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Innovative Monitoring Tools and Early Warning Systems for Risk Management: A Case Study

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  • ASE s.r.l.

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During recent years, the availability of innovative monitoring instrumentation has been a fundamental component in the development of efficient and reliable early warning systems (EWS). In fact, the potential to achieve high sampling frequencies, together with automatic data transmission and elaboration are key features for a near-real time approach. This paper presents a case study located in Central Italy, where the realization of an important state route required a series of preliminary surveys. The monitoring system installed on site included manual inclinometers, automatic modular underground monitoring system (MUMS) inclinometers, piezometers, and geognostic surveys. In particular, data recorded by innovative instrumentation allowed for the detection of major slope displacements that ultimately led to the landslide collapse. The implementation of advanced tools, featuring remote and automatic procedures for data sampling and elaboration, played a key role in the critical event identification and prediction. In fact, thanks to displacement data recorded by the MUMS inclinometer, it was possible to forecast the slope failure that was later confirmed during the following site inspection. Additionally, a numerical analysis was performed to better understand the mechanical behavior of the slope, back-analyze the monitored event, and to assess the stability conditions of the area of interest.
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... The identification of pre-failure conditions in areas presenting instability signs can be performed through in-situ observations and monitoring (Brunner, Hartinger, and Richter 2000;Borgatti et al. 2008;Cascini et al. 2019;Segalini et al. 2019), by exploiting satellitebased technologies such as Interferometric Synthetic Aperture Radar (InSAR) Lacroix et al. 2018;Reyes-Carmona et al. 2020), optical image data (Desrues, Lacroix, and Brenguier 2019), or a combination of different sensors (Clarkson, Williams, and Seppälä 2020). The parameters controlling the landslides effect in term of hazard and landscape change include the landslide occurrence time, size, duration, speed, and total amount of their movement (Schulz et al. 2018). ...
... This theory generated mainly empirical and semi-empirical methodologies, all based on the assumption that the time of slope failure can be forecasted by extrapolating the trend towards zero of the inverse-velocity vs time plot. In particular, collapse predictions obtained through the applications of the Inverse Velocity Method (IVM) firstly introduced by Fukuzono (1985) can be found in literature, displaying generally positive results (Petley 2004;Rose and Hungr 2007;Segalini et al. 2019). ...
Article
Landslides represent a serious hazard in many areas around the world, potentially leading to human losses and significant damages to structures and buildings. For this reason, over the years a consistent number of studies and researches have been carried out to analyse these natural phenomena and their evolution. This study presents the application of an automatic procedure specifically developed to identify the onset of landslide acceleration by analysing monitoring displacement data with a multi-criteria approach. The proposed procedure aims to identify this point by applying a four-level validation process on a pre-determined dataset. Once the analysis returns a positive result for a certain number of monitoring data, it is possible to state that the landslide reached the accelerating phase of its evolution, thus allowing to define a specific point representing the onset of acceleration. The method was applied to several historical case studies taken from scientific literature, in order to test its practicability and effectiveness. This procedure could be especially useful in Early Warning Systems where time of failure forecasting models are implemented, allowing to improve their performances by providing an automated and reliable procedure to define the beginning of potentially critical landslide events.
... Several methods are available to obtain deformation measurements, each with different characteristics, temporal sampling, and spatial coverage. Local techniques include crackmeters, extensometers and inclinometers, that quantify in-situ deformation at the specific location at the landslide or building they are applied to (Logar et al., 2017;Segalini et al., 2019). Slope scale techniques, used to quantify differential deformation within a landslide, include total station measurements, and Global Navigation Satellite System (GNSS) measurement campaigns (Benoit et al., 2015). ...
