On 24 December 2018 a new lateral eruption of Mt. Etna volcano began. The phenomenon produced an intense seismic swarm, strong gaseous emissions from the summit craters and a well-defined lava flow, emplaced on the southwestern portion of the Valle del Bove depression. During the following paroxysm occurred on 29 May 2019, a new lava flow partially covered the previous ones. Aiming to evaluate the effects over time that the emplacement of lava flows produces over the volcanic structure, here we exploited a multidisciplinary approach, comprising both optical (Sentinel-2) and radar (Sentinel-1 and Cosmo-SkyMed) satellite data, processed through different remote sensing techniques. In detail, Sentinel-2 data allowed to retrieve the lava flows boundaries, Sentinel-1 data permitted to reconstruct ground displacement maps and related time series during the January 2016 – July 2021 time span whilst Cosmo-SkyMed ones were used to estimate the topographic changes caused by the lava emplacement.

The fallout of lapilli and incandescent bombs during the 3rdJuly 2019 paroxysm had triggered wildfires in Stromboli island, destroying the endemic vegetation and cultures. Data acquired by Landsat 8 OLI/TIRS, Sentinel 2A and Pleiades 1A-B satellites were processed in order to obtain the spectral indexes for the burned areas detection: NBR (Normalized Burn Ratio), NDVI (Normalized Difference Vegetation Index) and IFIRE (Index Fire). The spectral indexes produced burnt vegetation resulting maps. Thanks to a drone imagery at spatial resolution of 8 cm, acquired within a few days after the paroxysm, it was possible to validate the results in the area of Ginostra village and identify the best satellite data useful for mapping the wildfires. This study provides elements to identify and quantify the areas affected by wildfires triggered by volcanic ballistic projectiles, providing elements for the volcanic hazard management or mitigation.

The unique spectral content provided by PRISMA's hyperspectral sensor gives the possibility to study the Earth's surface and environment from space in unprecedented detail. In this respect, our work presents the results of an Italian Space Agency-funded project aiming to develop eight prototypes for providing Value Added products based on such data. Prototypes focus on vegetation, urban areas, water quality, material detection, and natural hazards, combining multiple state-of-the-art techniques based on Machine Learning, physical models, and index-based algorithms. This is particularly relevant given the increasing demand for accurate information to address sustainable policies and support decision-making processes. Through a series of case studies, we highlight the versatility and utility of PRISMA's hyperspectral data for various scientific and operational applications.

A quick analysis of gaseous content in volcanic plumes is possible by using hyperspectral remote sensing data. In the present work, an algorithm to calculate CO2columnar abundance in tropospheric volcanic plumes is applied to two volcanic test sites. The algorithm is based on the CIBR (Continuum Interpolated Band Ratio) remote sensing technique which exploits spectroscopy measurements by analyzing gases absorptions features in the SWIR (Short Wave InfraRed) spectral range. Specifically, PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite acquisitions are used for CO2retrieval purposes. The PRISMA space mission was launched by the ASI (Italian Space Agency) on March 22, 2019; the on board spectrometer is able to acquire images of the Earth in the VNIR ($0.4-1.0\ \ \mu \mathrm{m}$) and SWIR ($0.9-2.5\ \ \mu \mathrm{m}$) spectral ranges continuously, with a ground spatial resolution of 30 m. The inversion technique is applied to two Italian test sites: the Stromboli volcano and the Solfatara-Pisciarelli area (in the caldera of Campi Flegrei). The results show the capability of the method to detect and estimate strong CO2concentrations at a local spatial scale. While the satellite data provide a wide view of the emissions, in situ measurements are able to achieve accurate estimates of gases concentrations at very high spatial resolution. Acquisitions by a miniature multi-Gas analysis system, mounted on UAV (Unmanned Aerial Vehicle), are also considered. The multi-Gas instrument can measure H2O, CO2, H2S and SO2gases. Specifically, data of carbon dioxide concentrations acquired on the Solfatara-Pisciarelli test site are here presented.

Synthetic Aperture RADAR data acquired during several space missions (Envisat, COSMO-SkyMed and Sentinel-1) were treated in order to obtain the ground displacement of the Ischia island (Naples, Italy) and to retrieve the deformation evolution during the investigated time period. The results, validated with available GPS measurements, were found by applying the Small Baseline Subset (SBAS) technique [1], one of the main algorithms proposed in the context of multitemporal methods of Differential SAR Interferometry. This technique permitted to identify and monitor areas affected by slope instability phenomena in a quite continuous time period, from 2002 to the end of 2019. The presented results constitute the basic information for the future application of a GIS-based interdisciplinary approach aimed at the prevention of natural disasters in correspondence with the Ischia island.

