of the Sparker seismic profiles (modified after Sbrana et al. [<a href="#B56-applsci-13-03554" class="html-bibr">56</a>]).</p>
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<p>The S. Angelo tephra of Ischia (modified after Brown et al. [<a href="#B23-applsci-13-03554" class="html-bibr">23</a>]) (<b>a</b>) stratigraphic column of the S. Angelo tephra. (<b>b</b>) Interpreted outcrop data showing the stratigraphic relantionships of the tephra and adjacent formations.</p>
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<p>The laccolith model of Ischia constructed by Carlino [<a href="#B30-applsci-13-03554" class="html-bibr">30</a>] (<b>a</b>,<b>b</b>,<b>c</b>) and Carlino et al. [<a href="#B19-applsci-13-03554" class="html-bibr">19</a>] (<b>d</b>). w: plate uplift; p<sub>0</sub>: laccolith pressure; p<sub>x</sub>. laccolith pressure at phase x; q: average magma influx; L: length of the elastic plate; h: thickness of the elastic plate; σ3: minimum principal stress [<a href="#B30-applsci-13-03554" class="html-bibr">30</a>].</p>
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<p>The model of block resurgence of Ischia proposed by Orsi et al. [<a href="#B11-applsci-13-03554" class="html-bibr">11</a>].</p>
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<p>Model for the uplift of the Ischia resurgence (modified after Molin et al. [<a href="#B52-applsci-13-03554" class="html-bibr">52</a>]) (<b>a</b>) Sketch diagram showing the actual tectonic setting, with the asymmetric block bordered by high-angle inward-dipping reverse faults, and outward-dipping normal faults in the innermost part. (<b>b</b>) Sketch diagram showing the model of the intermittent trapdoor uplift, with the seismic activity controlled by the reverse faults on the most strained side of the block. (<b>c</b>) Sketch diagram showing the model of the intermittent trapdoor uplift, with the activity of the reverse fault controlling the collapse of the periphery of the block and forming the outward-dipping normal faults.</p>
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<p>Seismic profile L28 (northern Ischia) and corresponding geologic interpretation.</p>
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<p>Seismic profile L47 (southern Ischia, Punta S. Pancrazio) and corresponding geologic interpretation.</p>
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16 pages, 4122 KiB  
Article
Identifying the Fingerprint of a Volcano in the Background Seismic Noise from Machine Learning-Based Approach
by Diego Rincon-Yanez, Enza De Lauro, Simona Petrosino, Sabrina Senatore and Mariarosaria Falanga
Appl. Sci. 2022, 12(14), 6835; https://doi.org/10.3390/app12146835 - 6 Jul 2022
Cited by 3 | Viewed by 1623
Abstract
This work is devoted to the analysis of the background seismic noise acquired at the volcanoes (Campi Flegrei caldera, Ischia island, and Vesuvius) belonging to the Neapolitan volcanic district (Italy), and at the Colima volcano (Mexico). Continuous seismic acquisition is a complex mixture [...] Read more.
This work is devoted to the analysis of the background seismic noise acquired at the volcanoes (Campi Flegrei caldera, Ischia island, and Vesuvius) belonging to the Neapolitan volcanic district (Italy), and at the Colima volcano (Mexico). Continuous seismic acquisition is a complex mixture of volcanic transients and persistent volcanic and/or hydrothermal tremor, anthropogenic/ambient noise, oceanic loading, and meteo-marine contributions. The analysis of the background noise in a stationary volcanic phase could facilitate the identification of relevant waveforms often masked by microseisms and ambient noise. To address this issue, our approach proposes a machine learning (ML) modeling to recognize the “fingerprint” of a specific volcano by analyzing the background seismic noise from the continuous seismic acquisition. Specifically, two ML models, namely multi-layer perceptrons and convolutional neural network were trained to recognize one volcano from another based on the acquisition noise. Experimental results demonstrate the effectiveness of the two models in recognizing the noisy background signal, with promising performance in terms of accuracy, precision, recall, and F1 score. These results suggest that persistent volcanic signals share the same source information, as well as transient events, revealing a common generation mechanism but in different regimes. Moreover, assessing the dynamic state of a volcano through its background noise and promptly identifying any anomalies, which may indicate a change in its dynamics, can be a practical tool for real-time monitoring. Full article
(This article belongs to the Section Earth Sciences)
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<p>Map of the Neapolitan volcanoes (Vesuvius, Campi Flegrei, and Ischia) with the seismic stations (circles in blue for Vesuvius, red for Campi Flegrei, and yellow for Ischia) used for the analysis.</p>
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<p>Map of Colima volcano with the seismic stations (magenta circles) (map data ©2021 Google).</p>
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<p>Workflow of the ML process.</p>
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<p>CNN architecture design with the colored layers. Yellow: convolution 1D; blue: batch normalization; orange: activation (ReLu); red: MaxPooling1D; gray: dropout (50%); light green: Lambda (mean); and purple: dense (softmax).</p>
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<p>Examples of vertical component recordings of seismic noise and corresponding spectrograms, at Campi Flegrei (ASB2 station), Ischia (IOCA station), Vesuvius (BKSG station), and Colima (COCA station).</p>
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26 pages, 7199 KiB  
Article
From Siliciclastic to Bioclastic Deposits in the Gulf of Naples: New Highlights from Offshore Ischia and Procida–Pozzuoli Based on Sedimentological and Seismo-Stratigraphic Data
by Gemma Aiello and Mauro Caccavale
Quaternary 2021, 4(4), 44; https://doi.org/10.3390/quat4040044 - 3 Dec 2021
Cited by 3 | Viewed by 2523
Abstract
This study discusses the siliciclastic to bioclastic deposits (in particular, the rhodolith deposits) in the Gulf of Naples based on sedimentological and seismo-stratigraphic data. The selected areas are offshore Ischia Island (offshore Casamicciola, Ischia Channel), where a dense network of sea-bottom samples has [...] Read more.