Article
Full-text available
Slow-moving landslides move downslope at velocities that range from mm year ⁻¹ to m year ⁻¹ . Such deformations can be measured using satellite-based synthetic aperture radar interferometry (InSAR). We developed a new method to systematically detect and quantify accelerations and decelerations of slowly deforming areas using InSAR displacement time series. The displacement time series are filtered using an outlier detector and subsequently piecewise linear functions are fitted to identify changes in the displacement rate (i.e., accelerations or decelerations). Grouped accelerations and decelerations are inventoried as indicators of potential unstable areas. We tested and refined our new method using a high-quality dataset from the Mud Creek landslide, CA, USA. Our method detects accelerations and decelerations that coincide with those previously detected by manual examination. Second, we tested our method in the region around the Mazar dam and reservoir in Southeast Ecuador, where the time series data were of considerably lower quality. We detected accelerations and decelerations occurring during the entire study period near and upslope of the reservoir. Application of our method results in a wealth of information on the dynamics of the surface displacement of hillslopes and provides an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of accelerations and decelerations can be used to study the physical behavior of a slow-moving slope or for regional hazard assessment by linking the timing of changes in displacement rates to landslide causal and triggering factors.
... Several methods are available to obtain deformation measurements, each with different characteristics, temporal sampling, and spatial coverage. Local techniques include crackmeters, extensometers and inclinometers, that quantify in-situ deformation at the specific location at the landslide or building they are applied to (Logar et al., 2017;Segalini et al., 2019). Slope scale techniques, used to quantify differential deformation within a landslide, include total station measurements, and Global Navigation Satellite System (GNSS) measurement campaigns (Benoit et al., 2015). ...
Article
Landslides are a major geohazard in hilly and mountainous environments. In-situ inspection of downslope motion is costly, sometimes dangerous and, requires prior knowledge of the existence of a landslide. Remote sensing from space is a way to detect and characterize landslides systematically at large scale. Interferometric Synthetic Aperture Radar (InSAR) has shown to be a valuable resource of deformation information, but it requires expert knowledge and considerable computational efforts. Moreover, the successful application of InSAR for landslides requires a favorable acquisition geometry relative to the landslide deformation pattern. Consequently, there is a need for a widely applicable tool to assess the potential of InSAR at a particular location a priori. Here we present a novel, generic approach to assess the potential of InSAR-based deformation tracking, providing a standardised and automated method applicable on any slope. We define the detection potential as the sensitivity of InSAR to detect downslope displacement combined with the presence of coherently scattering surfaces. We show that deformation can be detected on at least 91% of the global landslide-prone slopes, and provide an open source Google Earth Engine tool for the quick assessment of the availability of potential coherent scatterers. This tool enables any person interested in applying InSAR to routinely assess the potential for monitoring landslide deformation in their region of interest.
... Each of the physical principles has its advantages and its use depends on the application. Sucesfull innovation of underground displacement monitoring based on MEMS sensors inclinometers were developed in Italy [2,3]. Inertial measurement unit is an essential part of devices used for the Global navigation satellite system, aerial photogrammetry, laser altimetry, remote sensing technologies, unmanned aerial vehicles, but it is also the main component of unmanned ground and marine vehicles. ...
Article
Full-text available
The inertial measurement unit is an electronic device built-in practically in any controlled or autonomous technology used for land mapping. It is based on a combination of accelerometers and gyroscopes and sometimes magnetometers used for relative orientation and navigation. The paper is focused on functions and trends of an inertial measurement unit, which is a part of inertial navigation indicator of position and velocity of moving devices on the ground, above and below ground in real-time.
... The IVM has been effectively applied to several landslides (e.g. Segalini et al. 2019) and it has also provided satisfactory forecasting results when using InSAR data Carlà et al. 2017Carlà et al. , 2019Moretto et al. 2017;Intrieri et al. 2018). For the correct implementation of the IVM to identify possible accelerations, the monitoring activity should be constant in time and continued for as long as possible (Valletta et al. 2020). ...
Preprint
When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of up to 2 cm/yr was obtained by means of Synthetic Aperture Radar Interferometry (InSAR) and Ground Penetrating Radar (GPR) data, during the last 5 and 22 years, respectively. The Structure-from-Motion (SfM) technique provided a higher rate, up to 26 cm/yr during the last 14 years, due to compaction of a slag heap located within the foot of the landslide. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. Differential Global Positioning Systems, inclinometers, ground drilling and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures.
