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Delirium is highly prevalent among hospitalized older adults and is associated with unfavorable outcomes. However, delirium often remains undiagnosed in the hospital context. Having a valid, simple, and fast screening tool could help in limiting the additional workload for healthcare professionals, without leaving delirium undetected. The aim of this study was to estimate the sensitivity and specificity of the Recognizing Acute Delirium As part of your Routine (RADAR) scale in an Italian hospital. An observational cross-sectional study was conducted. A total of 150 patients aged ≥70 years were enrolled. Receiver operating characteristic (ROC) curves using the Confusion Assessment Method (CAM) criterion-defined delirium as the gold standard were plotted to evaluate the performance of the RADAR scale. The cut-off suggested by previous research was used to estimate the sensitivity, specificity, and positive and negative predictive values of the RADAR scale. The involved patients were mostly females (60%; n = 90), with a median age of 84 years (I–III quartiles: 80–88). According to the CAM and the RADAR scale, 37 (25%) and 58 (39%) patients were classified as experiencing delirium, respectively. The area under the ROC curve of the RADAR scale was 0.916. Furthermore, the RADAR scale showed robust sensitivity (95%), specificity (80%), and positive (60%) and negative predictive values (98%). The RADAR scale is thus suggested to be a valid tool for screening assessment of delirium in hospitalized older adults. [ABSTRACT FROM AUTHOR]

In this research article, we propose a practical methodology for evaluating the affecting potential of detachment areas in rockfalls. Our innovative approach combines an assessment of the visibility of rockfall source areas, with reference to specific rockfall scenarios and elements at risk, considering the rockfall Susceptibility Index to Failure (SIF) of these areas. The result is the characterization of source areas through a rockfall Source Affecting Index (SAI), which considers both the morphology of the slope and the geostructural conditions of the rock walls. This information can be very useful since it aids in optimizing more in-depth analyses, as well as the placement of monitoring instruments or stabilization systems. The proposed methodology has been implemented in the open-source software QGIS through the development of an easy-to-use plugin named Ranking of the Affecting Potential of Detachment Areas in Rockfalls, or "RADAR". RADAR is designed to be used in conjunction with QPROTO, a well-known QGIS plugin for preliminary rockfall susceptibility/hazard analyses based on a visibility analysis and a simplified mechanical method. To demonstrate the effectiveness of the proposed approach, an application to a case study located in the Western Alps (Bardonecchia, Italy) is presented and discussed in the paper. [ABSTRACT FROM AUTHOR]

Clouds cover substantial parts of the Earth's surface and they are one of the most essential components of the global climate system impacting the Earth's radiation balance as well as the water cycle redistributing water around the globe as precipitation. Therefore, continuous observation of clouds is of primary interest in climate and hydrological studies. This work documents the first efforts in Italy in remote sensing clouds and precipitation using a combination of K- and W-band (24 and 94 GHz, respectively) radar profilers. Such a dual-frequency radar configuration has not been widely used yet, but it could catch on in the near future given its lower initial cost and ease of deployment for commercially available systems at 24 GHz, with respect to more established configurations. A field campaign running at the Casale Calore observatory at the University of L'Aquila, Italy, nestled in the Apennine mountain range is described. The campaign features are preceded by a review of the literature and the underpinning theoretical background that might help newcomers, especially in the Italian community, to approach cloud and precipitation remote sensing. This activity takes place in interesting time for radar sensing clouds and precipitation, stimulated both by the launch of the ESA/JAXA EarthCARE satellite missions scheduled in 2024, which will have on-board, among other instruments, a W-band Doppler cloud radar and the proposal of new missions using cloud radars currently undergoing their feasibility studies (e.g., WIVERN and AOS in Europe and Canada, and U.S., respectively). [ABSTRACT FROM AUTHOR]

