Digital image correlation (DIC) analysis of the 3 December 2013 Montescaglioso landslide (Basilicata, Southern Italy). Results from a multi-dataset investigation

Image correlation remote sensing monitoring techniques are becoming key tools for providing effective qualitative and quantitative information suitable for natural hazard assessments, specifically for landslide investigation and monitoring. In recent years, these techniques have been successfully integrated and shown to be complementary and competitive with more standard remote sensing techniques, such as satellite or terrestrial Synthetic Aperture Radar interferometry. The objective of this article is to apply the proposed in-depth calibration and validation analysis, referred to as the Digital Image Correlation technique, to measure landslide displacement. The availability of a multi-dataset for the 3 December 2013 Montescaglioso landslide, characterized by different types of imagery, such as LANDSAT 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor), high-resolution airborne optical orthophotos, Digital Terrain Models and COSMO-SkyMed Synthetic Aperture Radar, allows for the retrieval of the actual landslide displacement field at values ranging from a few meters (2–3 m in the north-eastern sector of the landslide) to 20–21 m (local peaks on the central body of the landslide). Furthermore, comprehensive sensitivity analyses and statistics-based processing approaches are used to identify the role of the background noise that affects the whole dataset. This noise has a directly proportional relationship to the different geometric and temporal resolutions of the processed imagery. Moreover, the accuracy of the environmental-instrumental background noise evaluation allowed the actual displacement measurements to be correctly calibrated and validated, thereby leading to a better definition of the threshold values of the maximum Digital Image Correlation sub-pixel accuracy and reliability (ranging from 1/10 to 8/10 pixel) for each processed dataset

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

Development of Landslide Warning System

Landslides cause approximately 25 to 50 deaths and US$1 - 2 billion worth of damage in the United States annually. They can be triggered by humans or by nature. It has been widely recognized that rainfall is one of the major causes of slope instability and failure. Slope remediation and stabilization efforts can be costly. An early warning system is a suitable alternative and can save human lives. In this project, an early warning system was developed for a 40-foot-high cut slope on the island of Hawaii. To achieve the objective, subsurface investigations were performed and undisturbed samples were collected. For the purpose of unsaturated soil testing, new testing apparatuses were developed by modifying the conventional oedometer and direct shear cells. The unsaturated soil was characterized using two separate approaches and, later, the results were discussed and compared. The slope site was instrumented for the measurement of suction, water content, displacement, and precipitation. The collected climatic data along with the calibrated hydraulic parameters were used to build an infiltration-evapotranspiration numerical model. The model estimations were compared with the field measurements and showed good agreement. The verified model was used to determine the pore-water pressure distribution during and after a 500-years return storm. Later, the pore-water pressure distribution was transferred to a slope stability software and used to study the slope stability during and after the storm. Based on a 2D slope stability analysis, the slope can survive the 500-year storm with a factor of safety of 1.20. Instrument threshold values were established for water content sensors and tensiometers using a traffic-light-based trigger criterion

Post-failure evolution analysis of a rainfall-triggered landslide by multi-temporal interferometry SAR approaches integrated with geotechnical analysis

Persistent Scatterers Interferometry (PSI) represents one of the most powerful techniques for Earth's surface deformation processes' monitoring, especially for long-term evolution phenomena. In this work, a dataset of 34 TerraSAR-X StripMap images (October 2013–October 2014) has been processed by two PSI techniques - Coherent Pixel Technique-Temporal Sublook Coherence (CPT-TSC) and Small Baseline Subset (SBAS) - in order to study the evolution of a slow-moving landslide which occurred on February 23, 2012 in the Papanice hamlet (Crotone municipality, southern Italy) and induced by a significant rainfall event (185 mm in three days). The mass movement caused structural damage (buildings' collapse), and destruction of utility lines (gas, water and electricity) and roads. The results showed analogous displacement rates (30–40 mm/yr along the Line of Sight – LOS-of the satellite) with respect to the pre-failure phase (2008–2010) analyzed in previous works. Both approaches allowed detect the landslide-affected area, however the higher density of targets identified by means of CPT-TSC enabled to analyze in detail the slope behavior in order to design possible mitigation interventions. For this aim, a slope stability analysis has been carried out, considering the comparison between groundwater oscillations and time-series of displacement. Hence, the crucial role of the interaction between rainfall and groundwater level has been inferred for the landslide triggering. In conclusion, we showed that the integration of geotechnical and remote sensing approaches can be seen as the best practice to support stakeholders to design remedial works.Peer ReviewedPostprint (author's final draft

Co-detection of acoustic emissions during failure of heterogeneous media: new perspectives for natural hazard early warning