... The IVM has been effectively applied to several landslides (e.g. Segalini et al. 2019) and it has also provided satisfactory forecasting results when using InSAR data Carlà et al. 2017Carlà et al. , 2019Moretto et al. 2017;Intrieri et al. 2018). For the correct implementation of the IVM to identify possible accelerations, the monitoring activity should be constant in time and continued for as long as possible (Valletta et al. 2020). ...
Article
[See the full-text in the following link: https://rdcu.be/cyFI0]. When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of the landslide around 2 cm/year was obtained by means of synthetic aperture radar interferometry (InSAR) and ground-penetrating radar (GPR) data, during the last 5 and 22 years, respectively. The structure-from-motion (SfM) technique provided a rate up to 26 cm/year during the last 14 years of a slag heap located within the foot of the landslide, due to compaction of the anthropical deposits. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. differential global positioning systems, inclinometers, ground drilling, and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures.
... Therefore, more sophisticated instruments which can record continuous movement, are much more useful. No single technique or instrument can provide complete information about a landslide, and therefore various combinations are usually employed (e.g.García et al. 2010;Brückl et al. 2013;Smethurst et al. 2017;Segalini et al. 2019). Some potentially useful slope monitoring approaches for sites in Fiji are outlined below. ...
Thesis
Landslides are a common geological hazard causing immense damage to life and structures around the world. In the nation of Fiji, especially on the main island of Viti Levu, landslides repeatedly damage key pieces of infrastructure such as arterial roads. This study addresses the issue of understanding the properties and mechanism of landslides in tropical residual soils triggered mostly by tropical cyclones and long-duration rainstorms. The study firstly began by understanding landslides along Kings Road in Viti Levu, Fiji in the aftermath of a Tropical Cyclone. This road of national importance is repeatedly affected by landslides during major rainfall events. The second phase of the study investigated the engineering properties of tropical residual soils of varying parent lithologies prone to landslides along roads in Viti Levu. The landslides were found to be numerous, but small, shallow and of complex types whereby rotational and translational earth and debris landslides transformed into flows. Residual soils most prone to slope failure along Kings Road, Lololo Road and Namosi Roads in Viti Levu are cohesive, plastic, sensitive, have low permeability and low residual strength. Failures are mostly driven by the formation of a perched water table during heavy rainfall, leading to excess porewater pressures to trigger the landslide. The third phase of study examined a specific landslide (the Kasavu Landslide). Computer modelling of this showed how the Kasavu Landslide materials were highly sensitive to increasing groundwater levels, with failure mechanisms varying with location in different parts of the landslide. No relationship was apparent between the engineering properties of failure-prone residual soils and underlying lithologies, but this requires further study. Tropical cyclones and floods affect Fiji annually, hence a proactive approach is needed to managing landslides hazards along Fiji’s trunk routes by relevant authorities. Several recommendations with regards to slope monitoring and stabilization have been made in this thesis which relevant authorities can consider. Monitoring slopes via Unmanned Aerial Vehicles, groundwater and precipitation are considered most useful for Fiji’s environment while relevant stabilization techniques not yet tried include use of soil nails and counterfeit drains. Full text available at: https://researchspace.auckland.ac.nz/handle/2292/50057
... Segalini et al. [4] describe a field-based monitoring system including piezometers, manual inclinometers, and automatic modular underground monitoring system (MUMS) inclinometers. Thanks to displacement data recorded by the latter, it was possible to forecast a slope failure. ...
Article
Full-text available
This editorial paper summarizes the contents of the papers included in the Special Issue “Mountain Landslides: Monitoring, Modeling, and Mitigation”. The Special Issue provides an overview of methodological papers, as well as some innovative research carried out in the field and in the lab. Even if most papers adopted an integrated approach, sections representing the three research issues outlined in the title can be drawn: the first deals with monitoring, the second focuses on modeling, and the third is related to mitigation. Regardless of the section, the papers included in this special issue put forward methodological and practical implications that, more than likely, can stimulate further research efforts and support the stakeholders to gain better knowledge of landslide hazards in mountain environments, with an aim to tackle the urgent issue of sustainable development in times of global change that can affect landslide occurrences in mountain chains of the world.