The recent PRISMA (PRecursore IperSpettrale della Missione Applicativa) space mission, launched by the ASI (Italian Space Agency) on March 2019, brought in orbit a hyperspectral sensor (in the range$0.4-2.5 \mu\mathrm{m})$and a panchromatic camera with a spatial resolution of 30 and 5 meters, respectively. The PRISMA data are available for free (under license) and represent a unique orbiting source of hyperspectral data to investigate and analyze geophysical/geological phenomena. PRISMA works as the precursor of the next generation of ESA-SENTINEL satellites. In this work, a series of possible applications of PRISMA hyperspectral data are presented also considering data fusion with the panchromatic camera and the integration with other available satellite data as from Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection).

In the frame of the Italian Space Agency (ASI) Hyperspectral Space Mission PRISMA, the Istituto Nazionale di Geofisica e Vulcanologia coordinates the scientific project ASI-AGI aimed to develop specific algorithms and products for geophysical applications. Data validation and calibration activities have been focused on active volcanic areas and three test sites have been selected in Sicily, Italy. In the period 23-27 June 2012 the project team has organized an hyperspectral airborne and field measurements campaign over Mt. Etna, Paternò area and Ciclopi Islands investigating various surface targets using different instruments. The airborne and ground campaign have been planned during satellites passes of Hyperion and ASTER. The whole data set acquired during this campaign allowed the airborne data calibration and provide a suitable data set to simulate PRISMA data and to test the developed algorithms in the framework of the project.

Volcanic plumes represent a visible indicator of volcanic activity. They vary in space and time, strongly influenced by the quiescent or eruptive status of the volcano. Different volcanic activities, such as volcanic clouds and plumes, inject into the atmosphere gases and aerosol at different latitudes, altitudes and with different times of residence. Released by the magma, plumes are a turbulent mixture of gases, solid particles and liquid droplets, emitted at high temperature continuously from summit craters, fumarolic fields or during eruptive episodes. Mt. Etna, in Sicily (Italy), is one of the world's most frequent emitters of volcanic plumes. It show a permanent degassing plumes periodically interrupted by copious tephra emission and fallout that damage the inhabited and cultivated areas and created serious hazards to air traffic, as volcanic clouds can spread thousand of km in the central Mediterranean area. Recurrent closures of the Catania International airport have often been necessary, causing great losses to the local economy (Andronico et al 2009). For these reasons Mt. Etna is continually monitored and recent a new approach has been adapted integrating ground network data with the analysis of space data. In order to extract geophysical parameters related to volcano status software modules has been developed divided by early warning phase, crisis phase and post- crisis phase. Modules using already developed remote sensing techniques in the VIS and IR wavelength range. Here we present two modules for the Mt. Etna volcanic plume analysis using ASTER on TERRA and HYPERION on EO-1 data. This study is carried out within the SRV project, funded by the Italian Space Agency (ASI).

The ASI-SRV (Sistema Rischio Vulcanico) project is devoted to the development of an integrated system based on EO and Non EO data to respond to specific needs of the Italian Civil Protection Department (DPC). ASI-SRV provides the capability to import many different EO and Non EO data into the system, it maintains a repository where the acquired data have to be stored and generates selected products which will be functional to the different volcanic activity phases. The processing modules for Radar and EO Optical sensors data allow to estimate a number of parameters which include: surface thermal proprieties, gas, aerosol and ash emissions and to characterize the volcanic products in terms of composition and geometry, surface deformations in terms of displacements and velocity. All the generated products are related to Italian actives volcanoes and three test sites have been chosen to demonstrate the capability of this integrated system: Vesuvio, Campi Flegrei (Campania region) and Etna (Sicilia region). In this paper the first results obtained by means of modules developed within the ASI-SRV project and dedicated to the processing of EO historical series are presented.

In the present study a remote sensing differential absorption technique, already developed to calculate the atmospheric water vapour abundance, has been adapted to calculate water vapour columnar abundance in tropospheric volcanic plume. Water vapour is the most abundant gas of a volcanic plume released into the atmosphere from an active volcanic system. The technique is based on the correlation between the dip in the spectral curve measured by the spectrometer were water vapour absorptions bands are presents, and the precipitable water content in the column. Airborne and satellite remote sensing images in the infrared wavelength range were used. The technique has been applied to data acquired over two different degassing volcanoes. The Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) acquired data over the Hawaiian Pu'u'O'o Vent cone of the Kilauea volcano on April 2000. The Hyperion sensor on EO-1 satellite has been requested to acquire data on July 2003, during a ground-based measurements campaign on Mt. Etna (Italy). The result is the spatial distribution of water vapour abundance of the Mt. Etna and of the Pu'u'O'o Vent volcanic plumes. A comparison between the two results has been done, showing the differences in the volcanic activity. The algorithm produces reliable results compared to the ground based measurements in the plume area acquired during a measurements campaign over Mt. Etna.