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Italy is famous for its one-of-a-kind landscapes and the many cultural heritage sites characterizing the story of its regions. In central Italy, during the medieval age, some of them were built on the top of high and steep cliffs, often on the top of ancient ruins, to protect urban agglomerations, goods and people. The geographical locations of these centers allowed them to maintain their original conformation over time, but, at the same time, exposed them to a high risk of landslides. In this context, this research aimed to present an integrated and low-cost approach to study the potential landslide phenomena affecting two medieval towns. Field surveys and mapping were carried out through the use of innovative digital mapping tools to create a digital database directly on the field. Data gathered during field surveys were integrated with GIS analyses for an improved interpretation of the geological and geomorphological features. Due to the inaccessibility of the cliffs surrounding the two villages, a more detailed analysis of these areas was performed through the use of unmanned aerial vehicle-based photogrammetry, while advanced differential synthetic aperture radar interferometry (A-DInSAR) interpretation was undertaken to verify the stability of the buildings in proximity to the cliffs and other potential active failures. The results of the study highlighted the similar geometry and structural settings of the two areas. Kinematically, the intersection of three main joint sets tends to detach blocks (sometimes in high volumes) from the cliffs. The A-DInSAR analysis demonstrated the presence of a landslide failure along the northwest side of the Monte San Martino town. The buildings in proximity to the cliffs did not show evidence of movements. More generally, this research gives insights into the pro and cons of different survey and analysis approaches and into the benefits of their procedural integration in space and in time. Overall, the procedure developed here may be applied in similar contexts in order to understand the structural features driving slopes' instabilities and create digital databases of geological/monitoring data. [ABSTRACT FROM AUTHOR]

Low-frequency aperture arrays represent sensitive instruments to detect signals from radio astronomic sources situated in the universe. In Italy, the Sardinia Aperture Array Demonstrator (SAAD) consists of an ongoing project of the Italian National Institute for Astrophysics (INAF) aimed to install an aperture array constituted of 128 dual-polarized Vivaldi antennas at the Sardinia Radio Telescope (SRT) site. The originally envisaged 128 elements of SAAD were re-scoped to the 16 elements of its precursor named SADino, with the aim to quickly test the system with a digital beam-former based on the Italian Tile Processing Module (iTPM) digital back-end. A preliminary measurements campaign of radio frequency interference (RFI) was performed to survey the less contaminated spectral region. The results of these measurements permitted the establishment of the technical requirements for receiving a chain for the SADino telescope. In this paper, the design, implementation, and characterization of this signal acquisition chain are proposed. The operative frequency window of SAAD and its precursor, SADino, sweeps from 260 MHz to 420 MHz, which appears very attractive for radio astronomy applications and radar observation in space and surveillance awareness (SSA) activities. [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 work, we present a new method based on the compressive sensing (CS) theory to correct phase unwrapping (PhU) errors in the multitemporal sequence of interferograms exploited by advanced differential interferometric synthetic aperture radar (DInSAR) techniques to generate deformation time series. The developed algorithm estimates the PhU errors by using a modified $L_{1}$ -norm estimator applied to the interferometric network built in the temporal/spatial baseline plane. Indeed, in order to search the minimum $L_{1}$ -norm sparse solution, we apply the iterative reweighted least-squares method with an improved weight function that takes account of the baseline characteristics of the interferometric pairs. Moreover, we also introduce a quality function to identify those solutions that have no physical meaning. Although the proposed approach can be applied to different multitemporal DInSAR approaches, our analysis is tailored to the full-resolution small baseline subset (SBAS) processing chain that we properly modify to implement the proposed CS-based algorithm. To assess the performance of the developed technique, we carry out an extended experimental analysis based on simulated and real SAR data. In particular, we process two wide SAR datasets acquired by Sentinel-1 and COSMO-SkyMed constellations over central Italy between 2011 and 2019. The achieved experimental results clearly demonstrate the effectiveness of the developed approach in retrieving PhU errors and generating displacement time series related to strongly nonlinear deformation phenomena. Indeed, the developed CS-based technique significantly increases the number of detected coherent points and improves the accuracy of the retrieved deformation time series. [ABSTRACT FROM AUTHOR]