... Links can be customized, according to the case, with different sensors able to record quantities such as displacements, water level variations and temperature. MUMS technology has been successfully applied to different case studies, including landslides (Segalini et al., 2019), tunnels (Carri et al., 2017) and geothermal fields (Tinti et al., 2018). ...
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Tunnels and underground structures are one of the most important components of road and railway networks, especially near urban areas. For this reason, it is particularly important to identify potentially hazardous conditions in order to guarantee the structure's durability and practicability. This paper presents a case study where a seismic event severely damaged a road tunnel located in Central Italy, impairing its accessibility and leading to its closure for safety reasons. Following the damage assessment, and given the importance of this specific structure, it was decided to perform a series of renovation works aimed to restore the tunnel's operability. In this context, an innovative automatic monitoring device, able to measure the structure deformation, was installed in a critical section of the road tunnel. This instrument, called Cir Array, is specifically designed for near-real time monitoring of convergence phenomena and localized deformations inside underground structures, obtaining accurate and reliable results during their operational phase. The instrumentation provided useful information about the structure's conditions, playing a major role into assessing the tunnel's accessibility and safety during the renovation works. Moreover, thanks to its automated and high frequency sampling process, it will allow the implementation of dedicated warning procedures related to the passage of the vehicles inside the tunnel.
Presentation
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The identification of potentially critical events involving unstable slopes is a major aspect in the field of natural hazards risk mitigation and management. In this framework, Early Warning Systems (EWS) exploiting advanced technologies represent an efficient approach to decrease the risk generated by landslide phenomena, allowing to reduce the possibility of damages and losses of human lives. EWS effectiveness has increased significantly in recent years, thanks to relevant advances in sensing technologies and data processing. In particular, the introduction of innovative monitoring instrumentation featuring automatic procedures and increased performances in terms of sampling rate and accuracy has permitted to develop EWS characterised by a near-real time approach. Among the several aspects involved in the development of a reliable Early Warning System, one of the most important is the ability to minimize the dissemination of false alarms, which should be avoided or identified in advance. The approach proposed in this study represents a new procedure aimed to assess the hazard level posed by a potentially critical event, previously identified by analysing displacement monitoring data. The process is implemented in a near-real time EWS and defines a total of five different hazard levels, on the basis of the results provided by two different models, namely an accelerating trend identification criterion and a failure forecasting model based on the Inverse Velocity Method (IVM). In particular, the forecasting analysis is performed only if the dataset elaborated by the onset-of-acceleration model highlights a potentially critical behaviour, which represents a first alert level. Following levels are determined by different conditions imposed on three parameters featured by the failure forecasting model, i.e. dataset dimension, coefficient of determination R-squared, and number of sensors displaying an accelerating trend. As these criteria get fulfilled, it is assumed that the monitored phenomenon is gradually evolving towards a more critical condition, thus reaching an increasing alert level depending on the analysis results. According to this classification, it is possible to set up for each single threshold a dedicated warning message, which could be automatically issued to authorities responsible of monitoring activities, in order to provide an adequate dissemination of information concerning the ongoing event. Moreover, the proposed procedure allows to customize the alert approach, giving the possibility to issue warning messages only if a certain Level is reached during the analysis.
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To manage natural risks, an increasing effort is being put in the development of early warning systems (EWS), namely, approaches facing catastrophic phenomena by timely forecasting and alarm spreading throughout exposed population. Research efforts aimed at the development and implementation of effective EWS should especially concern the definition and calibration of the interpretative model. This paper analyses the main features characterizing predictive models working in EWS by discussing their aims and their features in terms of model accuracy, evolutionary stage of the phenomenon at which the prediction is carried out and model architecture. Original classification criteria based on these features are developed throughout the paper and shown in their practical implementation through examples of flow-like landslides and earth flows, both of which are characterized by rapid evolution and quite representative of many applications of EWS.
