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The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model's precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms. [ABSTRACT FROM AUTHOR]

Xylella Fastidiosa has been recently detected for the first time in southern Italy, representing a very dangerous phytobacterium capable of inducing severe diseases in many plants. In particular, the disease induced in olive trees is called olive quick decline syndrome (OQDS), which provokes the rapid desiccation and, ultimately, death of the infected plants. In this paper, we analyse about two thousands pixels of MODIS satellite evapotranspiration time series, covering infected and uninfected olive groves in southern Italy. Our aim is the identification of Xylella Fastidiosa-linked patterns in the statistical features of evapotranspiration data. The adopted methodology is the well-known Fisher–Shannon analysis that allows one to characterize the time dynamics of complex time series by means of two informational quantities, the Fisher information measure (FIM) and the Shannon entropy power (SEP). On average, the evapotranspiration of Xylella Fastidiosa-infected sites is characterized by a larger SEP and lower FIM compared to uninfected sites. The analysis of the receiver operating characteristic curve suggests that SEP and FIM can be considered binary classifiers with good discrimination performance that, moreover, improves if the yearly cycle, very likely linked with the meteo-climatic variability of the investigated areas, is removed from the data. Furthermore, it indicated that FIM exhibits superior effectiveness compared to SEP in discerning healthy and infected pixels. [ABSTRACT FROM AUTHOR]

Analysis of a series of thermal mappings obtained by UAS flights on quiescent volcanoes requires some special techniques to be performed. The main challenge is represented by the difficulty of separating hot and cold pixels in areas where their temperatures are quite similar. This task is indeed much simpler, for example, for lava flows where the temperature differences between the hot lava and the cold soil is rather big. This paper shows various software developed in order to perform this extraction and calculate the trends over time of both the average temperature and the heat flux from the soil. This prototypal implementation used thermal flights performed over a time span of a few years on an area in the Campi Flegrei caldera in southern Italy. Standard image manipulation techniques were used to segmentate and clusterise each thermal mapping in order to reduce the thermal anomalies to some sets of simpler features characterised by their fundamental parameters. The temporal trends of some physical parameters (temperature, heat flux, etc.) were extracted from these sets, and we found interesting results necessary for correlations and for ongoing research with other parameters. [ABSTRACT FROM AUTHOR]

In this paper, we complete pioneering research that indicates the very low frequency (VLF) signal amplitude and phase noise reductions, and short-period wave excitations and attenuations as new potential earthquake precursors. We consider changes in the VLF signal broadcast in Italy by the ICV transmitter and recorded in Serbia that start a few tens of minutes before earthquakes. The sampling interval of the analyzed data is 0.1 s. The main objectives of this study are (1) to complete this research in the time and frequency domains during the periods of the four earthquakes analyzed in the previous studies, and (2) to define the parameters of the VLF signal amplitude and phase in both domains that should be further examined in statistical analyses of the aforementioned potential earthquake precursors. In the first part of this study, we analyze the ICV signal amplitude in the frequency domain during the period around three earthquakes that occurred in November 2010 near the considered signal propagation path. Here, we apply the Fourier transform to the relevant recorded data. In the second part, we compare characteristics of the signal amplitude and phase noise reductions in the time domain, and wave excitations and attenuations in the frequency domain. The results of these comparisons indicate the parameters that should be analyzed in subsequent studies to confirm the connection of the considered VLF signal changes with seismic activity before earthquakes, and potentially establish procedures for their detection are: (a) the start and end times of the noise reductions in the time domain and the excited/attenuated waves in the frequency domain, (b) the differences in the corresponding times, and (c) the wave periods of wave excitations of both the signal amplitude and phase. [ABSTRACT FROM AUTHOR]

This paper provides an assessment of a 24 GHz multiple-input multiple-output radar as a remote sensing tool to retrieve bathymetric maps in coastal areas. The reconstruction procedure considered here exploits the dispersion relation and has been previously employed to elaborate the data acquired via X-band marine radar. The estimation capabilities of the sensor are investigated firstly on synthetic radar data. With this aim, case studies referring to sea waves interacting with a constant and a spatially varying bathymetry are both considered. Finally, the reconstruction procedure is tested by processing real data recorded at Bagnoli Bay, Naples, South Italy. The preliminary results shown here confirm the potential of the radar sensor as a tool for sea wave monitoring. [ABSTRACT FROM AUTHOR]

Coastal managers, policymakers, and scientists use shoreline accretion/erosion trends to determine the coastline's historical evolution and generate models capable of predicting future changes. Different solutions have been developed to obtain shoreline positions from Earth observation data in recent years, the so-called Satellite-Derived Shorelines (SDS). Most of the methodologies available in the literature use multispectral optical satellite imagery. This paper proposes two new methods for shoreline mapping at the subpixel level based on PRISMA hyperspectral imagery. The first one analyses the spectral signatures along defined beach profiles. The second method uses techniques more commonly applied to multispectral image analysis, such as Spectral Unmixing algorithms and Spatial Attraction Models. The results obtained with both methodologies are validated on three Mediterranean microtidal beaches located in two different countries, Italy and Greece, using image-based ground truth shorelines manually photointerpreted and digitised. The obtained errors are around 6 and 7 m for the first and second methods, respectively. These results are comparable to the errors obtained from multispectral data. The paper also discusses the capability of the two methods to identify two different shoreline proxies. [ABSTRACT FROM AUTHOR]