This study evaluated the effectiveness of various remote sensing (RS) data (Sentinel-1, Sentinel-2, and Landsat 8) in the early recognition of irrigated areas in a densely cultivated area of central Italy. The study was based on crop data collected on more than 2000 plots in 2016 and 2017, characterized by quite different climatic conditions. The different RS data sources were used both alone and combined and with precipitation to define corresponding random forest (RF) classifiers whose overall accuracy (OA) was assessed by gradually increasing the number of available features from the beginning of the irrigation season. All tested RF classifiers reach stable OAs (OA 0.9) after 7-8 weeks from the start of the irrigation season. The performance of the radar indexes slightly improves when used in combination with precipitation data, but three weeks of features are required to obtain OA above 80%. The optical indices alone (Sentinel-2 and Landsat 8) reach OA ?85% in the first week of observation. However, they are ineffective in cloudy conditions or when rainfed and irrigated fields have similar vigour. The most effective and robust indices are those based on combined sources (radar, optical, and meteorological), allowing OAs of about 92% and 96% at the beginning and in the middle of the irrigation season, respectively. [ABSTRACT FROM AUTHOR]

Accurate, timely, and reliable precipitation observations are mandatory for hydrological forecast and early warning systems. In the case of convective precipitation, traditional rain gauge networks often miss precipitation maxima, due to density limitations and the high spatial variability of the rainfall field. Despite several limitations like attenuation or partial beam blocking, the use of C-band weather radar has become operational in most European weather services. Traditionally, weather-radar-based quantitative precipitation estimation (QPE) is derived from horizontal reflectivity data. Nevertheless, dual-polarization weather radar can overcome several shortcomings of the conventional horizontal-reflectivity-based estimation. As weather radar archives are growing, they are becoming increasingly important for climatological purposes in addition to operational use. For the first time, the present study analyses one of the longest datasets from fully operational polarimetric C-band weather radars; these are located in Estonia and Italy, in very different climate conditions and environments. The length of the datasets used in the study is 5 years for both Estonia and Italy. The study focuses on long-term observations of summertime precipitation and their quantitative estimations by polarimetric observations. From such derived QPEs, accumulations for 1 h, 24 h, and 1-month durations are calculated and compared with reference rain gauges to quantify uncertainties and evaluate performances. Overall, the radar products showed similar results in Estonia and Italy when compared to each other. The product where radar reflectivity and specific differential phase were combined based on a threshold exhibited the best agreement with gauge values in all accumulation periods. In both countries reflectivity-based rainfall QPE underestimated and specific differential-phase-based product overestimated gauge measurements. [ABSTRACT FROM AUTHOR]

A strong windthrow affected many forests in Slovenia and northern Italy on the night of the 29th and the 30th of October, 2018. In this paper, we propose a new methodology for windthrow identification, comprising two new indexes, PCA-CI for evaluating change detection and PCA-WI for the identification of windthrows by analysing the time series of C-SAR Sentinel-1 data. The proposed methodology, unlike the previous studies on the identification of windthrows, does not subtract the values of dual and single polarised VH-VV data combinations, but proposes a new approach with a multivariate transformation of dimensionality reduction of the time series of the dual and single polarised data in two different time frames. [ABSTRACT FROM AUTHOR]

In this paper, we study the impact of lightning and radar reflectivity factor data assimilation on the precipitation VSF (very short-term forecast, 3 h in this study) for two severe weather events that occurred in Italy. The first case refers to a moderate and localized rainfall over central Italy that occurred on 16 September 2017. The second case occurred on 9 and 10 September 2017 and was very intense and caused damages in several geographical areas, especially in Livorno (Tuscany) where nine people died. The first case study was missed by several operational forecasts, including that performed by the model used in this paper, while the Livorno case was partially predicted by operational models. We use the RAMS@ISAC model (Regional Atmospheric Modelling System at Institute for Atmospheric Sciences and Climate of the Italian National Research Council), whose 3D-Var extension to the assimilation of radar reflectivity factor is shown in this paper for the first time. Results for the two cases show that the assimilation of lightning and radar reflectivity factor, especially when used together, have a significant and positive impact on the precipitation forecast. For specific time intervals, the data assimilation is of practical importance for civil protection purposes because it changes a missed forecast of intense precipitation (≥40 mm in 3 h) to a correct one. While there is an improvement of the rainfall VSF thanks to the lightning and radar reflectivity factor data assimilation, its usefulness is partially reduced by the increase in false alarms, especially when both datasets are assimilated. [ABSTRACT FROM AUTHOR]