This study discusses the siliciclastic to bioclastic deposits (in particular, the rhodolith deposits) in the Gulf of Naples based on sedimentological and seismo-stratigraphic data. The selected areas are offshore Ischia Island (offshore Casamicciola, Ischia Channel), where a dense network of sea-bottom samples has been collected, coupled with Sparker Multi-tip seismic lines, and offshore Procida–Pozzuoli (Procida Channel), where sea-bottom samples are available, in addition to Sparker seismic profiles. The basic methods applied in this research include sedimentological analysis, processing sedimentological data, and assessing seismo-stratigraphic criteria and techniques. In the Gulf of Naples, and particularly offshore Ischia, bioclastic sedimentation has been controlled by seafloor topography coupled with the oceanographic setting. Wide seismo-stratigraphic units include the bioclastic deposits in their uppermost part. Offshore Procida–Pozzuoli, siliciclastic deposits appear to prevail, coupled with pyroclastic units, and no significant bioclastic or rhodolith deposits have been outlined based on sedimentological and seismo-stratigraphic data. The occurrence of mixed siliciclastic–carbonate depositional systems is highlighted in this section of the Gulf of Naples based on the obtained results, which can be compared with similar systems recognized in the central Tyrrhenian Sea (Pontine Islands). Full article
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<p>Study area (<b>top</b>). Sketch geologic map of the Gulf of Naples and of the adjacent Campania Plain (<b>bottom</b>).</p>
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<p>Sketch stratigraphic diagram showing the main regional unconformities (U2, U3, U4, U5, and U6) occurring in the Gulf of Pozzuoli, as controlled by the coastal subsidence, by the tectonic uplift, and by the sea level rise (modified after Steinmann et al., 2018) [<a href="#B34-quaternary-04-00044" class="html-bibr">34</a>]. Ve I (Volcanic Epoch I–15-9.5 ky B.P.). Ve II (Volcanic Epoch II–8.6-5 ky B.P.). Ve III (Volcanic Epoch III–4.8-3.7 ky B.P.). M2, M3, and M4 (M4.1, M4.2a, and M4.2b) represent the seismic units of the Gulf of Pozzuoli. The seismic unit M2 corresponds to the caldera filling. The seismic units M3 and M4.1 correspond to the deposition in the uplifting resurgent dome. The seismic unit M4.2a represents an infralittoral prograding unit deposited between 3.7 ky B.P. and 2 ky B.P. The seismic unit M4.2b represents a coastal wedge deposited during and after the phase of volcano-tectonic subsidence starting at 2 ky B.P.</p>
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<p>(<b>a</b>) Superficial circulation as controlled by a NE wind (modified after Cianelli et al., 2011) [<a href="#B79-quaternary-04-00044" class="html-bibr">79</a>]; (<b>b</b>) superficial circulation as controlled by a SW wind (modified after Cianelli et al., 2011) [<a href="#B79-quaternary-04-00044" class="html-bibr">79</a>]; (<b>c</b>,<b>d</b>) superficial circulation as controlled by the daily alternation of breeze winds; (<b>e</b>) oceanographic circulation as controlled by a NW Tyrrhenian current.</p>
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<p>(<b>a</b>) Superficial circulation as controlled by a NE wind (modified after Cianelli et al., 2011) [<a href="#B79-quaternary-04-00044" class="html-bibr">79</a>]; (<b>b</b>) superficial circulation as controlled by a SW wind (modified after Cianelli et al., 2011) [<a href="#B79-quaternary-04-00044" class="html-bibr">79</a>]; (<b>c</b>,<b>d</b>) superficial circulation as controlled by the daily alternation of breeze winds; (<b>e</b>) oceanographic circulation as controlled by a NW Tyrrhenian current.</p>
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<p>(<b>a</b>) Superficial circulation as controlled by a NE wind (modified after Cianelli et al., 2011) [<a href="#B79-quaternary-04-00044" class="html-bibr">79</a>]; (<b>b</b>) superficial circulation as controlled by a SW wind (modified after Cianelli et al., 2011) [<a href="#B79-quaternary-04-00044" class="html-bibr">79</a>]; (<b>c</b>,<b>d</b>) superficial circulation as controlled by the daily alternation of breeze winds; (<b>e</b>) oceanographic circulation as controlled by a NW Tyrrhenian current.</p>
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<p>Shows the DEM of Ischia–Procida, with superimposed the location of sea bottom samples. The sedimentological data have been plotted into ternary diagrams. While we can refer to the previous study for the Ischia samples and their elaboration [<a href="#B37-quaternary-04-00044" class="html-bibr">37</a>], at Procida–Pozzuoli, the samples have been plotted by dividing them into two groups, from sample B1A2 to sample B1054 (<a href="#quaternary-04-00044-f006" class="html-fig">Figure 6</a>a,c) and from sample BXMIS1 to sample PM27 (<a href="#quaternary-04-00044-f006" class="html-fig">Figure 6</a>b,d).</p>