Deep-seated gravitational slope deformations (DsGSDs) are slope-scale phenomena which are widespread in mountainous regions. Despite interacting with human infrastructures and settlements, only a few cases are monitored with ground-based systems. Remote sensing technologies have recently become a consolidated instrument for monitoring and studying such widespread and slow processes. This paper proposes a three-step novel methodology to analyze the morpho-structural domain of DsGSDs by exploiting the advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) technique through (i) the analysis of A-DInSAR measurement point density and distribution defining a coverage threshold; (ii) the assessment of the actual ground deformation with respect to the orientation of phenomena based on slope, aspect, and C-index; and (iii) ground deformation mapping with previously ranked velocity interpolation. The methodology was tested on two differently oriented phenomena: the mainly north–south-oriented Croix de Fana and the mainly east–west-oriented Valtournenche DsGSD, located in the Aosta Valley Region, northern Italy. The results show a variation in the kinematic behavior between the morpho-structural domains, while also considering any other superimposed surficial deformations. This work provides the lines for the implementation of a rapid and low-cost tool based on the use of A-DInSAR measurements which are suitable for assessing the impact of any type of DsGSD on the anthropic facilities and infrastructures in mountainous areas. [ABSTRACT FROM AUTHOR]

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years. [ABSTRACT FROM AUTHOR]

This paper presents a study on applying satellite Interferometric Synthetic Aperture Radar (InSAR) technology for the remote monitoring of road bridges and interpreting the results from a structural standpoint. The motivation behind this study arises from the widespread deterioration observed in many road bridges worldwide, leading to the need for large-scale, economic, and effective structural health monitoring (SHM) techniques. While traditional contact-type sensors have cost sustainability limitations, remote sensing techniques, including satellite-based InSAR, offer interesting alternative solutions. The objective of this study is three-fold: (i) to process InSAR data specifically for road bridges in operational conditions through the Multi-Temporal InSAR technique and extract displacement time series of reflective targets on their decks; (ii) to interpret the observed millimetric bridge displacements to verify the consistency with expected response to environmental loads and the possibility to detect unexpected behaviours; and (iii) to investigate the correlation between bridge displacements and environmental loads as temperature and river water flow variations. The study focuses on the multi-span prestressed concrete A22 Po River Bridge in Italy, utilising a dataset of X-Band HIMAGE mode Stripmap images acquired over eight years by the satellite constellation COSMO-SkyMed. The study demonstrates the effectiveness of InSAR-based SHM in detecting temperature-induced displacements and identifying different bridge spans simply by studying the sign of the correlation between displacements and temperature variation. It also reveals an unexpected behaviour in a portion of the bridge retrofitted to prevent scour issues a few years before the dataset start date. Furthermore, the correlation between pier displacements and river level variations underscores the importance of considering environmental factors and the geotechnical characteristics of the foundation soils in bridge monitoring. The results obtained from this study are significant with a view to using this satellite InSAR-based monitoring for early detection of anomalous bridge behaviour on a large scale. [ABSTRACT FROM AUTHOR]

The study reported in this paper concerns the temporal variation in the b-value of the Gutenberg–Richter frequency–magnitude law, applied to the earthquakes that struck Italy from 2009 to 2016 in the geographical areas of L'Aquila, the Emilia Region, and Amatrice–Norcia. Generally, the b-value varies from one region to another dependent on earthquake incidences. Higher values of this parameter are correlated to the occurrence of low-magnitude events spread over a wide geographical area. Conversely, a lower b-value may lead to the prediction of a major earthquake localized along a fault. In addition, it is observed that each seismic event has a different "occurrence time", which is a key point in the statistical study of earthquakes. In particular, its results are absolutely different for each specific event, and may vary from years to months or even just a few hours. Hence, both short- and long-term precursor phenomena have to be examined. Accordingly, the b-value analysis has to be performed by choosing the best time windows to study the foreshock and aftershock activities. [ABSTRACT FROM AUTHOR]

This work describes a procedure for building a high-quality 3D model of a rocky pinnacle in the Dolomites, Italy, using Structure from Motion (SfM) techniques. The pinnacle, known as "Campanile di Val Montanaia", is challenging to survey due to its high elevation and sub-vertical cliffs. The construction of the 3D model is the first step in a multi-disciplinary approach to characterize the rock mass and understand its behavior and evolution. This paper discusses the surveying operations, which involved climbing the pinnacle to collect Ground Control Points (GCPs) and using a UAV to capture aerial imagery. The photographs were processed using SfM software to generate point clouds, mesh, and texture, which were then used for rock mass discontinuity mapping. The study compares models of different qualities and point densities to determine the optimal trade-off between processing time and accuracy in terms of discontinuity mapping. The results show that higher quality models allow for more detailed mapping of discontinuities, with some drawbacks due to noise in the case of the densest solution (e.g., increase in frequency of outliers across the point cloud). These pros and cons are also discussed in relation to the computational cost necessary to build the models. The study also examines the limitations and challenges of performing discontinuity mapping in the different models, including subjectivity in interpretation. A further element of interest is the publication of a high-quality 3D georeferenced model of the "Campanile di Val Montanaia" to be used for several potential further applications, such as stability analyses and numerical modeling. [ABSTRACT FROM AUTHOR]