The combined acquisition of 3D ultrasonic tomography and radar scans is growing for cultural heritage diagnostics. Both methods proved to be efficient in the detection and location of fractures and weaknesses within the investigated artefacts. Although the two techniques are widely applied together, an integrated approach for data interpretation is still missing. We present the results of radar and ultrasonic prospections carried out on the statue of the young Ramses II, an absolute masterpiece of the Egyptian art preserved in the collection of the Museo Egizio of Torino (Italy). Geophysical results are incorporated within the 3D model of the statue retrieved from total station measurements, ground-based and handheld laser scanning. A data integration approach is then proposed for the joint interpretation of the geophysical results, exploiting the final ultrasonic velocity model and radar attribute analysis (i.e. local dissimilarity computation) to define a combined damage index. The proposed methodology is efficient in fracture detection and location and improves the readability of the final results also for non-expert geophysical interpreters, offering guidance to the museum for preservation and restoration of the masterpiece., (© 2022. The Author(s).)

MultiEXCELL, a new rainfall model oriented to the analysis of radio propagation impairments which was developed on the basis of a comprehensive rain field database collected by the weather radar sited in Spino d'Adda (Italy), is presented. Single rain cells are modeled by an analytical exponential profile which best represents real single-peaked rain structures. The rain cells' probability of occurrence is analytically derived from the local rainfall statistics. The spatial features of the rain field at mid- and large-scale are investigated through their natural aggregative process. The clusters (aggregates) of cells are studied in terms of distance between individual cells, number of cells per aggregate, and distance between aggregates. Finally, the fractional area covered by rain, which the rainfall spatial correlation strongly depends on, is derived from radar data through the comparison with the same quantity provided by global long-term numerical weather products. The MultiEXCELL procedure for the generation of spatially correlated synthetic rain fields is duly presented and the model's accurateness is preliminary assessed against the available radar dataset. Although MultiEXCELL is mainly oriented to propagation-related applications, its cellular approach may reveal useful also in hydrology, for the prediction/management of water resources, and in meteorology, for the nowcasting of the temporal evolution of rain structures. [ABSTRACT FROM AUTHOR]

Abstract. Flash flood events are floods characterised by a very rapid response of basins to storms, often resulting in loss of life and property damage. Due to the specific spacetime scale of this type of flood, the lead time available for triggering civil protection measures is typically short. Rainfall threshold values specify the amount of precipitation for a given duration that generates a critical discharge in a given river cross section. If the threshold values are exceeded, it can produce a critical situation in river sites exposed to alluvial risk. It is therefore possible to directly compare the observed or forecasted precipitation with critical reference values, without running online real-time forecasting systems. The focus of this study is the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated by minimising a utility function based on the informative entropy concept and by using a simulation approach based on radar data. The study concludes with a system performance analysis, in terms of correctly issued warnings, false alarms and missed alarms [ABSTRACT FROM AUTHOR]