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Predicting the time of failure is a topic of major concern in the field of geological risk management. Several approaches, based on the analysis of displacement monitoring data, have been proposed in recent years to deal with the issue. Among these, the inverse velocity method surely demonstrated its effectiveness in anticipating the time of collapse of rock slopes displaying accelerating trends of deformation rate. However, inferring suitable linear trend lines and deducing reliable failure predictions from inverse velocity plots are processes that may be hampered by the noise present in the measurements; data smoothing is therefore a very important phase of inverse velocity analyses. In this study, different filters are tested on velocity time series from four case studies of geomechanical failure in order to improve, in retrospect, the reliability of failure predictions: Specifically, three major landslides and the collapse of an historical city wall in Italy have been examined. The effects of noise on the interpretation of inverse velocity graphs are also assessed. General guidelines to conveniently perform data smoothing, in relation to the specific characteristics of the acceleration phase, are deduced. Finally, with the aim of improving the practical use of the method and supporting the definition of emergency response plans, some standard procedures to automatically setup failure alarm levels are proposed. The thresholds which separate the alarm levels would be established without needing a long period of neither reference historical data nor calibration on past failure events.
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The paper proposes the evaluation of the technical performance of a regional landslide early warning system by means of an original approach, called EDuMaP method, comprising three successive steps: identification and analysis of the Events (E), i.e. landslide events and warning events derived from available landslides and warnings databases; definition and computation of a Duration Matrix (DuMa), whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model Performance (P) by means of performance criteria and indicators applied to the duration matrix. During the first step, the analyst takes into account the features of the warning model by means of ten input parameters, which are used to identify and classify landslide and warning events according to their spatial and temporal characteristics. In the second step, the analyst computes a time-based duration matrix having a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The proposed method is based on a framework clearly distinguishing between local and regional landslide early warning systems as well as among correlation laws, warning models and warning systems. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warnings data from the municipal early warning system operating in Rio de Janeiro (Brazil).
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Ten small rock slides (with a volume ranging from 101 to 103 m3) on a slope affected by working activities were detected, located, and timed using pictures collected by an automatic camera during 40 months of continuous monitoring with terrestrial SAR interferometry (TInSAR). These landslides were analyzed in detail by examining their pre-failure time series of displacement inferred from high-sampling frequency (approximately 5 min) TInSAR monitoring. In most of these cases, a typical creep behavior was observed with the displacement starting 370 to 12 h before the collapse. Additionally, an evident acceleration decrease of the displacement a few hours before the failure was observed in some rock/debris slides, thus suggesting the possibility of a mechanical feature of the slope that differs from the classical creep theory. The efficacy of the linear Fukuzono approach for the prediction of time of failure was tested by back-analyzing the ten landslides. Furthermore, a modified Fukuzono approach named average data Fukuzono (ADF) was implemented and applied to our dataset. Such an approach is able to improve forecasting effectiveness by reducing the error due to anomalies in the time series of displacement, like the acceleration decrease before failure. A prediction with a temporal accuracy of at least 2 h was obtained for all the analyzed rock/debris slides.
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Warning systems are increasingly applied to reduce damage caused by different magnitudes of rockslides and rock-falls. In an integrated risk-management approach, the optimal risk mitigation strategy is identified by comparing the achieved effectiveness and cost; estimating the reliability of the warning system is the basis for such considerations. Here, we calculate the reliability and effectiveness of the warning system installed in Preonzo prior to a major rockfall in May 2012. BReliability^ is defined as the ability of the warning system to forecast the hazard event and to prevent damage. To be cost-effective, the warning system should forecast an event with a limited number of false alarms to avoid unnecessary costs for intervention measures. The analysis shows that to be reliable, warning systems should be designed as fail-safe constructions. They should incorporate components with low failure probabilities, high redundancy, have low warning thresholds, and additional control systems. In addition, the experts operating the warning system should have limited risk tolerance. In an additional hypothetical probabilistic analysis, we investigate the effect of the risk attitude of the decision makers and of the number of sensors on the probability of detecting the event and initiating a timely evacuation, as well as on the related intervention cost. The analysis demonstrates that quantitative assessments can support the identification of optimal warning system designs and decision criteria.