Traditional soil characterization methods are time consuming, laborious and invasive and do not allow for long-term repeatability of measurements. The overall aim of this paper was to assess and model spatial variability of the soil in an olive grove in south Italy by using data from two sensors of different types: a multi-spectral on-board drone radiometer and a hyperspectral visible-near infrared-shortwave infrared (VIS-NIR-SWIR) reflectance radiometer, as well as sample data, to arrive at a delineation of homogeneous areas. The hyperspectral data were processed using Continuum Removal (CR) methodology to obtain information about the content and composition of clay. Differently, the multispectral data were firstly upscaled to the support of soil data using geostatistics and taking into account the change of support. Secondly, the data acquired with the two different sensors were integrated with soil granulometric properties by using two multivariate geostatistical techniques: multi-collocated cokriging to achieve a more exhaustive and finer-scale soil characterization, and multi-collocated factor cokriging to extract synthetic scale-dependent indices (regionalized factors) for the delineation of soil in homogeneous zones. This paper shows the impact of change of support on the uncertainty of soil prediction that can have a significant effect on decision making in Precision Agriculture. Moreover, four regionalized factors at two different scales (two for each scale) were retained and mapped. Each factor provided a different delineation of the field with areas characterized by different granulometries and clay compositions. The applied method is sufficiently flexible and could be applied to any number and type of sensors. [ABSTRACT FROM AUTHOR]

In the second half of the twentieth century, after the end of the Second World War, a considerable anthropogenic pressure was observed in most of the Mediterranean territories. This process has caused the expansion of existing settlements and the construction of numerous new towns, often located very close to rivers. A frequent consequence of this process is the transformation of several rivers through planform changes, narrowing, channelization and culverting to recover spaces where inhabited centers expanded, and the construction of structures interacting with rivers. This issue is very important in territories such as the Metropolitan City of Reggio Calabria, in southern Italy, which is an interesting case study due to the considerable anthropogenic pressures observed in the last 70 years. The main goal of this paper is to evaluate the effects of anthropogenic pressure in the last 70 years on some rivers of the Metropolitan City of Reggio Calabria in terms of the following issues: planform changes, channelization, culverting, and the presence of structures and infrastructures interacting with rivers. The specific goals of this paper are the quantification of the effects of anthropogenic pressure on the rivers of the study area analyzing sixteen parameters, the identification of possible conditions of hydraulic hazard through the analysis of past events, and the proposal of structural and non-structural mitigation interventions. In many rivers of the study area, the significant effects of anthropogenic pressure are visible through rivers that pass above highways, barred rivers, rivers replaced by roads and numerous crossing roads with a missing levee. [ABSTRACT FROM AUTHOR]

Volcanic plume height is one the most important features of explosive activity; thus, it is a parameter of interest for volcanic monitoring that can be retrieved using different remote sensing techniques. Among them, calibrated visible cameras have demonstrated to be a promising alternative during daylight hours, mainly due to their low cost and low uncertainty in the results. However, currently these measurements are generally not fully automatic. In this paper, we present a new, interactive, open-source MATLAB tool, named 'Plume Height Analyzer' (PHA), which is able to analyze images and videos of explosive eruptions derived from visible cameras, with the objective of automatically identifying the temporal evolution of eruption columns. PHA is a self-customizing tool, i.e., before operational use, the user must perform an iterative calibration procedure based on the analysis of images of previous eruptions of the volcanic system of interest, under different eruptive, atmospheric and illumination conditions. The images used for the calibration step allow the computation of ad hoc expressions to set the model parameters used to recognize the volcanic plume in new images, which are controlled by their individual characteristics. Thereby, the number of frames used in the calibration procedure will control the goodness of the model to analyze new videos/images and the range of eruption, atmospheric, and illumination conditions for which the program will return reliable results. This also allows improvement of the performance of the program as new data become available for the calibration, for which PHA includes ad hoc routines. PHA has been tested on a wide set of videos from recent explosive activity at Mt. Etna, in Italy, and may represent a first approximation toward a real-time analysis of column height using visible cameras on erupting volcanoes. [ABSTRACT FROM AUTHOR]