Abstract: The problem of severe thunderstorm risk in the Lombardy region (Italy) is serious. In fact during the warm season many thunderstorms (TS) occur in high density populated area located between the river Po and the Alps. In the year 2003, about 90 TS caused damage to people, houses, cars, agriculture and electrical lines. About 30 municipalities undergo damage by tornadoes. The 2003 summer was not particularly anomalous with respect to others for TS activity. In this region storms are well detected by some C-band radars and the Meteosat satellites, but the study of the correlation between these variables and the TS severity needs the collection of many met-data at the ground. Unfortunately the lack of a fine mesh met-station network forces the use of local press news or subjective reports to identify the impact of TS. Since 2006 ERSE has been collaborating with the Lombardy Region – Civil Protection Service/Office – in developing and testing a system to detect and nowcast severe thunderstorms, STAF (Storm Track Alert and Forecast). STAF is a nowcasting tool based on Radar and MSG (Meteosat Second Generation) data that selects only severe TS, tracks them and produces alert messages to users. In order to evaluate the severity of a TS, a crucial issue for STAF is the correlation between variables detected by the remote-sensing instruments and the effects at the ground. The paper describes a method to classify the severity of a TS by computing an index named “probability of damage” (PD). The index has been carried out by means of a storm archive, where radar and satellite data are stored together with damages reports from newspapers, all collected in 2003 summer. The index has been verified during the 2009 summer, when STAF was applied in a field test involving a group of Civil Protection observers and users. The results of this test are reported in the paper. The test has been also an occasion for verifying the effectiveness of information provided by STAF to selected people locally responsible for public alert and rescue in the case of a severe weather event. [Copyright &y& Elsevier]

Piemonte region, in the north-western Italy, is characterized by complex orography and Mediterranean influence that often causes extreme rainfall event, during the warm season. Although the region is monitored by a dense gauge network (more than one gauge per 100 km²), the ground measurements are often inadequate to properly observe intense and highly variable precipitations. Polarimetric weather radars provide a unique way to monitor rainfall over wide areas, with the required spatial detail and temporal resolution. Nevertheless, most European weather radar networks are operating at C-band, which may seriously limit quantitative precipitation estimation in heavy rainfall due to relevant power signal attenuation. Phase measurements, unlike power measurements, are not affected by signal attenuation. For this reason, polarimetric radars, for which the differential phase shift measurements are available, provide an additional way in which to estimate precipitation, which is immune to signal attenuation. In this work differential phase based rainfall estimation techniques are applied to analyze two flash-floods: the first one occurred on the Ligurian Apennines on 16 August 2006 and the second occurred on 13 September 2008, causing rain accumulations above 270 mm in few hours. [ABSTRACT FROM AUTHOR]

The integration of high-resolution, non-invasive geophysical techniques (such as ground-penetrating radar or GPR) with emerging sensing techniques (acoustics, thermography) can complement limited destructive tests to provide a suitable methodology for a multi-scale assessment of the state of preservation, material and construction components of monuments. This paper presents the results of the application of GPR, infrared thermography (IRT) and ultrasonic tests to the 13th century rose window of Troia Cathedral (Apulia, Italy), affected by widespread decay and instability problems caused by the 1731 earthquake and reactivated by recent seismic activity. This integrated approach provided a wide amount of complementary information at different scales, ranging from the sub-centimetre size of the metallic joints between the various architectural elements, narrow fractures and thin mortar fillings, up to the sub-metre scale of the internal masonry structure of the circular ashlar curb linking the rose window to the façade, which was essential to understand the original building technique and to design an effective restoration strategy. [ABSTRACT FROM AUTHOR]

This paper aims to highlight the use of the georadar as a useful prospecting technique to identify the areal density and the geometrical features of the grottoes placed in a historical town characterised by high seismic hazard. The town considered here is Rionero in Vulture (Southern Italy) that was hit by several historical earthquakes, among which the 1930 Irpinia earthquake (Me=6.7, Is=VIII MCS). For this event a damage map was already available from a previous study (Gizzi and Masini, 2006). This map shows that some sectors of the town suffered higher damage. One factor causing the uneven distribution of the effects is considered to be the presence of grottoes. To strengthen this work hypothesis it was necessary to indepth investigate the subsoil of Rionero in Vulture. Therefore, geophysical data were correlated and integrated with data obtained from field surveys and historical documentary sources. All these investigations allowed to obtain more insights about the influences of the man-made caves on seismic damage. [ABSTRACT FROM AUTHOR]