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<p>Shows the DEM of Ischia–Procida, with superimposed the location of sea bottom samples. The sedimentological data have been plotted into ternary diagrams. While we can refer to the previous study for the Ischia samples and their elaboration [<a href="#B37-quaternary-04-00044" class="html-bibr">37</a>], at Procida–Pozzuoli, the samples have been plotted by dividing them into two groups, from sample B1A2 to sample B1054 (<a href="#quaternary-04-00044-f006" class="html-fig">Figure 6</a>a,c) and from sample BXMIS1 to sample PM27 (<a href="#quaternary-04-00044-f006" class="html-fig">Figure 6</a>b,d).</p>
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<p>Ternary plots constructed for the Ischia sea bottom samples (modified after Aiello, 2021) [<a href="#B37-quaternary-04-00044" class="html-bibr">37</a>]. (<b>a</b>) ternary plot (clay–sand–silt); (<b>b</b>) ternary plot (gravel–sand–silt); (<b>c</b>) ternary plot (clay–sand–silt); (<b>d</b>) ternary plot (gravel–sand–silt).</p>
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<p>Ternary plots of the sea bottom samples constructed at Procida–Pozzuoli. (<b>a</b>) ternary plot (clay–sand–silt), (<b>b</b>) ternary plot (clay–sand–silt); (<b>c</b>) ternary plot (gravel–sand–silt); (<b>d</b>) ternary plot (gravel–sand–silt).</p>
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<p>Seismic profile L27 and corresponding geologic interpretation (offshore Casamicciola).</p>
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<p>Seismic profile L57 and corresponding geologic interpretation (Ischia Channel).</p>
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<p>L65 Sparker seismic profile (Procida Channel) and corresponding geologic interpretation.</p>
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12 pages, 3585 KiB  
Article
Shrinking of Ischia Island (Italy) from Long-Term Geodetic Data: Implications for the Deflation Mechanisms of Resurgent Calderas and Their Relationships with Seismicity
by Alessandro Galvani, Giuseppe Pezzo, Vincenzo Sepe and Guido Ventura
Remote Sens. 2021, 13(22), 4648; https://doi.org/10.3390/rs13224648 - 18 Nov 2021
Cited by 7 | Viewed by 2088
Abstract
The identification of the mechanisms responsible for the deformation of calderas is of primary importance for our understanding of the dynamics of magmatic systems and the evaluation of volcanic hazards. We analyze twenty years (1997–2018) of geodetic measurements on Ischia Island (Italy), which [...] Read more.
The identification of the mechanisms responsible for the deformation of calderas is of primary importance for our understanding of the dynamics of magmatic systems and the evaluation of volcanic hazards. We analyze twenty years (1997–2018) of geodetic measurements on Ischia Island (Italy), which include the Mt. Epomeo resurgent block, and is affected by hydrothermal manifestations and shallow seismicity. The data from the GPS Network and the leveling route show a constant subsidence with values up to −15 ± 2.0 mm/yr and a centripetal displacement rate with the largest deformations on the southern flank of Mt. Epomeo. The joint inversion of GPS and levelling data is consistent with a 4 km deep source deflating by degassing and magma cooling below the southern flank of Mt. Epomeo. The depth of the source is supported by independent geophysical data. The Ischia deformation field is not related to the instability of the resurgent block or extensive gravity or tectonic processes. The seismicity reflects the dynamics of the shallow hydrothermal system being neither temporally nor spatially related to the deflation. Full article
(This article belongs to the Special Issue Ground Deformation Patterns Detection by InSAR and GNSS Techniques)
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Graphical abstract
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<p>Location and geological map of Ischia Island from [<a href="#B12-remotesensing-13-04648" class="html-bibr">12</a>] with epicentral and hypocentral (N-S cross section) distributions of the 1999–2017 earthquakes from [<a href="#B24-remotesensing-13-04648" class="html-bibr">24</a>]. Historical earthquakes are from [<a href="#B18-remotesensing-13-04648" class="html-bibr">18</a>]. Hydrothermal manifestations are from [<a href="#B20-remotesensing-13-04648" class="html-bibr">20</a>,<a href="#B17-remotesensing-13-04648" class="html-bibr">17</a>]. The depth of the hydrothermal reservoirs in the N-S cross section is from [<a href="#B20-remotesensing-13-04648" class="html-bibr">20</a>,<a href="#B21-remotesensing-13-04648" class="html-bibr">21</a>].</p>
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<p>Ischia GPS network and vertical and planar velocity field in mm/yr calculated in the time span 1997–2018.</p>