Illegal archaeological excavations, generally denoted as looting, is one of the most important damage factors to cultural heritage, as it upsets the human occupation stratigraphy of sites of archaeological interest. Looting identification and monitoring are not an easy task. A consolidated instrument used for the detection of archaeological features in general, and more specifically for the study of looting is remote sensing. Nevertheless, passive optical remote sensing is quite ineffective in dense vegetated areas. For these type of areas, in recent decades, LiDAR data and its derivatives have become an essential tool as they provide fundamental information that can be critical not only for the identification of unknown archaeological remains, but also for monitoring issues. Actually, LiDAR can suitably reveal grave robber devastation, even if, surprisingly, up today LiDAR has been generally unused for the identification of looting phenomenon. Consequently, this paper deals with an approach devised ad hoc for LiDAR data to detect looting. With this aim, some spatial visualization techniques and the geomorphon automatic landform extraction were exploited to enhance and extract features linked to the grave robber devastation. For this paper, the Etruscan site of San Giovenale (Northern Lazio, Italy) was selected as a test area as it is densely vegetated and was deeply plundered throughout the 20th century. Exploiting the LiDAR penetration capability, the prediction ability of the devised approach is highly satisfactory with a high rate of success, varying from 85–95%. [ABSTRACT FROM AUTHOR]

Structural Health Monitoring (SHM) represents a very powerful tool to assess the health condition of buildings. In recent years, the growing availability of high-resolution SAR satellite images has made possible the application of multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques for structural monitoring purposes, with high precision, low costs, timesaving, and the possibility to investigate wide areas. However, a comprehensive validation of the effectiveness of MT-InSAR in this application field has not been achieved yet. For this reason, in this paper a comparison between interferometric data and on-site measurement of displacements is proposed. The application case study is the Civic Tower of the city of L'Aquila (Abruzzo Region, Italy). After the seismic events that affected the area in 2009, an on-site monitoring system was installed on the tower to detect any changes in the damage pattern in the period 2010–2013. Furthermore, images acquired by COSMO-SkyMed constellation in Stripmap mode (~3 m resolution) during the same period were processed by the Permanent Scatterer-InSAR (PSI) technique to estimate the deformation of the structure and the surrounding area. The obtained results indicate that both methods are consistent in the measurement of displacement trends of the building and a slight rotation/displacement of the tower was detected. Such evidence highlights both the huge potential and the limitations of using InSAR techniques for SHM. [ABSTRACT FROM AUTHOR]

An interdisciplinary study of the ancient landscape of the Trieste Karst (north-eastern Italy) is presented in this paper. Airborne Laser Scanning (ALS) has been applied to obtain high-resolution topography of the 25 km2 investigated area in order to identify potential archaeological anomalies. The ALS-derived high-resolution Digital Terrain Models have been visualized and managed using QGIS and Relief Visualization Toolbox. Possible archaeological anomalies have been verified through field surveys and interpreted using a multidisciplinary approach mainly based on the collection of associated archaeological materials and geomorphological and stratigraphic evidence. From a methodological perspective, the elaboration and study of ALS-derived images, and in particular the local relief model visualization, combined with the collection of Roman shoe hobnails, have proven to be effective approaches for the certain identification and dating of Roman roads in karst environments. The obtained results have revealed an almost completely unknown Roman landscape: the investigated area was crossed by important public roads, whose layout has been accurately reconstructed for a total length of over 10 km, and occupied by large country estates, sometimes enclosed within boundary walls perfectly fitting the Roman land division grid. One of the identified buildings could correspond to a road station, perhaps the Avesica known from ancient itinerary documents—i.e., the itinerarium Antonini Augusti—due to its position and proximity to a major road junction. [ABSTRACT FROM AUTHOR]

The modeling and simulation of topography-induced imaging distortions are crucial for consistent radiometric information exploitation in current and forthcoming SAR-based Earth observation missions with a high spatial and temporal resolution, with relevance in several applications. In this paper, for the first time, we specifically investigate the compensation of topography-induced radiometric distortions affecting SAR images acquired by the L-band Argentinian satellite SAOCOM. We adopt a recently developed calibration method relying on an analytical formulation derived in the rigorous framework of the differential geometry of surfaces. We first provide an original interpretation of the analytical formulation, thus providing further insights into the relevant area-stretching-based formalism. Then, the numerical implementation of the method is specialized to systematically process the data acquired by SAOCOM sensors; hence, the resulting sensor-specific prototype solution processor is employed in this study. Finally, experiments performed over a real scenario in the southern part of Italy, characterized by large topography variations, are presented and discussed, thus elucidating the effectiveness of the adopted method applied to SAOCOM images. The adopted effective SAR calibration strategy opens up the way to its operational use in large-scale SAOCOM data processing. [ABSTRACT FROM AUTHOR]

Satellite interferometry has recently developed as a powerful tool for monitoring displacements on structures for structural health monitoring (SHM), as it allows obtaining information on past deformation and performing back analysis on structural behavior. Despite the increasing literature on this subject, the lack of protocols for applying and interpreting interferometric data for structural assessment prevents these techniques from being employed alongside conventional SHM. This paper proposes a methodology for exploiting satellite interferometric data aiming at remotely detecting displacements and buildings' criticalities at different levels of analysis, i.e., urban scale and single-building scale. Moreover, this research exploits the capability of satellite monitoring for damage diagnosis, comparing the millimeter scale displacements to information derived from on-site inspections. Different data-driven algorithms were applied to detect seasonal and irreversible components of displacements, such as statistical models for damage identification derived from traditional on-site monitoring. Thus, the proposed methodology was applied to a XVI-century case study located in the city center of Rome (Italy), Palazzo Primoli, and two stocks of COSMO-SkyMed (CSK) images processed through the Small BAseline Subset Differential Interferometry (SBAS-DInSAR) technique were used to assess displacements for an eight-year-long (between 2011 and 2019) monitoring period. [ABSTRACT FROM AUTHOR]