Rising magma, dike intrusions, and flank collapse are observed at many volcanoes worldwide, but how they interact is still poorly documented. Extensive synthetic aperture radar interferometry and continuous global positioning system observations captured a sharp dike intrusion at Mount Etna, Italy, during the 2018 paroxysm that triggered a vigorous seaward sliding of the eastern flank connected with brittle failure and deep magmatic resourcing. We propose a feedback process between flank acceleration and magma intrusion that derives from the interaction between the long- and short-term deformation of the volcano. The flank sliding acts as a valve that modulates the emplacement and eruption of magma within the shallow system. Rapid flank acceleration could potentially evolve into sudden collapses and seismic release at shallow depth. In turn, flank slip events could act as a sentinel for changes in magma depth and paroxysmal eruptions at Mount Etna. [ABSTRACT FROM AUTHOR]

Although Deep-Seated Gravitational Slope Deformations are well-known in the literature, their evolution and kinematics are still poorly understood. Their behavior is often complex and characterized by small movements associated with steady-state creep, alternating with periods of stasis, or accelerating downslope movements that, in some cases, could result in sudden and catastrophic failure events. Therefore, a multidisciplinary approach is often required. In this work, we shed light on the complex geometry and kinematics of the Pisciotta DSGSD, a deep-seated roto-translational sliding involving structurally complex turbiditic rock mass and interacting with man-made infrastructures. To reveal the geometrical features and the spatial and temporal behavior of the analyzed phenomenon, a multidisciplinary investigation was performed. Typical DSGSD landforms were mapped employing in-situ surveys, aided by stereoscopic analysis of historical aerial images and high-resolution drone-based mapping. Structural data and ancillary ground-based surveys revealed the presence of a highly weathered and folded turbiditic sequence, with competent sandstone and calcarenite units alternated by tectonically disrupted, weak argillite and mudrock layers. Remote sensing measurements from optical imagery and Synthetic Aperture Radar satellite data assessed the DSGSD's past and current kinematics, allowing to distinguish a pre-failure period with accelerating displacement rates, a failure period with maximum displacement rates, and a current post-failure period with decelerating displacement rates. Analytical modeling established the deep reach (up to 85 m) of the studied DSGSD as it allowed the estimation of its bottom surface and volume, as verified by available boreholes and inclinometric measurements. Furthermore, numerical modeling outcomes highlighted how the progressive weakening and alteration of the DSGSD material, in conjunction with changes in groundwater dynamics, serve as the primary mechanisms driving the observed kinematics. The models also revealed the intricate interaction between the DSGSD and the neighboring infrastructures. • Kinematic analysis of the Pisciotta Deep-Seated Gravitational Slope Deformation. • Airborne and satellite optical data identified its long-term displacements. • The interferometric analysis provided insights into its current short-term behavior. • Ground-based surveys validated the observations from remote-sensing data. • Analytical and numerical models unveiled its complex geometry and kinematics. [ABSTRACT FROM AUTHOR]

A MIMO GB-SAR system called MELISSA was put in place to monitor landslides in Italy and the sinking of the Costa Concordia cruise liner in France. It comprises 12 pyramidal horn antennas placed in a linear geometry for transmission, and these are used in the detection of the motion of a target (for example a landslide or other terrestrial deformation). The low half power beam width (19.76° at θ = 90°) of the transmitting radiation pattern of MELISSA results in low coverage area of the target. This paper proposes two alternative types of horn antenna for the current transmitter module of MELISSA, namely the cantenna and coaxial cavity horn antenna, for installation in a 2×6 planar antenna array. A higher value of the 3 dB beamwidth is observed using these arrays (38.320 at θ = 90° and 104.80 at φ = 0° for the cantenna array and 410 at θ = 90° and 140.40 at φ = 0° for the coaxial cavity horn antenna array). The overall gain of the proposed systems is around 10 dBi, and the efficiencies are between 85% and 90%. Using the Dolph Chebyshev beamforming technique on the proposed antenna arrays yields a zero sidelobe level, which improves the overall peak sidelobe ratio of the system and in turn the quality of the images obtained. Our proposed design for the transmitting section of the MELISSA system has applications terrestrial deformation monitoring with higher area coverage. [ABSTRACT FROM AUTHOR]