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<p>Ischia earthquakes (data from [<a href="#B24-remotesensing-13-04648" class="html-bibr">24</a>]) and OSCM (CGNSS) time series. Violet vertical bars are the starting and ending elaboration times. Yellow bars identify the removal of outlier solutions. Green vertical bar recorded in 2017 testifies of the Md 4 earthquake, whereas the green one recorded in 2018 is due to technical causes.</p>
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<p>Vertical GPS vs. levelling velocities in mm/yr. The linear regression is reported as a dashed line.</p>
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<p>Source depth, position, and volume variation of a homogeneous closuring (red symbols). The parameter uncertainties, best fit (in red), and trade-offs are shown.</p>
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<p>(<b>a</b>) Horizontal and (<b>b</b>) vertical GNSS velocities on Ischia Island. Black arrows represent the observed vectors; red and green ones are the modelled velocities for 4 km and 2 km depth models respectively; in (<b>c</b>,<b>d</b>), the corresponding closuring distributions for both models. Panels in second and third rows (<b>e</b>–<b>k</b>), report the observed, modelled, and residual levelling velocities for 4 km and 2 km depth models respectively; in panel (<b>h</b>,<b>l</b>) the corresponding 3D views of both displacement models are shown.</p>
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<p>Sketch summarizing the conceptual model of the dynamics of Ischia Island and in particular the relationship among magma degassing, seismicity. and deformation.</p>
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15 pages, 21822 KiB  
Article
Multitemporal and Multisensor InSAR Analysis for Ground Displacement Field Assessment at Ischia Volcanic Island (Italy)
by Lisa Beccaro, Cristiano Tolomei, Roberto Gianardi, Vincenzo Sepe, Marina Bisson, Laura Colini, Riccardo De Ritis and Claudia Spinetti
Remote Sens. 2021, 13(21), 4253; https://doi.org/10.3390/rs13214253 - 22 Oct 2021
Cited by 13 | Viewed by 3923
Abstract
Volcanic islands are often affected by ground displacement such as slope instability, due to their peculiar morphology. This is the case of Ischia Island (Naples, Italy) dominated by the Mt. Epomeo (787 m a.s.l.), a volcano-tectonic horst located in the central portion of [...] Read more.
Volcanic islands are often affected by ground displacement such as slope instability, due to their peculiar morphology. This is the case of Ischia Island (Naples, Italy) dominated by the Mt. Epomeo (787 m a.s.l.), a volcano-tectonic horst located in the central portion of the island. This study aims to follow a long temporal evolution of ground deformations on the island through the interferometric analysis of satellite SAR data. Different datasets, acquired during Envisat, COSMO-SkyMed and Sentinel-1 satellite missions, are for the first time processed in order to obtain the island ground deformations during a time interval spanning 17 years, from November 2002 to December 2019. In detail, the multitemporal differential interferometry technique, named small baseline subset, is applied to produce the ground displacement maps and the associated displacement time series. The results, validated through the analysis and the comparison with a set of GPS measurements, show that the northwestern side of Mt. Epomeo is the sector of the island characterized by the highest subsidence movements (maximum vertical displacement of 218 mm) with velocities ranging from 10 to 20 mm/yr. Finally, the displacement time series allow us to correlate the measured ground deformations with the seismic swarm started with the Mw 3.9 earthquake that occurred on 21 August 2017. Such correlations highlight an acceleration of the ground, following the mainshock, characterized by a subsidence displacement rate of 0.12 mm/day that returned to pre-earthquake levels (0.03 mm/day) after 6 months from the event. Full article
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<p>Location of Ischia Island within the Gulf of Naples, Southern Italy. Geographic coordinate system is UTM 33N, WGS 84.</p>
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<p>Hillshade relief of Ischia with the epicentres of the 2017 seismic sequence [<a href="#B9-remotesensing-13-04253" class="html-bibr">9</a>] and the area examined through the displacement time series analysis in addition to the municipalities and their limits, contour lines, faults [<a href="#B10-remotesensing-13-04253" class="html-bibr">10</a>] and landslides phenomena mapped within the island (IFFI landslides inventory). Geographic coordinate system is UTM 33N, WGS 84.</p>
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<p>Descending (<b>a</b>) and ascending (<b>b</b>) LOS displacement maps computed by using Envisat data.</p>
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<p>Comparison between GPS displacement rates reprojected on Envisat descending (blue triangles) and ascending (red triangles) LOS and, respectively, displacement rates evaluated through SBAS processing: descending track (light blue diamonds) and ascending track (orange diamonds).</p>