Earth flows are complex gravitational events characterised by a heterogeneous displacement pattern in terms of scale, style, and orientation. As a result, their monitoring, for both knowledge and emergency purposes, represents a relevant challenge in the field of engineering geology. This paper aims to assess the capabilities, peculiarities, and limitations of different remote sensing monitoring techniques through their application to the Pietrafitta earth flow (Southern Italy). The research compared and combined data collected during the main landslide reactivations by different ground-based remote sensors such as Robotic Total Station (R-TS), Terrestrial Synthetic Aperture Radar Interferometry (T-InSAR), and Terrestrial Laser Scanner (TLS), with data being derived by satellite-based Digital Image Correlation (DIC) analysis. The comparison between R-TS and T-InSAR measurements showed that, despite their different spatial and temporal resolutions, the observed deformation trends remain approximately coherent. On the other hand, DIC analysis was able to detect a kinematic process, such as the expansion of the landslide channel, which was not detected by the other techniques used. The results suggest that, when faced with complex events, the use of a single monitoring technique may not be enough to fully observe and understand the processes taking place. Therefore, the limitations of each different technique alone can be solved by a multi-sensor monitoring approach. [ABSTRACT FROM AUTHOR]

In this paper, we propose a processing chain jointly employing Sentinel-1 and Sentinel-2 data, aiming to monitor changes in the status of the vegetation cover by integrating the four 10 m visible and near-infrared (VNIR) bands with the three red-edge (RE) bands of Sentinel-2. The latter approximately span the gap between red and NIR bands (700 nm–800 nm), with bandwidths of 15/20 nm and 20 m pixel spacing. The RE bands are sharpened to 10 m, following the hyper-sharpening protocol, which holds, unlike pansharpening, when the sharpening band is not unique. The resulting 10 m fusion product may be integrated with polarimetric features calculated from the Interferometric Wide (IW) Ground Range Detected (GRD) product of Sentinel-1, available at 10 m pixel spacing, before the fused data are analyzed for change detection. A key point of the proposed scheme is that the fusion of optical and synthetic aperture radar (SAR) data is accomplished at level of change, through modulation of the optical change feature, namely the difference in normalized area over (reflectance) curve (NAOC), calculated from the sharpened RE bands, by the polarimetric SAR change feature, achieved as the temporal ratio of polarimetric features, where the latter is the pixel ratio between the co-polar and the cross-polar channels. Hyper-sharpening of Sentinel-2 RE bands, calculation of NAOC and modulation-based integration of Sentinel-1 polarimetric change features are applied to multitemporal datasets acquired before and after a fire event, over Mount Serra, in Italy. The optical change feature captures variations in the content of chlorophyll. The polarimetric SAR temporal change feature describes depolarization effects and changes in volumetric scattering of canopies. Their fusion shows an increased ability to highlight changes in vegetation status. In a performance comparison achieved by means of receiver operating characteristic (ROC) curves, the proposed change feature-based fusion approach surpasses a traditional area-based approach and the normalized burned ratio (NBR) index, which is widespread in the detection of burnt vegetation. [ABSTRACT FROM AUTHOR]

Mapping urban areas from space is a complex task involving the definition of what should be considered as part of an urban agglomerate beyond the built-up features, thus modelling the transition of a city into the surrounding landscape. In this paper, a new technique to map urban areas using multitemporal synthetic aperture radar data is presented. The proposed methodology exploits innovative RGB composites in combination with self-organizing map (SOM) clustering and object-based image analysis. In particular, the clustered product is used to extract a coarse urban area map, which is then refined using object-based processing. In this phase, Delaunay triangulation and the spatial relationship between the identified urban regions are used to model the urban–rural gradient between a city and the surrounding landscape. The technique has been tested in different scenarios representative of structurally different cities in Italy and Germany. The quality of the obtained products is assessed by comparison with the Urban Atlas of the European Environmental Agency, showing good agreement with the adopted reference data despite their different taxonomies. [ABSTRACT FROM AUTHOR]

In this paper, characterization of the optical and microphysical properties of extremely fresh biomass burning aerosol is presented. This work aims to characterize, for the first time to our knowledge, freshly formed smoke particles observed only a few minutes after they were emitted from a nearby forest fire. The smoke particles were detected by combining passive (sun-photometer) and active (Raman lidar) techniques. On 14 August 2021, an EARLINET (European Aerosol Research Lidar Network) multi-wavelength Raman lidar and a co-located AERONET sun-photometer in Potenza, South Italy, observed an extremely fresh smoke plume. The lidar measurements, carried out from 22:27 to 02:16 UTC, revealed a thick biomass burning layer below 2.7 km. The particle depolarization ratio at 532 nm was 0.025, and lidar ratios at 355 and 532 nm were, respectively, 40 and 38 sr. The mean value of the Ångström exponent was 1.5. The derived size distribution was bimodal with a peak at 0.13 µm, an effective radius mean value of 0.15 µm, and a single scattering albedo of 0.96 at all wavelengths. The real part of the refractive index was 1.58 and the imaginary was 0.006. The AERONET measurements at 5:34 UTC confirmed the lidar measurements. [ABSTRACT FROM AUTHOR]