Persistent scatterers interferometry (PSI) based on the analysis of satellite synthetic aperture radar (SAR) data in the field of landslide mapping is becoming a widespread tool, commonly used together with traditional geomorphological survey techniques and other monitoring instruments. Having acquired permanent scatterers interferometry SAR (PSInSAR™) data since 2005, the Region of Liguria has in recent years carried out several operational tests to define the correct procedures to provide appropriate interpretations of PSI data sets with respect to landslide mapping and state of activity definition. These experiences have resulted in the elaboration of a semi-automatic procedure using spatial analysis tools provided by any commercial geographic information system (GIS) software to allow a quick overview of huge data and obtain indications of potentially unstable areas. An analysis of the results shows a good general congruity between the potentially unstable areas detected and landslide inventory maps, but also some anomalies. [ABSTRACT FROM AUTHOR]

This paper describes the high precision digital sun sensor under development at the University of Naples. The sensor determines the sun line orientation in the sensor frame from the measurement of the sun position on the focal plane. It exploits CMOS technology and an original optical head design with multiple apertures. This allows simultaneous multiple acquisitions of the sun as spots on the focal plane. The sensor can be operated either with a fixed or a variable number of sun spots, depending on the required field of view and sun-line measurement precision. Multiple acquisitions are averaged by using techniques which minimize the computational load to extract the sun line orientation with high precision. Accuracy and computational efficiency are also improved thanks to an original design of the calibration function relying on neural networks. Extensive test campaigns are carried out using a laboratory test facility reproducing sun spectrum, apparent size and distance, and variable illumination directions. Test results validate the sensor concept, confirming the precision improvement achievable with multiple apertures, and sensor operation with a variable number of sun spots. Specifically, the sensor provides accuracy and precision in the order of 1 arcmin and 1 arcsec, respectively. [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]

The lack of availability of historical and reliable river water level information is an issue that can be overcome through the exploitation of modern satellite remote sensing systems. This research has the objective of contributing in solving the information-gap problem of river flow monitoring through a synthetic aperture radar (SAR) signal processing technique that has the capability to perform water flow elevation estimation. This paper proposes the application of a new method for the design of a robust procedure to track over the time double-bounce reflections from bridges crossing rivers to measure the gap space existing between the river surface and bridges. Specifically, the difference in position between the single and double bounce is suitably measured over the time. Simulated and satellite temporal series of SAR data from COSMO-SkyMed data are compared to the ground measurements recorded for three gauges sites over the Po and Tiber Rivers, Italy. The obtained performance indices confirm the effectiveness of the method in the estimation of water level also in narrow or ungauged rivers. [ABSTRACT FROM AUTHOR]

This work presents the development of an efficient tool for managing, visualizing, analysing, and integrating with other data sources, the deformation time-series obtained by applying the advanced differential interferometric synthetic aperture radar (DInSAR) techniques. To implement such a tool we extend the functionalities of GeoNode, which is a web-based platform providing an open source framework based on the Open Geospatial Consortium (OGC) standards, that allows development of Geospatial Information Systems (GIS) and Spatial Data Infrastructures (SDI). In particular, our efforts have been dedicated to enable the GeoNode platform to effectively analyze and visualize the spatio/temporal characteristics of the DInSAR deformation time-series and their related products. Moreover, the implemented multi-thread based new functionalities allow us to efficiently upload and update large data volumes of the available DInSAR results into a dedicated geodatabase. The examples we present, based on Sentinel-1 DInSAR results relevant to Italy, demonstrate the effectiveness of the extended version of the GeoNode platform. [ABSTRACT FROM AUTHOR]