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<p>(<b>a</b>) Descending displacement map computed by using COSMO-SkyMed data. (<b>b</b>) Comparison between GPS displacement rates reprojected on satellite LOS (blue triangles) and those ones retrieved by SBAS processing (light blue diamonds).</p>
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<p>Descending (<b>a</b>) and ascending (<b>b</b>) LOS displacement maps computed by using Sentinel-1A data.</p>
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<p>Comparison between GPS displacement rates reprojected on Sentinel-1A descending (blue triangles) and ascending (red triangles) LOS and, respectively, displacement rates evaluated through SBAS processing: descending track (light blue diamonds) and ascending track (orange diamonds).</p>
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<p>Horizontal (<b>a</b>,<b>c</b>) and vertical (<b>b</b>,<b>d</b>) displacement maps for Envisat (<b>a</b>,<b>b</b>) and Sentinel-1A (<b>c</b>,<b>d</b>) datasets.</p>
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<p>Comparison between GPS horizontal displacement rates (blue triangles) and those retrieved through SBAS processing using Sentinel-1A data (red diamonds) and Envisat data (green diamonds).</p>
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<p>Comparison between GPS vertical displacement rates (blue triangles) and those retrieved through SBAS processing using Sentinel-1A data (red diamonds) and Envisat data (green diamonds).</p>
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<p>Detail of the maximum deformation zone and location of the area examined through the time series. Sentinel-1A vertical displacement map, epicentres [<a href="#B9-remotesensing-13-04253" class="html-bibr">9</a>] and faults [<a href="#B10-remotesensing-13-04253" class="html-bibr">10</a>] are also visible.</p>
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<p>LOS displacement time series performed at the centre of the maximum deformation area detected by the totality of the elaborations and conducted with all available descending datasets: Envisat from 11/2002 to 06/2010 (purple circles), COSMO-SkyMed from 02/2011 to 08/2017 (pink squares) and Sentinel-1A from 01/2015 to 12/2019 (light blue diamonds).</p>
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<p>(<b>a</b>) Time series of vertical displacements plotted at the centre of the maximum deformation area identified by the totality of the elaborations and derived from Envisat (11/2002–06/2010) and Sentinel-1A (01/2015–12/2019) processing. (<b>b</b>) Detail of the acceleration recorded by the Sentinel-1A sensor following the 21 August 2017 earthquake (red line).</p>
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18 pages, 5169 KiB  
Article
Petrography and Mineral Chemistry of Monte Epomeo Green Tuff, Ischia Island, South Italy: Constraints for Identification of the Y-7 Tephrostratigraphic Marker in Distal Sequences of the Central Mediterranean
by Massimo D'Antonio, Ilenia Arienzo, Richard J. Brown, Paola Petrosino, Carlo Pelullo and Biagio Giaccio
Minerals 2021, 11(9), 955; https://doi.org/10.3390/min11090955 - 31 Aug 2021
Cited by 8 | Viewed by 3321
Abstract
The 56 ka Monte Epomeo Green Tuff (MEGT) resulted from the largest volume explosive eruption from Ischia island (south Italy). Its tephra is one of the main stratigraphic markers of the central Mediterranean area. Despite its importance, a detailed characterisation of the petrography [...] Read more.
The 56 ka Monte Epomeo Green Tuff (MEGT) resulted from the largest volume explosive eruption from Ischia island (south Italy). Its tephra is one of the main stratigraphic markers of the central Mediterranean area. Despite its importance, a detailed characterisation of the petrography and mineral chemistry of MEGT is lacking. To fill this gap, we present detailed petrographic description and electron microprobe mineral chemistry data on samples collected on-land from the MEGT. Juvenile clasts include pumice, scoria, and obsidian fragments with porphyritic/glomeroporphyritic, vitrophyric, and fragmental textures. The porphyritic index is 13–40 vol.%, and phenocryst phases include alkali-feldspar, plagioclase, clinopyroxene, ferrian phlogopite, and titano-magnetite, in order of decreasing abundance; accessory phases include sphene, hydroxy-fluor-apatite, and rare edenite. Plagioclase varies from predominant andesine to subordinate oligoclase, whereas alkali-feldspar is more variable from sanidine to anorthoclase; quasi-pure sanidine commonly occurs as either rim or recrystallisation overgrowth of large phenocrysts due to hydrothermal alteration. Secondary minerals include veins and patches of carbonate minerals, Fe-Mn oxyhydroxides, clay minerals, and zeolites. Clinopyroxene is ferroan diopside (En45–29Fs7–27) and never reaches Na-rich compositions. This feature allows the discrimination of MEGT from aegirine-bearing, distal tephra layers erroneously attributed to MEGT, with implications for the areal distribution of Ischia explosive deposits. Full article