This paper explored the relationship between acidic sulfate alteration, geostructural frameworks, and geomorphological changes that can be observed in active volcanic hydrothermal systems. The target area was Pisciarelli in the Campi Flegrei volcano, where diffuse acidic sulfate alteration and hydrothermal dynamics have been growing since 2012, causing a progressive deterioration of landscapes. Terrestrial Laser Scanner (TLS), photogrammetry of proximity survey, geological field work, mineralogical and geochemical analysis with Optical Microscopy (OM), electron microscopy, and energy dispersive micro-analysis (BSEM-EDS) and X-ray Powder Diffraction (XRPD) to characterize (and monitor) altered rock outcrops were repeatedly carried out in the area. We present the multi-temporal acquisition and analysis referring to Terrestrial Laser Scanning (TLS) datasets (2014 survey) with 3D-point clouds obtained from the Structure for Motion (SfM) photogrammetry (2021 survey) with a high-resolution digital camera aimed at evaluating volumetric changes on the mostly damaged and altered fault scarp. For each survey, we obtained a vertical Digital Elevation Model (DEM) and a true color RGB orthomosaic that provided the setting of the area at the different times and its evolution through their comparison. Changing sites were examined in the field and characterized for mineralogical and geochemical purposes. The investigated slope lost up to about 4 m3 of deposits between 2014 and 2021, mostly related to hydrothermal alteration induced by gas emissions and meteoric infiltration. Our methodological approach appears promising to evaluate evolution and rock-fall susceptibility of solfataric terrains subjected to hydrothermal dynamics. [ABSTRACT FROM AUTHOR]

Lightning is an important threat to life and properties and its forecast is important for several applications. In this paper, we show the performance of the "dynamic lightning scheme" for next-day total strokes forecast. The predictions were compared against strokes recorded by a ground observational network for a forecast period spanning one year. Specifically, a total of 162 case studies were selected between 1 March 2020 and 28 February 2021, characterized by at least 3000 observed strokes over Italy. The events span a broad range of lightning intensity from about 3000 to 600,000 strokes in one day: 69 cases occurred in summer, 46 in fall, 18 in winter, and 29 in spring. The meteorological driver was the Weather Research and Forecasting (WRF) model (version 4.1) and we focused on the next-day forecast. Strokes were simulated by adding three extra variables to WRF, namely, the potential energies for positive and negative cloud to ground flashes and intracloud strokes. Each potential energy is advected by WRF, it is built by the electrification processes occurring into the cloud, and it is dissipated by lightning. Observed strokes were remapped onto the WRF model grid with a 3 km horizontal resolution for comparison with the strokes forecast. Results are discussed for the whole year and for different seasons. Moreover, statistics are presented for the land and the sea. In general, the results of this study show that lightning forecast with the dynamic lightning scheme and WRF model was successful for Italy; nevertheless, a careful inspection of forecast performance is necessary for tuning the scheme. This tuning is dependent on the season. A numerical experiment changing the microphysics scheme used in WRF shows the sensitivity of the results according to the choice of the microphysics scheme. [ABSTRACT FROM AUTHOR]

The Etna volcano is renowned worldwide for its extraordinary lava fountains that rise several kilometers above the vent and feed eruptive columns, then drift hundreds of kilometers away from the source. The Italian Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) is responsible for the monitoring of Mt. Etna, and for this reason, has deployed a network of visible and thermal cameras around the volcano. From these cameras, INGV-OE keeps a keen eye, and is able to observe the eruptive activity, promptly advising the civil protection and aviation authorities of any changes, as well as quantifying the spread of lava flows and the extent of pyroclastic and ash plumes by using a careful analysis of the videos recorded by the monitoring cameras. However, most of the work involves analysis carried out by hand, which is necessarily approximate and time-consuming, thus limiting the usefulness of these results for a prompt hazard assessment. In addition, the start of lava fountains is often a gradual process, increasing in strength from Strombolian activity, to intermediate explosive activity, and eventually leading to sustained lava fountains. The thresholds between these different fields (Strombolian, Intermediate, and lava fountains) are not clear cut, and are often very difficult to distinguish by a manual analysis of the images. In this paper, we presented an automated routine that, when applied to thermal images and with good weather conditions, allowed us to detect (1) the starting and ending time of each lava fountain, (2) the area occupied by hot pyroclasts, (3) the elevation reached by the lava fountains over time, and (4) eventually, to calculate in real-time the erupted volume of pyroclasts, giving results close to the manual analysis but more focused on the sustained portion of the lava fountain, which is also the most dangerous. This routine can also be applied to other active volcanoes, allowing a prompt and uniform definition of the timing of the lava fountain eruptive activity, as well as the magnitude and intensity of the event. [ABSTRACT FROM AUTHOR]