Differential synthetic aperture radar interferometry (DInSAR) is a remote sensing technique that allows monitoring ground deformation with accuracy of the order of fractions of the radiated wavelength, by means of proper combination and processing of repeat-pass data. In contrast to the satellite case, application of such a technique to airborne data is not, today, a well-established task. Several airborne campaigns, involving mainly C/L-band data, have been planned in the last years to exploit the potentialities of these more flexible platforms for deformation monitoring. In this paper, we show the results of an airborne DInSAR X-band experiment carried out over the Perugia area (center of Italy) by using the OrbiSAR system. We discuss the processing chain applied to the acquired data, which allows achieving a satisfactory compromise between accuracy and efficiency. Eleven repeated passes were carried out in two days; two corner reflectors were located on the ground in a hilly region. One corner reflector was vertically moved between the two days to evaluate the system detection capability. Moreover, we carry out an analysis of all possible differential interferograms for a region 2 x 4 km wide. [ABSTRACT FROM AUTHOR]

Abstract: A Ground-Based SAR (GB-SAR) interferometer was employed to measure the surface displacements of a landslide occurring in the Carnian Alps, north-eastern Italy, which has affected a national road and seriously damaged a road tunnel still under construction. Moreover, since the landslide is located on the left bank of the Tagliamento River Valley, it is feared that this mass movement might dam the river, creating a basin that would increase natural hazard for the valley inhabitants. The data collected from December 2002 to July 2005 by a conventional monitoring system, consisting of a GPS network and boreholes equipped with inclinometric tubes, showed that the landslide was moving at a quasi-constant rate of about 3 cm per year. Due to the slow deformation rate of the landslide, a recently developed GB-SAR technique based on the analysis of a restricted ensemble of coherent points was used. Two surveys, each lasting two days, were planned in December 2004 and July 2005, in order to map and measure the surface displacements that occurred over time. The results from the radar were compared with the ones derived from the GPS monitoring network. An agreement was achieved among the data collected, showing the capability of the GB-SAR technique to measure displacements even within a time span of several months between the surveys. [Copyright &y& Elsevier]

A spatial characterization of the midlatitude meso-scale rain fields from C-band radar measurements is performed by means of a systematic analysis and modeling of convective rain-cell bidimensional shapes and spatial correlation. A large rainfall dataset that is derived from an operational C-band dual-polarized radar, which is placed in S. Pietro Capofiume near Bologna (Italy), has been collected and analyzed for this purpose. Different models of convective rainy horizontal structures are described and compared. Special attention is devoted to the consolidated unimodal models (or unimodal patterns) like GAUCELL with a Gaussian rain-rate profile and EXCELL with an exponential rain-rate profile, and the hybrid models like HYCELL and DEXCELL based on a proper combination of the previous unimodal models. The new hybrid model DEXELL, which is introduced here, is an extension of the HYCELL model, which is previously proposed in literature. A pixel-by-pixel model numerical integration is carried out in order to perform a homogeneous comparison between the rain-cell model and the measured features such as peak, average, root mean square, gradient average, and gradient deviation of rain rate. A maximum-likelihood algorithm, which is expressed in terms of the principal component of the previous rain-cell features, is introduced to estimate rain-cell pattern parameters from the available radar data. A detailed sensitivity analysis, which is devoted to find the best behavior in terms of root-mean-square error and correlation coefficient between the modeled and measured rain-cell features, is finally carried out. [ABSTRACT FROM AUTHOR]