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<p>(<b>A</b>) Geological sketch map of Ischia island, showing the areal distribution of the main volcanic units, including the Monte Epomeo Green Tuff (modified after D’Antonio et al., 2013 [<a href="#B19-minerals-11-00955" class="html-bibr">19</a>]). (<b>B</b>) Map of the central Mediterranean area; numbered red circles indicate the main distal locations where the MEGT products have been either recognised or hypothesised: 1—PRAD 1–2 bore hole, Adriatic Sea [<a href="#B20-minerals-11-00955" class="html-bibr">20</a>]; 2—KET 8218 bore hole, Adriatic Sea [<a href="#B3-minerals-11-00955" class="html-bibr">3</a>]; 3—Fucino Basin, Abruzzo, Central Italy [<a href="#B2-minerals-11-00955" class="html-bibr">2</a>]; 4—Lago Grande di Monticchio, Basilicata [<a href="#B4-minerals-11-00955" class="html-bibr">4</a>,<a href="#B6-minerals-11-00955" class="html-bibr">6</a>]; 5—San Gregorio Magno basin, Campania [<a href="#B7-minerals-11-00955" class="html-bibr">7</a>,<a href="#B8-minerals-11-00955" class="html-bibr">8</a>]; 6—Oscurusciuto [<a href="#B10-minerals-11-00955" class="html-bibr">10</a>]; 7, 8, 10, 11—KET 8022, KET 8004, KET 8003, KET 8011 bore holes, Tyrrhenian Sea [<a href="#B3-minerals-11-00955" class="html-bibr">3</a>]; 9—ODP Leg 107, Site 650, Tyrrhenian Sea [<a href="#B21-minerals-11-00955" class="html-bibr">21</a>]; 12—Stromboli, Aeolian Archipelago [<a href="#B22-minerals-11-00955" class="html-bibr">22</a>]; 13, 14, 16—RC9-190, RC9-191, V10-68 bore holes, Ionian Sea [<a href="#B23-minerals-11-00955" class="html-bibr">23</a>]; 15—M25/4-11 bore hole, Ionian Sea ([<a href="#B9-minerals-11-00955" class="html-bibr">9</a>] and references therein); 17—ODP Leg 160 Site 964 and KC01B bore holes, Ionian Sea [<a href="#B5-minerals-11-00955" class="html-bibr">5</a>,<a href="#B24-minerals-11-00955" class="html-bibr">24</a>].</p>
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<p>Selected thin section photomicrographs of the investigated MEGT samples; additional photomicrographs are provided in <a href="#app1-minerals-11-00955" class="html-app">Supplementary Figure S1</a>. Key for mineral names (abbreviated according to Whitney and Evans, 2010 [<a href="#B48-minerals-11-00955" class="html-bibr">48</a>], except for Fe, Mn oxy-hydroxides, abbreviated as Fe, Mn oxy-hyd): Afs = alkali-feldspar; Cpx = clinopyroxene; Pl = plagioclase; Opq = opaque oxide; Spn = sphene; Ap = apatite; Amp = amphibole; Cb = carbonate. (<b>A</b>) fresh scoria showing porphyritic texture and microcrystalline/felty groundmass (cross-polarised light; sample OIS0102); (<b>B</b>) fresh scoria showing porphyritic texture and microcrystalline/felty groundmass (plane-polarised light; sample OIS0102); (<b>C</b>) gabbroic agglomerate in vitrophyric obsidian, showing the typical perlitic fractures; in the agglomerate, the plagioclase rim is slightly altered (enriched in Fe, see EMPA data in <a href="#app1-minerals-11-00955" class="html-app">Table S1</a>) and the interstitial glass is partly altered (plane-polarised light; sample MEGT0318); (<b>D</b>) volcanic bomb (scoria) showing porphyritic/glomeroporphyritic texture and microcrystalline/felty/fluidal groundmass with pervasive alteration by Fe, Mn oxy-hydroxides patches and veins cutting phenocrysts (cross-polarised light; sample MEGT0302); (<b>E</b>) same sample as D, showing abundant carbonate patches in the groundmass, and a plagioclase phenocryst at the core of an alkali-feldspar phenocryst (cross-polarised light; sample MEGT0302); (<b>F</b>) same sample as D, showing a thick carbonate vein cutting a large alkali-feldspar phenocryst (cross-polarised light; sample MEGT0302); (<b>G</b>) scoria showing porphyritic texture and microcrystalline/felty groundmass with pervasive alteration by patches of Fe, Mn oxy-hydroxides, and perhaps clays; the alkali-feldspar phenocryst on the left side is partly corroded by alteration (cross-polarised light; sample MEGT0301); (<b>H</b>) same sample as G, showing an agglomerate made up of dominant alkali-feldspar and clinopyroxene, and minor black mica, opaque oxide, and apatite; the clinopyroxene phenocryst is almost totally replaced by carbonate and Fe, Mn oxy-hydroxides; the alkali-feldspar phenocrysts exhibit a comb texture, suggesting that alteration has proceeded from rim toward the inner part (cross-polarised light; sample MEGT0301).</p>