In March 2019, the PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite was launched by the Italian Space Agency (ASI), and it is currently operational on a global basis. The mission includes the hyperspectral imager PRISMA working in the 400–2500 nm spectral range with 237 bands and a panchromatic (PAN) camera (400–750 nm). This paper presents an evaluation of the PRISMA top-of-atmosphere (TOA) L1 products using different in situ measurements acquired over a fragmented rural area in Southern Italy (Pignola) between October 2019 and July 2021. L1 radiance values were compared with the TOA radiances simulated with a radiative transfer code configured using measurements of the atmospheric profile and the surface spectral characteristics. The L2 reflectance products were also compared with the data obtained by using the ImACor code atmospheric correction tool. A preliminary assessment to identify PRISMA noise characteristics was also conducted. The results showed that: (i) the PRISMA performance, as measured at the Pignola site over different seasons, is characterized by relative mean absolute differences (RMAD) of about 5–7% up to 1800 nm, while a decrease in accuracy was observed in the SWIR; (ii) a coherent noise could be observed in all the analyzed images below the 630th scan line, with a frequency of about 0.3–0.4 cycles/pixel; (iii) the most recent version of the standard reflectance L2 product (i.e., Version 2.05) matched well the reflectance values obtained by using the ImACor atmospheric correction tool. All these preliminary results confirm that PRISMA imagery is suitable for an accurate retrieval of the bio-geochemical variables pertaining to a complex fragmented ecosystem such as that of the Southern Apennines. Further studies are needed to confirm and monitor PRISMA data performance on different land-cover areas and on the Radiometric Calibration Network (RadCalNet) targets. [ABSTRACT FROM AUTHOR]

The paper explores the potential of the satellite advanced differential synthetic aperture radar interferometry (A-DInSAR) technique for the identification of impending slope failure. The advantages and limitations of satellite InSAR in monitoring pre-failure landslide behaviour are addressed in five different case histories back-analysed using data acquired by different satellite missions: Montescaglioso landslide (2013, Italy), Scillato landslide (2015, Italy), Bingham Canyon Mine landslide (2013, UT, USA), Big Sur landslide (2017, CA, USA) and Xinmo landslide (2017, China). This paper aimed at providing a contribution to improve the knowledge within the subject area of landslide forecasting using monitoring data, in particular exploring the suitability of satellite InSAR for spatial and temporal prediction of large landslides. The study confirmed that satellite InSAR can be successful in the early detection of slopes prone to collapse; its limitations due to phase aliasing and low sampling frequency are also underlined. According to the results, we propose a novel landslide predictability classification discerning five different levels of predictability by satellite InSAR. Finally, the big step forward made for landslide forecasting applications since the beginning of the first SAR systems (ERS and Envisat) is shown, highlighting that future perspectives are encouraging thanks to the expected improvement of upcoming satellite missions that could highly increase the capability to monitor landslides' pre-failure behaviour. [ABSTRACT FROM AUTHOR]

Modeling of synthetic aperture radar (SAR) imaging distortions induced by topography is addressed and a novel radiometric calibration method is proposed in this paper. An analytical formulation of the problem is primarily provided in purely geometrical terms, by adopting the theoretical notions of the differential geometry of surfaces. The novel and conceptually simple formulation relies on a cylindrical coordinate system, whose longitudinal axis corresponds to the sensor flight direction. A 3D representation of the terrain shape is then incorporated into the SAR imaging model by resorting to a suitable parametrization of the observed ground surface. Within this analytical framework, the area-stretching function quantitatively expresses in geometrical terms the inherent local radiometric distortions. This paper establishes its analytical expression in terms of the magnitude of the gradient of the look-angle function uniquely defined in the image domain, thus resulting in being mathematically concise and amenable to a straightforward implementation. The practical relevance of the formulation is also illustrated from a computational perspective, by elucidating its effective discrete implementation. In particular, an inverse cylindrical mapping approach is adopted, thus avoiding the drawback of pixel area fragmentation and integration required in forward-mapping-based approaches. The effectiveness of the proposed SAR radiometric calibration method is experimentally demonstrated by using COSMO-SkyMed SAR data acquired over a mountainous area in Italy. [ABSTRACT FROM AUTHOR]

Local and Regional Authorities require indicators at the intra-urban scale to design adequate policies to foster the achievement of the objectives of Sustainable Development Goal (SDG) 11. Updated high-resolution population density and settlement maps are the basic input products for such indicators and their sub-indicators. When provided at the intra-urban scale, these essential variables can facilitate the extraction of population flows, including both local and regular migrant components. This paper discusses a modification of the dasymetric method implemented in our previous work, aimed at improving the population density estimation. The novelties of our paper include the introduction of building height information and site-specific weight values for population density correction. Based on the proposed improvements, selected indicators/sub-indicators of four SDG 11 targets were updated or newly implemented. The output density map error values are provided in terms of the mean absolute error, root mean square error and mean absolute percentage indicators. The values obtained (i.e., 2.3 and 4.1 people, and 8.6%, respectively) were lower than those of the previous dasymetric method. The findings suggest that the new methodology can provide updated information about population fluxes and processes occurring over the period 2011–2020 in the study site—Bari city in southern Italy. [ABSTRACT FROM AUTHOR]

