After a period of mild eruptive activity, Stromboli showed between 2017 and 2018 a reawakening phase, with an increase in the eruptive activity starting in May 2017. The alert level of the volcano was raised from “green” (base) to “yellow” (attention) on 7 December 2017, and a small lava overflowed the crater rim on 15 December 2017. Between July 2017 and August 2018 the monitoring networks recorded nine major explosions, which are a serious hazard for Stromboli because they affect the summit area, crowded by tourists. We studied the 2017–2018 eruptive phase through the analysis of multidisciplinary data comprising thermal video-camera images, seismic, geodetic and geochemical data. We focused on the major explosion mechanism analyzing the well-recorded 1 December 2017 major explosion as a case study. We found that the 2017–2018 eruptive phase is consistent with a greater gas-rich magma supply in the shallow system. Furthermore, through the analysis of the case study major explosion, we identified precursory phases in the strainmeter and seismic data occurring 77 and 38 s before the explosive jet reached the eruptive vent, respectively. On the basis of these short-term precursors, we propose an automatic timely alarm system for major explosions at Stromboli volcano.
Land Surface Temperature (LST) from satellite data is a key component in many aspects of environmental research. In volcanic areas, LST is used to detect ground thermal anomalies providing a supplementary tool to monitor the activity status of a particular volcano. In this work, we describe a procedure aimed at identifying spatial thermal anomalies in thermal infrared (TIR) satellite frames which are corrected for the seasonal influence by using TIR images from ground stations. The procedure was applied to the volcanic area of Campi Flegrei (Italy) using TIR ASTER and Landsat 8 satellite imagery and TIR ground images acquired from the Thermal Infrared volcanic surveillance Network (TIRNet) (INGV, Osservatorio Vesuviano). The continuous TIRNet time-series images were processed to evaluate the seasonal component which was used to correct the surface temperatures estimated by the satellite’s discrete data. The results showed a good correspondence between de-seasoned time series of surface ground temperatures and satellite temperatures. The seasonal correction of satellite surface temperatures allows monitoring of the surface thermal field to be extended to all the satellite frames, covering a wide portion of Campi Flegrei volcanic area.
Abstract. The Solfatara volcano in the Campi Flegrei caldera (Italy), is monitored by different, permanent ground networks handled by INGV (Istituto Nazionale di Geofisica e Vulcanologia), including thermal infrared cameras (TIRNet). The TIRNet network is composed by five stations equipped with FLIR A645SC or A655SC thermal cameras acquiring at nightime infrared scenes of portions of the Solfatara area characterized by significant thermal anomalies. The dataset processed in this work consists of daily maximum temperatures time-series from 25 April 2014 to 31 May 2019, acquired by three TIRNet stations (SF1 and SF2 inside Solfatara crater, and PIS near Pisciarelli boiling mud pool), and also consists of atmospheric pressure and air temperature time-series. Data pre-processing was carried out in order to remove the seasonal components and the influence of the Earth tides to the selected time-series. By using the STL algorithm (Seasonal Decomposition of Time Series by Loess), the time-series were decomposed into three components (seasonal, trend and remainder) to find seasonality and remove it. Then, a harmonic analysis was performed on the de-seasonalized signals in order to identify and remove the long-period tidal constituents (mainly fortnightly and monthly). Finally, Power Spectral Density was calculated by FFT Matlab algorithm, after applying an acausal Butterworth filter, focusing on the [15–120] d band, to check if characteristic periodicities exist for each site. The reliability and significance of the spectral peaks were proved by statistical and empirical methods. We found that most of the residual periodicities are ascribable to ambient factors, while 18.16 d for Pisciarelli site and 88.71 d for Solfatara have a possible endogenous origin.
We present a long-range terrestrial laser scanner application for the geostructural mapping of Coroglio cliff, a tuff rock face exposed along the coastal zone of Campi Flegrei, Napoli. The procedure includes several phases (geomorphological analysis, structural field survey, laser scanner data acquisition and data processing, 3-D model development and analysis, geostructural classification of discontinuity orientation data and 2-D vertical cartographic production). Field data were processed with specific software dedicated to geostructural and geometric analysis. Spatial data were managed with a geographical information system and have been used for the construction of 2-D and 3-D geometric models of the rock cliff surface and geostructural interpretation. The main product of this study is a vertical geostructural map of the Coroglio cliff at 1:500 scale that illustrates the spatial distribution and orientation of the major families of structural discontinuities detected along the exposed surface of the cliff. The cartographic product includes base information useful to identify the main rock failure mechanisms along the cliff and represents a first step for the zonation of areas susceptible to block failures and the planning of monitoring activities.
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