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<p>Ternary classification diagram Ab-An-Or for feldspars [<a href="#B49-minerals-11-00955" class="html-bibr">49</a>] showing all plagioclase and alkali-feldspar crystals analysed in the selected MEGT volcanic rocks. Ab = albite molar %, including Sr-feldspar; An = anorthite molar %; Or = orthoclase molar %, including celsian. Early = phenocryst core; late = phenocryst rim, microphenocrysts and groundmass microlites; overgrowth on phenocryst. The pink fields are drawn using mineral chemistry data on Ischia trachytes and phonolites from the literature [<a href="#B14-minerals-11-00955" class="html-bibr">14</a>,<a href="#B19-minerals-11-00955" class="html-bibr">19</a>,<a href="#B41-minerals-11-00955" class="html-bibr">41</a>,<a href="#B43-minerals-11-00955" class="html-bibr">43</a>].</p>
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<p>Pyroxene quadrilateral classification diagram Di-Hd-En-Fs [<a href="#B51-minerals-11-00955" class="html-bibr">51</a>]. (<b>A</b>) clinopyroxene crystals analysed in the selected MEGT volcanic rocks. The pink field has been drawn using mineral chemistry data on Ischia trachytes and phonolites from the literature [<a href="#B14-minerals-11-00955" class="html-bibr">14</a>,<a href="#B19-minerals-11-00955" class="html-bibr">19</a>,<a href="#B41-minerals-11-00955" class="html-bibr">41</a>,<a href="#B43-minerals-11-00955" class="html-bibr">43</a>]. (<b>B</b>) clinopyroxene crystals and fragments separated from samples S16 [<a href="#B7-minerals-11-00955" class="html-bibr">7</a>,<a href="#B8-minerals-11-00955" class="html-bibr">8</a>] and TF-7 [<a href="#B2-minerals-11-00955" class="html-bibr">2</a>]. See Discussion for details. Early = phenocryst core; late = phenocryst rim, microphenocrysts and microlites; fragment = broken crystal for which it is not possible to ascertain the original shape.</p>
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<p>Fe<sub>2</sub>O<sub>3</sub>-TiO<sub>2</sub>-FeO ternary diagram [<a href="#B53-minerals-11-00955" class="html-bibr">53</a>] for opaque oxides of the selected MEGT volcanic rocks.</p>
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<p>MgCO<sub>3</sub>-CaCO<sub>3</sub>-[Fe+Mn]CO<sub>3</sub> ternary diagram for carbonates of the selected MEGT volcanic rocks.</p>
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<p>Total alkali vs. silica classification diagram (TAS; [<a href="#B57-minerals-11-00955" class="html-bibr">57</a>]) showing the composition of apparently fresh glass analysed in MEGT volcanic rocks (this work; data from <a href="#app1-minerals-11-00955" class="html-app">Supplementary Table S1</a>), compared with whole rock data on MEGT and 75–55 ka Ischia volcanic rocks from the literature [<a href="#B11-minerals-11-00955" class="html-bibr">11</a>,<a href="#B15-minerals-11-00955" class="html-bibr">15</a>]. All analyses were plotted after normalisation to 100% on a water-free basis, according to recommendation by I.U.G.S. [<a href="#B57-minerals-11-00955" class="html-bibr">57</a>]. K-B = potassic basalt; K-TB = potassic trachybasalt; SH = shoshonite; LT = latite; TR = trachyte (these rock names are relative to a potassic alkaline series); TH/Bas = tephrite/basanite; PH-TH = phonotephrite; TH-PH = tephriphonolite; PH = phonolite.</p>
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<p>Occurrence of the Monte Epomeo Green Tuff distal tephra, the marine Ischia tephra Y-7, and other “Ischia layers” corresponding to either MEGT or Y-7 or both tephra layers, but still not definitively correlated. Data sources: PRAD 1-2 [<a href="#B20-minerals-11-00955" class="html-bibr">20</a>]; Fucino [<a href="#B2-minerals-11-00955" class="html-bibr">2</a>]; Lago Grande di Monticchio [<a href="#B6-minerals-11-00955" class="html-bibr">6</a>]; San Gregorio Magno [<a href="#B7-minerals-11-00955" class="html-bibr">7</a>,<a href="#B8-minerals-11-00955" class="html-bibr">8</a>]; Oscurusciuto [<a href="#B10-minerals-11-00955" class="html-bibr">10</a>]; KET 8004, KET 8011, KET 8003, KET 8218 [<a href="#B3-minerals-11-00955" class="html-bibr">3</a>]; ODP Leg 107 Site 650 [<a href="#B21-minerals-11-00955" class="html-bibr">21</a>]; RC9-190, RC9-191, and V10-68 [<a href="#B23-minerals-11-00955" class="html-bibr">23</a>]; Stromboli [<a href="#B22-minerals-11-00955" class="html-bibr">22</a>]; M25/4-11 [<a href="#B9-minerals-11-00955" class="html-bibr">9</a>]; ODP Leg 160 Site 964, KC01B [<a href="#B5-minerals-11-00955" class="html-bibr">5</a>,<a href="#B24-minerals-11-00955" class="html-bibr">24</a>].</p>
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18 pages, 7353 KiB  
Technical Note
The Ground Deformation History of the Neapolitan Volcanic Area (Campi Flegrei Caldera, Somma–Vesuvius Volcano, and Ischia Island) from 20 Years of Continuous GPS Observations (2000–2019)
by Prospero De Martino, Mario Dolce, Giuseppe Brandi, Giovanni Scarpato and Umberto Tammaro
Remote Sens. 2021, 13(14), 2725; https://doi.org/10.3390/rs13142725 - 11 Jul 2021
Cited by 41 | Viewed by 4888
Abstract
The Neapolitan volcanic area includes three active and high-risk volcanoes: Campi Flegrei caldera, Somma–Vesuvius, and Ischia island. The Campi Flegrei volcanic area is a typical example of a resurgent caldera, characterized by intense uplift periods followed by subsidence phases (bradyseism). After about 21 [...] Read more.