For decades, bad practices in municipal and industrial waste management have had negative environmental impacts, generating high health risks for people and the environment. The use of badly designed, not engineered, and not well-operated landfills has, around the world, produced a large number of potentially contaminated sites, for which there are urgent needs to assess the actual risk and to proceed, in case, with reclamation activities. One of these sites, an abandoned waste disposal site located near a Site of Community Importance on the central-eastern coast of Sardinia (Italy), is the subject of the case history described in this work. As a part of a multi-method geophysical characterisation, a frequency-domain electromagnetic (FDEM) mapping survey was carried out with the specific aim of detecting the presence of buried materials (waste) and of delineating the lateral extent of the landfill by identifying the electrical conductivity anomalies produced, for the most part, by the conductive waste fill. Using an EM31 device in the vertical-dipole configuration, at a height of 0.9 m above the ground, both quadrature and in-phase electromagnetic responses were collected over a 7-hectare area with elevation varying between 6 m and 2.8 m above sea level. After removing the measurements identified as data coming from any recognisable surface man-made features within the survey area or near its perimeter, the filtered quadrature response (expressed as apparent conductivity) ranged from 5.5 mS/m to about 188.6 mS/m. All values are beyond the low induction number (LIN) condition and valid for the classical EM31 mapping, thus requiring advanced data processing. To obtain undistorted, meaningful, and interpretable high-resolution maps, measured data have been processed to correct the bias, introduced by the nonlinearity of the device, as a function of height above ground and the topography. The comparative analysis of the apparent conductivity map, obtained by the properly processed EM31 data and some aerial photos that clearly documented the site history, has allowed unequivocal delineation of the landfill extent, in good agreement with the results obtained with other geophysical methods (not described in this paper) and with the ground truthing data provided by three boreholes, which were core-drilled at the end of the study at three locations selected on the basis of the apparent conductivity map. [ABSTRACT FROM AUTHOR]

The purpose of the present paper is to investigate the effects of variable eruption source parameters on volcanic plume transport in the Mediterranean basin after the paroxysm of Mount Etna on 23 November 2013. This paroxysm was characterized by a north-east transport of ash and gas, caused by a low-pressure system in northern Italy. It is evaluated here in a joint approach considering the WRF-Chem model configured with eruption source parameters (ESPs) obtained elaborating the raw data from the VOLDORAD-2B (V2B) Doppler radar system. This allows the inclusion of the transient and fluctuating nature of the volcanic emissions to accurately model the atmospheric dispersion of ash and gas. Two model configurations were considered: the first with the climax values for the ESP and the second with the time-varying ESP according to the time profiles of the mass eruption rate recorded by the V2B radar. It is demonstrated that the second configuration produces a considerably better comparison with satellite retrievals from different sensors platforms (Ozone Mapping and Profiler Suite, Meteosat Second-Generation Spinning Enhanced Visible and Infrared Imager, and Visible Infrared Imaging Radiometer Suite). In the context of volcanic ash transport dispersion modeling, our results indicate the need for (i) the use of time-varying ESP, and (ii) a joint approach between an online coupled chemical transport model like WRF-Chem and direct near-source measurements, such as those carried out by the V2B Doppler radar system. [ABSTRACT FROM AUTHOR]

The use of Unmanned Aerial Vehicles (UAV) on wetlands is becoming a common survey technique that is extremely useful for understanding tidal flats and salt marshes. However, its implementation is not straightforward because of the complexity of the environment and fieldwork conditions. This paper presents the morphological evolution of the Po della Pila tidal flat in the municipality of Porto Tolle (Italy) and discusses the reliability of UAV-derived Digital Surface Models (DSMs) for such environments. Four UAV surveys were performed between October 2018 and February 2020 on an 8 ha young tidal flat that was generated, amongst others, as a consequence of the massive sediment injection into the Po Delta system due to the floods of the 1950s and 1960s. The DSM accuracy was tested by processing (i.e., photogrammetry) diverse sets of pictures taken at different altitudes during the same survey day. The DSMs and the orthophotos show that the tidal flat is characterised by several crevasse splays and that the sediment provision depends strictly on the river. During the study period, the sediment budget was positive (gaining 800 m3/year and an average rate of vertical changes of 1.3 cm/year). Comparisons of DSMs demonstrated that neither lower flight altitudes (i.e., 20–100 m) nor the combination of more photos from different flights during the same surveys necessarily reduce the error in such environments. However, centimetric errors (i.e., RMSEs) are achievable flying at 80–100 m, as the increase of GCP (Ground Control Point) density is the most effective solution for enhancing the resolution. Guidelines are suggested for implementing high-quality UAV surveys in wetlands. [ABSTRACT FROM AUTHOR]