Abstract: The applicability of the Permanent Scatterers Synthetic Aperture Radar Interferometry (PSInSAR) technique for detecting and monitoring ground displacements was tested in the Oltrepo Pavese territory (Northern Italy, southern Lombardia), which could be representative of similar geological contexts in the Italian Apennines. The study area, which extends for almost 1100 km2, is characterized by a complex geological and structural setting and the presence of clay-rich sedimentary formations. These characteristics make the Oltrepo Pavese particularly prone to several geological hazards: shallow and deep landslides, subsidence and swelling/shrinkage of the clayey soils. The PSInSAR technique used in this study overcomes most of the limitations of conventional interferometric approaches by identifying, within the area of interest, a set of “radar benchmarks” (PS), where very precise displacement measurements can be carried out. More than 90,000 PS were identified by processing Synthetic Aperture Radar (SAR) images acquired from 1992 to 2001 by the European Remote Sensing satellites (ERS). The PSInSAR application at a sub-regional scale detected slow ground deformations ranging from +5 to −16 mm/year, and resulting from various processes (landslides, swelling/shrinkage of clay soils and water pumping). The PS displacements were analysed by collecting data obtained through geological, geomorphologic field surveys, geotechnical analysis of the soils and the information was integrated within a landslide inventory and the damaged building inventory. Despite the limited number of landslide bodies with PS (7% of the inventoried landslides), the PS data helped to revise the state of activity of several landslides. Furthermore, some previously unknown unstable slopes were detected. Two areas of uplift and two areas of subsidence were identified. [Copyright &y& Elsevier]

Rain cells are structures which represent an important component of convective precipitation and a study of their properties represents a necessary step both towards improved stochastic models of small-scale precipitation and for the verification of deterministic high resolution local-area models. The case of intense convective precipitation in the tropics has been analysed in a recent study (von Hardenberg et al., 2003). Here we extend the analysis to mid-latitudes and we present results on the structure of convective rain cells observed by radar measurements in Italy. In particular we consider the average shape of precipitation cells and its dependence on radar resolution and the distributions of ellipticities. [ABSTRACT FROM AUTHOR]

An integrated geophysical survey using both the electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) methods was undertaken over a cave of great archaeological interest in southern Italy. The survey was performed to assess the stability of the carbonate rock roof of the cave. A geophysical survey was preferred to boreholes and geotechnical tests, in order to avoid the risk of mass movements. The interpretation of integrated data from ERT and GPR resulted in an evaluation of some of the electromagnetic (EM) characteristics (such as the EM wave velocity) and the detection of discontinuities (fractures) in the carbonate rock. It is well known that rock fractures constitute a serious problem in cave maintenance, and progressive cracking within the bed rock is considered to be one of the main causes of collapse. An analysis of the back-scattered energy was also required for the GPR data interpretation. Cracks within the bedrock were detected to a depth of about 2m by using GPR, which allowed for the identification of the loosened zone around the cave. [ABSTRACT FROM AUTHOR]

Heavy and localized summer events are very hard to predict and, at the same time, potentially dangerous for people and properties. This paper focuses on an event occurred on 15 July 2020 in Palermo, the largest city of Sicily, causing about 120 mm of rainfall in 3 h. The aim is to investigate the event predictability and a potential way to improve the precipitation forecast. To reach this aim, lightning (LDA) and radar reflectivity data assimilation (RDA) was applied. LDA was able to trigger deep convection over Palermo, with high precision, whereas the RDA had a key role in the prediction of the amount of rainfall. The simultaneous assimilation of both data sources gave the best results. An alert for a moderate–intense forecast could have been issued one hour and a half before the storm developed over the city, even if predicting only half of the total rainfall. A satisfactory prediction of the amount of rainfall could have been issued at 14:30 UTC, when precipitation was already affecting the city. Although the study is centered on a single event, it highlights the need for rapidly updated forecast cycles with data assimilation at the local scale, for a better prediction of similar events. [ABSTRACT FROM AUTHOR]