The Neapolitan volcanic area includes three active and high-risk volcanoes: Campi Flegrei caldera, Somma–Vesuvius, and Ischia island. The Campi Flegrei volcanic area is a typical example of a resurgent caldera, characterized by intense uplift periods followed by subsidence phases (bradyseism). After about 21 years of subsidence following the 1982–1984 unrest, a new inflation period started in 2005 and, with increasing rates over time, is ongoing. The overall uplift from 2005 to December 2019 is about 65 cm. This paper provides the history of the recent Campi Flegrei caldera unrest and an overview of the ground deformation patterns of the Somma–Vesuvius and Ischia volcanoes from continuous GPS observations. In the 2000–2019 time span, the GPS time series allowed the continuous and accurate tracking of ground and seafloor deformation of the whole volcanic area. With the aim of improving the research on volcano dynamics and hazard assessment, the full dataset of the GPS time series from the Neapolitan volcanic area from January 2000 to December 2019 is presented and made available to the scientific community. Full article
(This article belongs to the Special Issue GNSS for Geosciences)
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Graphical abstract

Graphical abstract
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<p>Vertical displacement at CFc from 1905 to December 2019. Red dots are levelling data (from Del Gaudio et al., 2010), and black dots are GPS measurements at RITE (Rione Terra–Pozzuoli) station taken since 2000.</p>
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<p>Map of the cGPS stations (black dots) at Campi Flegrei caldera (<b>a</b>), Ischia and Procida islands (<b>b</b>), and Somma–Vesuvius volcanic complex (<b>c</b>). The blue dots in (<b>a</b>) indicate the cGPS stations of the MEDUSA infrastructure. (<b>d</b>) Map of the Campania region with volcanic areas. Purple triangles indicate some RING cGPS stations.</p>
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<p>Daily north displacements (in a local reference frame) for the Campi Flegrei cGPS stations (black dots in <a href="#remotesensing-13-02725-f002" class="html-fig">Figure 2</a>a) from January 2000 to December 2019.</p>
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<p>Daily east displacements (in a local reference frame) for the Campi Flegrei cGPS stations (black dots in <a href="#remotesensing-13-02725-f002" class="html-fig">Figure 2</a>a) from January 2000 to December 2019.</p>
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<p>Daily vertical displacements for the Campi Flegrei cGPS stations (black dots in <a href="#remotesensing-13-02725-f002" class="html-fig">Figure 2</a>a) from January 2000 to December 2019.</p>
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<p>Weekly filtered GPS time series of MEDUSA stations CFBA, CFBB, and CFBC (north, east, and up components) and CFSB (up component only) from January 2016 to December 2019. The error bars represent the interquartile range (IQR) of each weekly median solution [<a href="#B47-remotesensing-13-02725" class="html-bibr">47</a>]. See <a href="#remotesensing-13-02725-f002" class="html-fig">Figure 2</a>a for the location of the stations (blue dots).</p>
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<p>Daily north (<b>a</b>), east (<b>b</b>), and vertical (<b>c</b>) displacements for the Ischia–Procida cGPS stations (black dots in <a href="#remotesensing-13-02725-f002" class="html-fig">Figure 2</a>b) from January 2001 to December 2019. The horizontal components (<b>a</b>,<b>b</b>) are in a local reference frame.</p>
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<p>Daily north (<b>a</b>), east (<b>b</b>), and vertical (<b>c</b>) displacements for the Somma–Vesuvius cGPS stations (black dots in <a href="#remotesensing-13-02725-f002" class="html-fig">Figure 2</a>c) from January 2001 to December 2019. The horizontal components (<b>a</b>,<b>b</b>) are in a local reference frame.</p>
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<p>(<b>a</b>) Horizontal deformation pattern from 2006 to 2019 (21 cGPS stations). (<b>b</b>) Vertical deformation pattern from 2006 to 2019 (9 cGPS stations). (<b>c</b>) Vertical deformation pattern from 2011 to 2019 (14 cGPS stations). (<b>d</b>) Vertical deformation pattern from 2017 to 2019 (25 cGPS stations).</p>
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<p>Horizontal (blue arrows) and vertical GPS velocity field (red arrows) for Ischia–Procida islands in the time span of 2001–2019. The black dots indicate the cGPS stations. For clarity, the error ellipses are not shown.</p>
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<p>Horizontal (blue arrows) and vertical GPS velocity field (red arrows) for the Somma–Vesuvius volcano in the time span of 2001–2019. The black dots indicate the cGPS stations. For clarity, the error ellipses are not shown.</p>
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