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.

This study explores the innovative use of digital image processing (DIP) techniques, also named PhotoMonitoring, for analysing the triggering conditions of shallow landslides. The approach, based on the combination of optical and infrared thermographic imaging (IRT), was applied to a laboratory-scale slope, reproduced in a flume test apparatus. Three experiments were conducted to replicate rainfall-induced shallow landslides, applying change detection and digital image correlation analysis to both optical and thermal images. The method combines IRT’s ability to measure ground surface temperature changes with DIP’s capacity to track movement and displacement. Results showed the high reliability of the displacement time-series obtained through IRT-DIP with respect to the reference optical-DIP. The IRT-DIP technique also detects anomaly signals two minutes before landslide occurrence that can be regarded as a possible failure precursor. This study testifies to the potential of image analysis as a remote sensing technique, demonstrating the ability of DIP to capture the dynamics of shallow landslides, as well as the advantages of optical–IRT combinations to follow slope deformation processes during night-time. This approach, if properly adapted to real-scale scenarios, may contribute to a better understanding of landslide behaviour, improve landslide monitoring strategies, and promote more effective early warning systems (EWS).

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.

Landslides pose significant threats to human lives and infrastructure, making accurate monitoring essential for understanding and preventing these events. Photomonitoring, utilizing optical/multispectral sensors and digital image processing techniques, has emerged as a valuable tool for studying and monitoring landslide deformation processes. This article explores the application of photomonitoring in landslide studies, presenting three diverse case studies showcasing its efficacy and versatility. The technique allows for continuous, automated, and real-time monitoring of landslide events, providing valuable insights into displacement patterns and deformation trends. To enhance its usability, the software IRIS was developed to analyze data acquired from various platforms and sensors. This innovative solution promises to improve landslide management, contributing to better comprehension, prevention, and mitigation strategies, ultimately ensuring the safety of communities and infrastructure in landslide-prone regions.

Earth flows are complex geological processes that, when interacting with linear infrastructures, have the potential to cause significant damage. Consequently, conducting comprehensive investigations and continuous monitoring are becoming paramount in designing effective mitigation measures and ensuring sustainable risk management practices. The use of digital image correlation (DIC) algorithms for the displacement monitoring of earth flows is a relatively new and growing field with a limited number of dedicated works in the literature. Within this framework, the present paper contributes by evaluating DIC techniques at several earth flow sites. These assessments were founded upon data obtained from both low-cost and multi-platform sensors, used to assess the displacement field, pinpointing the most active sectors, and gauging their rates of movement during different kinematic phases. In this regard, the highest localized movement velocities reached in the Pietrafitta (0.01 m/day) and Grillo (0.63 m/day) earth flows experience different ongoing kinematic processes. The versatility of these techniques is notable, manifesting in the ease of installation, cost-effectiveness, and adaptability to various platforms. The proven reliability in terms of maximum accuracy (1 pixel) and sensitivity (0.05 m) lays the foundation for the extensive use of the presented techniques. The amalgamation of these attributes positions DIC techniques as competitive, adaptable, and readily deployable tools in earth flow studies.