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Rapid mass movements (RMM) pose a substantial risk to people and infrastructure. Reliable and cost-efficient measures have to be taken to reduce this risk. One of these measures includes establishing and advancing the state of practice in the application of early warning systems (EWSs). EWSs have been developed during the past decades and are rapidly increasing. In this paper, we focus on the technical part of EWSs, i.e., the prediction and timely recognition of imminent hazards, as well as on monitoring slopes at risk and released mass movements. Recent innovations in assessing spatial precipitation, monitoring and precursors of the triggering and deformation of RMM offer new opportunities for next-generation EWSs. However, technical advancement can only be transferred into more reliable, operational EWSs with an adequate well-instructed dedicated staff. To this end, an intense dialog between scientists, engineers and those in charge of warning, as well as further experience with new comprehensive prototype systems jointly operated by scientists and practitioners, will be essential.
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The forecast of a landslide's time of failure and the definition of alert thresholds are fundamental aspects in the study of natural hazards. However, these tasks are particularly difficult due to the large number of parameters and factors involved, and are therefore usually performed with a site-specific approach. This work describes an attempt to generalize the behavior of a landslide approaching collapse, with particular attention to the definition of a general criterion to define alert thresholds. The procedure started with the creation of a database of displacement data recorded for historical landslides, then the inverse velocity model was applied to these datasets to evaluate the time of failure under the assumption of linear behavior during the accelerating phase. A model calibration was conducted to best describe the monitored data and highlight any non-linear trend. A curve describing the velocity versus time relationship was then computed for each single slope failure case using the parameter obtained through this operation. In the final step of the study, these curves were processed with a normalization procedure, thus obtaining a dimensionless velocity-related coefficient. This parameter allowed the comparison of different landslide datasets on a single graph, which can be used as a general reference to define alert thresholds for emergency purposes. In order to test the criterion's ability to represent landslide behavior, the procedure was also applied to a different case by simulating progressive data acquisition.
Chapter
The paper illustrates the efficiency of a novel inclinometer device by comparing results obtained from some prototypes installed in three landslides and those derived from classic inclinometers. The new device, called Modular Underground Monitoring System (MUMS) is intended to be applied for natural and artificial slope deformation monitoring and landslides dynamics control, assessment and forecasting. The MUMS instrumentation was developed from the idea of replacing the standard measurement procedure by locating nodes at known distances along a connecting cable placed within a vertical borehole. Each node measures its local orientation (related to the National Elevation Dataset (NED)) by means of a micro electro-mechanical system (MEMS) formed by a 3D digital linear acceleration sensor and a 3D magnetic sensor. This allows us to determine the direction cosines of the borehole axis in each node and calculate its 3D shape and deformation along the whole borehole. This paper compares the classic instruments and the new MUMS device, with evidence of the advantages of measurement automation and economy in the use of the proposed device, which could also be equipped with other electronic instruments that would allow the measurement of other interesting physical quantities (i.e. pore pressure, temperature, stresses etc.) together with displacement components. The comparison is carried out through the examination of few installation in various types of landslides, with particular attention to the accuracy and repeatability of the measurements that are automatically made.
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This paper describes the analysis of the effectiveness and reliability of a new type of inclinometric chain, which is still under development by the authors, and is intended to be applied in the underground slope monitoring field. In the first part, the paper describes the new instrumentation which should allow for a deeper and detailed understanding of the type, location and origin of slope movements that should, in turn, help in understanding the triggering causes and the evolution mechanisms of landslides, and provide an innovative and substantial contribution to their stability analysis and control. The second portion of the paper is dedicated to a comparison between the classic instruments and the new MUMS device, demonstrating the advantages of measurement automation and economy in the use of the proposed device, which could also be equipped with other electronic instruments that would allow the measurement of other interesting physical quantities (such as pore pressure, temperature, stresses, etc.) together with displacement components.