Heatwaves, have been made more frequent and intense in the last decades due to climate change and have been severely impacting the population, especially vulnerable ones, causing illness, death and impact on productivity. Heatwaves and their consequences are worst in urban areas that become islands of higher temperatures, usually refereed to as urban heat islands, UHI. In the framework of the European Commission-funded research project ARCH: Advancing Resilience of historic areas against Climate-related and other Hazards this phenomenon has been analyzed with special focus on historic and cultural heritage areas. This paper proposes an easy to be implemented procedure to provide to local administrations and stakeholders readable and easy to be understood information on the location of UHI within the territory and the induced risks of impact on the population, enabling them to take informed decisions on possible and effective mitigation strategies. The proposed procedures use satellite thermal maps to quantify the thermal hazard within the analysed territory in the first instance; the exposure to UHI effect in terms of location and severity of possible urban islands within the city is evaluated by considering both the land cover and the population. A social vulnerability assessment is then performed based on age and economic indicators readily available from census data. Using a fuzzy overlay approach all the above-mentioned assessments are combined to estimate the risk for possible impacts to the population induced by heatwaves.

This study is to discuss the ability of full-resolution, i.e., speckled, Sentinel-1 single-look-complex (SLC) Synthetic Aperture Radar (SAR) imagery to monitor water-area coverage of salt ponds. Three scenarios are considered: 1) completely filled of water, 2) empty, 3) intermediate. The metric adopted to track the pond water area evolution is based on the speckle statistics and, in particular, on the departure from the fully developed speckle model.Experiments, performed using a time-series of Sentinel-1 SAR imagery collected over the salt pond "Sale ’e Porcus", Sardinia, Italy, show that Normalized Intensity Moments (NIMs) allow a good separation between the three cases under different wind conditions.

The Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is a new ESA Earth Observation mission which consists in developing a hyperspectral satellite to support EU policies on the management of natural resources, ultimately helping to address the global issue of food security. One of the mission activities is associated to the development of the CHIME-E2E (End-to-End) Performance Simulator that shall be used to evaluate the sensor design and future processing modules provided by the partners by simulating future CHIME images and thematic products. In the frame of this activity, the CHIME Mission Advisory Group (MAG) has identified a collection of five core high priority products (HPP) that includes the retrieval of canopy nitrogen, leaf nitrogen content, leaf mass/area, soil organic carbon content (SOC) and kaolinite abundance. In this paper, we present the first results of applying the L2B prototype processing to hyperspectral airborne and spatial imagery used to simulate realistic CHIME data, to derive soil and mineral maps. The obtained results demonstrate the potential of the next generation of Copernicus missions with high spectral resolution and wide swath imaging satellite for geoscience research and applications.

This work aims to characterize the surface of an Italian geothermal field, Parco Naturalistico delle Biancane (PNB), by using hyperspectral data and define the main diagnostic spectral features of lithotypes affected by mineral alteration due to geothermal activity. Hyperspectral data acquired by PRISMA (Hyperspectral Precursor of the Application Mission) and AVIRIS-NG (Airborne Visible / Infrared Imaging Spectrometer – Next Generation), coupled with a spectral library of the main lithotype of the area, represent the dataset used for the analysis. All the spectral data cover the VNIR (Visible and Near InfraRed) and SWIR (Short-Wave InfraRed) spectral range. The Material Identification and Characterization Algorithm (MICA) has been used to perform the comparison between the spectral features from the spectral library and the PRISMA and AVIRIS hyperspectral images in order to obtain an automatic lithotype classification map.

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.

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).

Current EO satellite missions providing imagery in the VIS- TIR region at high spatial resolution offer the possibility to estimate a number of important parameters to monitor volcanic activities at worldwide level. Therefore, space missions contribute in understanding the ongoing phenomena to mitigate the volcanic risk when population and infrastructures are exposed. New hyperspectral and thermal missions which could provide images at high spatial and temporal resolution are under study in cooperation between Space Agencies (NASA, ASI, ESA etc.) and hopefully will improve the monitoring capabilities of active volcanoes in highly populated areas. In the present work we describe several results obtained in the last years by EO satellite missions for the volcanic risk. While the satellite data provide a wide description of scenes, in situ and proximal measurements are crucial to retrieve gas emissions and analyze surface characteristics at very high spatial resolution. Data acquired from drones (UAV) and thermal cameras in volcanic areas are presented and discussed. Moreover, this work shows the need of validation process for satellite products comparing with measurements collected during field campaigns.

In June 2019 the ESA organized the airborne SurfSense campaign in the frame of the study of Copernicus candidate High Spatio-Temporal Resolution Land Surface Temperature Monitoring (LSTM) mission study. Parco delle Biancane was added as secondary target since the occurrence of a field campaign organized by INGV aimed to measure surface temperature using data acquired by different sensors at different spatial resolutions: Earth Observation (EO) data from the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS, [1]) and thermal images acquired by the FlyBit drone. In addition to these data, the airborne sensor Hyperspectral Thermal Emission Spectrometer (HyTES) was flown over the area. Our goal is to test the possibility to integrate data at different observation scales and to use the proximal measurements to better understand the thermal structure, the interaction of the environment in test areas and to validate the methodology for estimating the surface temperature by using EO data.

In this work data observed by the geostationary MSG-SEVIRI and the polar NASA-Terra/Aqua-MODIS orbiting satellite instruments, have been used for the proximal and distal monitoring of the 24-30 December 2018 Etna eruption. The combined use of the SEVIRI high repetition time and the MODIS high spatial resolution allows a reliable near real time volcanic characterization from the source to the atmosphere. For the proximal monitoring the parameters estimated are the eruption starts and duration and the volcanic plume top height, while the distal monitoring was inverted relying on the determination of the volcanic cloud altitude and the ash/SO2retrievals. Achieved products were validated by comparing these results with those observed remotely by ground based networks.Results obtained in this study show the ability of satellite-based systems to entirely follow eruptive events in near real time, offering a powerful tool to mitigate volcanic risk on both local population and airspace.

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.

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.

The algorithm described in this paper approaches the atmospheric correction of hyperspectral data as a spectral unmixing problem, minimizing the need of a priori information on atmospheric conditions and maximizing the advantage of hyperspectral data. The proposed method is foreseen to be used for the processing of the HypSEO mission data, an Italian Space Agency future mission aimed to the demonstration of the spaceborne hyperspectral sensor technology and data exploitation.