Nowadays the use of remote monitoring sensors is a standard practice in landslide characterization and monitoring. In the last decades, technologies such as LiDAR, terrestrial and satellite SAR interferometry (InSAR) and photogrammetry demonstrated a great potential for rock slope assessment while limited studies and applications are still available for ArcSAR Interferometry, Gigapixel imaging and Acoustic sensing. Taking advantage of the facilities located at the Poggio Baldi Landslide Natural Laboratory, an intensive monitoring campaign was carried out on May 2019 using simultaneously the HYDRA-G ArcSAR for radar monitoring, the Gigapan robotic system equipped with a DSLR camera for photo-monitoring purposes and the DUO Smart Noise Monitor for acoustic measurements. The aim of this study was to evaluate the potential of each monitoring sensor and to investigate the ongoing gravitational processes at the Poggio Baldi landslide. Analysis of multi-temporal Gigapixel-images revealed the occurrence of 84 failures of various sizes between 14–17 May 2019. This allowed us to understand the short-term evolution of the rock cliff that is characterized by several impulsive rockfall events and continuous debris production. Radar displacement maps revealed a constant movement of the debris talus at the toe of the main rock scarp, while acoustic records proved the capability of this technique to identify rockfall events as well as their spectral content in a narrow range of frequencies between 200 Hz to 1000 Hz. This work demonstrates the great potential of the combined use of a variety of remote sensors to achieve high spatial and temporal resolution data in the field of landslide characterization and monitoring.

<p>Rockfalls could be catastrophic for their inherent characteristics such as limited precursor deformation, unforeseeable movement, and extreme velocity. Potential damages in a rockfall event are mostly associated with blocks reaching vulnerable elements during their descent down the slope. The block volumes involved in a rockfall as well as detachment locations, trajectories and velocity along a slope are the parameters that directly determine the intensity of a rockfall hazard. Therefore, there is a dire need to develop effective evaluation strategies for rockfall phenomena through efficient monitoring and analysis techniques. Recent years have witnessed significant developments in the monitoring, analytical and physical methods for the study of rockfall phenomena. Improvements in the use of laser scanning, and drone photogrammetry have allowed to exploit high-resolution virtual outcrop models (VOMs) and derive accurate information about slope evolution. Rock falls are strictly related to fracture patterns pervading the rock mass. Hence, kinematic analyses can quantify the susceptibility to failure of a rock block. Moreover, discontinuity extraction represents the key data to investigate the spatial distribution of fractures and consequently to determine the potential rock block volumes. The trajectories of the rock fragments depend on the slope geometry and the characteristics of the propagation zone, local asperities, and the mechanical attributes of the exposed bedrock and soil cover.</p><p>The present study concerns the evaluation of rockfall activity, susceptibility, and hazard modelling of the Poggio Baldi landslide (Central Italy). The Poggio Baldi landslide is affected by frequent rockfalls, and it is being monitored for several years with multiple remote sensing instruments. It is home to a permanent natural monitoring laboratory managed by the Department of Earth Sciences of the Sapienza University of Rome and NHAZCA SRL. Over the years, many surveys and investigations have been carried out using modern remote sensing techniques to capture active gravitational processes.</p><p>Here, we introduce a new approach combining 3D and 2D VOM to assess rockfall activity and the associated hazard. Most active rockfall source sectors were found using 3D change detection on multitemporal VOMs, thus suggesting the state of activity of the rock scarp. In these sectors, we thoroughly surveyed the discontinuity sets and their patterns, such as spacing and persistence by integrating data from UAV-based photogrammetric point clouds and orthoimages. These data were then used to calculate the volume of the typical rock blocks characterizing each area. Moreover, we implemented a GIS-based modified kinematic method to assess the failure susceptibility of the rock scarp using slope morphometry and discontinuity orientations. Finally, to simulate the potential runout of falling blocks from the most active and susceptible areas of the slope, rockfall trajectory simulations were performed on a physical characteristics-based GIS model. The results of kinematic susceptibility and rockfall runout were then statistically assessed by comparing them with real depletion and accumulation areas derived by the multitemporal VOMs with a time span of 3 years. Through this approach, it was possible to perform detailed rockfall hazard simulations for each source area using specific structural/geomechanical data.</p>

<p>In the last decades, technologies such as LiDAR, terrestrial and satellite SAR interferometry (InSAR) and photogrammetry demonstrated a great potential for rock slope assessment. However, studies and applications are still limited for ArcSAR Interferometry, Gigapixel imaging, Acoustic sensing and PhotoMonitoring. With an aim to explore deeper potentials of all above mentioned techniques in monitoring rockfalls and the related debris talus, a permanent natural monitoring site was founded in Poggio Baldi landslide (Central Italy) with various remote monitoring instruments. In detail, the annual volume lost from the cliff is about 3x103 m3 due to frequent rockfalls (up to 84 in three days). Officially inaugurated in October 2021, the permanent Natural Laboratory of Poggio Baldi is completely energy independent and remotely controlled, thus allowing a continuous and efficient monitoring of the rock slope. It is equipped with optical tools (multi resolution cameras), 3D modelling tools (LiDAR and drone photogrammetry), radar tools (linear and arc GB-InSAR, and doppler radar), acoustic tools, seismic tools (sound level meter and geophone) and a weather station. Thanks to the Department of Earth Sciences of the Sapienza University of Rome and NHAZCA SRL for the foundation, contribution, and continuous management of the site. The Poggio Baldi natural laboratory is now continuously monitoring the mass movement activities in a failed slope in Poggio Baldi. The goal is to understand the relationship between rockfalls, predisposing and triggering factors such as thermal, seismic, and meteorological stress that can provide critical information for setting up early warning systems. The acquired data are frequently analysed to assess and improve the prevailing facilities. Additionally, various tools, techniques and methodologies are being developed and implemented at the site to further enhance the capabilities of the monitoring activity. The laboratory is open to host third-party companies and research agencies for testing experimental instruments related to rock and slope deformation and associated risks.</p>

The study presents results from applying the Real Aperture Radar interferometry technique and Digital Image Correlation through a mobile phone camera to identify static and dynamic deformations of a gantry during surveying operations on the Michelangelo’s David at the Galleria dell’Accademia di Firenze Museum in Florence. The statue has considerable size and reaches an elevation of more than seven meters on its pedestal. An ad-hoc gantry was designed and deployed, given the cramped operating area around the statue. The scanner had a stability control system that forbid surveying in instrument movements. However, considering the unicity of the survey and its rare occurrence, the previous survey had been carried out in the year 2000; verifying stability and recording deformations is a crucial task, and necessary for validation. As the gantry does not have an on-board stability sensor, and considering the hi-survey accuracy requested, a redundant, contactless, remote monitoring system of the gantry and the statue stability was chosen to guarantee the maximum freedom of movement around the David to avoid any interference during scanning operations. Thanks to the TInRAR technique, the gantry and the statue were monitored with an accuracy of 0.01 mm. At the same time, a Digital Image Correlation analysis was performed on the gantry, which can be considered a Multi-Degree-Of-Freedom (MDOF) system, to accurately calculate the vibration frequency and amplitude. A comparison between TInRAR and DIC results reported substantial accordance in detecting gantry’s oscillating frequencies; a predominant oscillation frequency of 1.33 Hz was identified on the gantry structure by TinSAR and DIC analysis.

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.