Hydrological monitoring systems relying on radar data and distributed hydrological models are now feasible at large-scale and represent effective early warning systems for flash floods. Here we describe a system that allows hydrological occurrences in terms of streamflow at a national scale to be monitored. We then evaluate its operational application in Italy, a country characterized by various climatic conditions and topographic features. The proposed system exploits a modified conditional merging (MCM) algorithm to generate rainfall estimates by blending data from national radar and rain-gauge networks. Then, we use the merged rainfall fields as input for the distributed and continuous hydrological model, Continuum, to obtain real-time streamflow predictions. We assess its performance in terms of rainfall estimates from MCM, using cross-validation and comparison with a conditional merging technique at an event-scale. We also assess its performance against rainfall fields from ground-based data at catchment-scale. We further evaluate the performance of the hydrological system in terms of streamflow against observed data (relative error on high flows less than 25% and Nash–Sutcliffe Efficiency greater than 0.5 for 72% and 46% of the calibrated study sections, respectively). These results, therefore, confirm the suitability of such an approach, even at national scale, over a wide range of catchment types, climates, and hydrometeorological regimes, and for operational purposes. [ABSTRACT FROM AUTHOR]

Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, "Runway n.3" of the "Leonardo Da Vinci International Airport" in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data-interpolated through Ordinary Kriging-and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient ( r = 0.94), the multiple R-squared coefficient ( R 2 = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs).

Different weather conditions are known to affect bird migration, yet the influence of fog and low clouds on migrating birds has been rarely examined so far, and hence, their impact on bird movement is not well understood. Fog avoidance could be a consequence of visual limitations within the fog or may be the outcome of deteriorated soaring conditions due to the obstruction of the sun. We carried out a radar study at the Strait of Messina, which is a bottleneck for migrating birds traversing the Central Mediterranean Sea, to determine if the intensity of diurnal soaring bird migration was influenced by fog and other weather variables. We recorded bird movements using an X-band radar, which can detect birds flying within the fog, and recorded weather conditions using local meteorological observations. We examined if bird passage rate (number of tracks/hour) at the radar site was influenced by fog, wind speed and direction, air temperature and the time of day. Our findings suggest that fog was the most important factor affecting bird migration intensity as recorded by the radar, indicating that birds actively avoided flying into fog. In addition, wind direction affected bird migration intensity, with lower numbers recorded with southerly tailwinds and higher numbers recorded with westerly crosswinds. Our findings highlight a consequence of widespread meteorological conditions, and of fog in particular, on migrating birds, with implications for bird migration navigation, path length and flight energetics.

Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) is an efficient technique for capturing short, subtle episodes of conduit pressurization in open vent volcanoes like Stromboli (Italy), because it can detect very shallow magma storage, which is difficult to identify using other methods. This technique allows the user to choose the optimal radar location for measuring the most significant deformation signal, provides an exceptional geometrical resolution, and allows for continuous monitoring of the deformation. Here, we present and model ground displacements collected at Stromboli by GBInSAR from January 2010 to August 2014. During this period, the volcano experienced several episodes of intense volcanic activity, culminated in the effusive flank eruption of August 2014. Modelling of the deformation allowed us to estimate a source depth of 482 ± 46 m a.s.l. The cumulative volume change was 4.7 ± 2.6 × 105 m3. The strain energy of the source was evaluated 3-5 times higher than the surface energy needed to open the 6-7 August eruptive fissure. The analysis proposed here can help forecast shifts in the eruptive style and especially the onset of flank eruptions at Stromboli and at similar volcanic systems (e.g. Etna, Piton de La Fournaise, Kilauea). [ABSTRACT FROM AUTHOR]

Acoustic remote sensing of the oceans requires a detailed understanding of the acoustic forward problem. The results of a shallow-water transmission experiment between a vertical array of sources and a vertical array of receivers are reported. The source array is used to provide additional degrees of freedom to isolate and track raylike arrivals by beamforming over both source and receiver arrays. The coordinated source-receiver array processing procedure is presented and its effectiveness in an example of tracking raylike arrivals in a fluctuating ocean environment is shown. Many of these arrivals can be tracked over an hour or more and show slowly varying amplitude and phase. The use of a double-beamforming algorithm lays the foundation for shallow-water acoustic remote sensing using travel time and source and receive angles of selected eigenrays.