A promising method for real time early warning of gravity driven rupture that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. The method capitalizes on co-detection of elastic waves emanating from micro-cracks by multiple and spatially separated sensors. Event co-detection is considered as surrogate for large event size with more frequent co-detected events marking imminence of catastrophic failure. Using a spatially explicit fiber bundle numerical model with spatially correlated mechanical strength and two load redistribution rules, we constructed a range of mechanical failure scenarios and associated failure events (mapped into AE) in space and time. Analysis considering hypothetical arrays of sensors and consideration of signal attenuation demonstrate the potential of the co-detection principles even for insensitive sensors to provide early warning for imminent global failure

Geophysical-geotechnical sensor networks for landslide monitoring

Landslides are often the result of complex, multi-phase processes where gradual deterioration of shear strength within the sub-surface precedes the appearance of surface features and slope failure. Moisture content increases and the build-up of associated pore water pressures are invariably associated with a loss of strength, and thus are a precursor to failure. Consequently, hydraulic processes typically play a major role in the development of landslides. Geoelectrical techniques, such as resistivity and self-potential are being increasingly applied to study landslide structure and the hydraulics of landslide processes. The great strengths of these techniques are that they provide spatial or volumetric information at the site scale, which, when calibrated with appropriate geotechnical and hydrogeological data, can be used to characterise lithological variability and monitor hydraulic changes in the subsurface. In this study we describe the development of an automated time-lapse electrical resistivity tomography (ALERT) and geotechnical monitoring system on an active inland landslide near Malton, North Yorkshire, UK. The overarching objective of the research is to develop a 4D landslide monitoring system that can characterise the subsurface structure of the landslide, and reveal the hydraulic precursors to movement. The site is a particularly import research facility as it is representative of many lowland UK situations in which weak mudrocks have failed on valley sides. Significant research efforts have already been expended at the site, and a number of baseline data sets have been collected, including ground and airborne LIDAR, geomorphologic and geological maps, and geophysical models. The monitoring network comprises an ALERT monitoring station connected to a 3D monitoring electrode array installed across an area of 5,500 m2, extending from above the back scarp to beyond the toe of the landslide. The ALERT instrument uses wireless telemetry (in this case GPRS) to communicate with an office based server, which runs control software and a database management system. The control software is used to schedule data acquisition, whilst the database management system stores, processes and inverts the remotely streamed ERT data. Once installed and configured, the system operates autonomously without manual intervention. Modifications to the ALERT system at this site have included the addition of environmental and geotechnical sensors to monitor rainfall, ground movement, ground and air temperature, and pore pressure changes within the landslide. The system is housed in a weatherproof enclosure and is powered by batteries charged by a wind turbine & solar panels. 3D ERT images generated from the landslide have been calibrated against resistivity information derived from laboratory testing of borehole core recovered from the landslide. The calibrated images revealed key aspects of the 3D landslide structure, including the lateral extent of slipped material and zones of depletion and accumulation; the surface of separation and the thickness of individual earth flow lobes; and the dipping in situ geological boundary between the bedrock formations. Time-lapse analysis of resistivity signatures has revealed artefacts within the images that are diagnostic of electrode movement. Analytical models have been developed to simulate the observed artefacts, from which predictions of electrode movement have been derived. This information has been used to correct the ERT data sets, and has provided a means of using ERT to monitor landslide movement across the entire ALERT imaging area. Initial assessment of seasonal changes in the resistivity signature has indicated that the system is sensitive to moisture content changes in the body of the landslide, thereby providing a basis for further development of the system with the aim of monitoring hydraulic precursors to failure

Quantification of landslide velocity from active waveguide generated acoustic emission

Acoustic emission (AE) has become an established approach to monitor stability of soil slopes. However, the challenge has been to develop strategies to interpret and quantify deformation behaviour from the measured AE. AE monitoring of soil slopes commonly utilises an active waveguide which is installed in a borehole through the slope and comprises a metal waveguide rod or tube with a granular backfill surround. When the host slope deforms, the column of granular backfill also deforms and this generates AE that can propagate along the waveguide. Presented in the paper are results from the commissioning of dynamic shear apparatus used to subject full scale active waveguide models to simulated slope movements. The results confirm that AE rates generated are proportional to the rate of deformation, and the coefficient of proportionality that defines the relationship has been quantified (e.g. 4.4 x 105 for the angular gravel examined). The authors demonstrate that slope velocities can be quantified continuously in real-time through monitoring active waveguide generated AE during a slope failure simulation. The results show that the technique can quantify landslide velocity to better than an order of magnitude (i.e. consistent with standard landslide movement classification) and can therefore be used to provide an early warning of slope instability through detecting and quantifying accelerations of slope movement