Landslides are the main secondary effects of earthquakes in mountainous areas. The spatial distribution of these landslides is controlled by the local seismic ground motion and the local slope stability. While gravitational instabilities in arid and semi-arid environments are understudied, we document the landslides triggered by the Sarpol Zahab earthquake (November 12, 2017, Mw7.3, Iran/Iraq border), the largest event ever recorded in the semi-arid Zagros Mountains. An original earthquake-induced landslide inventory was derived, encompassing landslides of various sizes and velocities (from rapid disrupted rockfalls to slow-moving coherent landslides). This inventory confirms the low level of triggered landslides in semi-arid environments. It also displays clear differences in the spatial and volumetric distributions of earthquake-induced landslides, having 386 rockfalls of limited size triggered around the epicenter, and 9 giant (areas of ca. 106 m2) active and ancient deep-seated landslides coseismically accelerated at locations up to 180 km from the epicenter. This unusual distant triggering is discussed and interpreted as an interaction between the earthquake source properties and the local geological conditions, emphasizing the key role of seismic ground motion variability at short spatial scales in triggering landslides. Finally, the study documents the kinematics of slow-moving ancient landslides accelerated by earthquakes, and opens up new perspectives for studying landslide triggering over short (~ 1–10 years) and long-time (~ 1000–10,000 years) periods.

Flow-like landslides in clay slopes pose major threats to people and infrastructure, which has led to numerous studies in recent decades. However, the mechanisms leading to the solid-fluid transition in clay are still poorly understood, despite numerous studies on its rheological evolution. The aim of this study is to contribute to quantify the degradation of clay at the surface of the Harmaliere landslide (French Alps) from the analysis of a series of three unmanned aerial vehicle (UAV) acquisitions. Two approaches were combined to process the acquired optical images. First, image classification was performed applying object-based image analysis (OBIA) to the red, green and blue (RGB) and surface roughness layers. Second, deeper analysis of the surface roughness allows to describe the morphology evolution and to interpret the degradation scheme from undegraded clay to degraded clay. The study shows that the applied methodology is appropriate to perform a thorough analysis of the material degradation pattern on the surface of a landslide. The temporal analysis shows an average degradation rate leading to the complete degradation of a block in about 2 years. Meanwhile, a spatial analysis shows that non-degraded clays degrade faster in the lower part of the study area, reactivated 30 years ago, than in the upper part, reactivated only a few years ago. In addition, roughness analyses enabled to highlight the evolution of the morphology during the degradation process of the clay blocks, from angular blocks to mounds.

Ambient Vibration-Based Structural Health Monitoring (AVB–SHM) studies on prone-to-fall rock compartments have recently succeeded in detecting both pre-failure damaging processes and reinforcement provided by bolting. The current AVB–SHM instrumentation layout is yet generally an overkill, creating cost and power issues and sometimes requiring advanced signal processing techniques. In this article, we paved the way toward an innovative edge-computing approach tested on ambient vibration records made during the bolting of a ~760 m3 limestone rock column (Vercors, France). First, we established some guidelines for prone-to-fall rock column AVB–SHM by comparing several basic, computing-efficient, seismic parameters (i.e., Fast Fourier Transform, Horizontal to Vertical and Horizontal to Horizontal Spectral Ratios). All three parameters performed well in revealing the unstable compartment’s fundamental resonance frequency. HHSR appeared as the most consistent spectral estimator, succeeding in revealing both the fundamental and higher modes. Only the fundamental mode should be trustfully monitored with HVSR since higher peaks may be artifacts. Then, the first application of a novelty detection algorithm on an unstable rock column AVB–SHM case study showed the following: the feasibility of automatic removing the adverse thermomechanical fluctuations in column’s dynamic parameters based on machine learning, as well as the systematic detection of clear, permanent change in column’s dynamic behavior after grout injection and hardening around the bolts (i1 and i2). This implementation represents a significant workload reduction, compared to physical-based algorithms or numerical twin modeling, and shows better robustness with regard to instrumentation gaps. We believe that edge-computing monitoring systems combining basic seismic signal processing techniques and automatic detection algorithms could help facilitate AVB–SHM of remote natural structures such as prone-to-fall rock compartments.

On November 12th 2017, the largest earthquake (Mw 7.3) ever recorded in the Zagros mountains occurred near the town of Sarpol-Zahab, Iran. While this region encompasses clusters of giant ancient ro...

The spatial incoherence of ground motion during an earthquake can have a significant effect on the dynamic response of engineering structures such as bridges, dams, nuclear power plants and lifeline facilities. The main objective of this paper is to study the effect of anisotropic heterogeneities in a soil layer overlying homogeneous bedrock on the lagged coherency of surface ground motion. A set of numerical experiments is performed based on 2D spatial variability of shear-wave velocities modeled as a homogeneous stationary random field and discretized by the EOLE method (Expansion Optimal Linear Estimation). Seismic ground motions were simulated using FLAC(2D) software in the 1-25 Hz band for a plane wave excitation with SV polarization. The soil is characterized by horizontal and vertical autocorrelation distances ranging between 5 and 20 m and 1 and 2 m, respectively, and a coefficient of variation of the shear-wave velocity varying between 5% and 40%. The synthetic seismograms calculated for 9 parameter sets (100 realizations each) clearly show seismic waves scattering and surface waves diffracted locally by the ground heterogeneities, generating large spatial variations in coherence mainly controlled by the coefficient of variation of shear-wave velocity. Consistently with existing models and experimental data, the numerical coherency curves decrease with frequency and receiver distance, however at a rate which is lower than that observed in the experimental data. This difference is probably due to intrinsic attenuation that is not accounted for in the simulations and/or to our 2D simulations that do not reproduce the complete wavefield. The numerical average coherency curves for each parameter set exhibit maxima within narrow frequency bands caused by the vertically trapped body waves and surface wave propagation properties within the average ground model. This interpretation is supported by experimental data recorded in the Koutavos-Argostoli valley (Greece).

The mass transfer mechanisms in landslides are complex to monitor because of their suddenness and spatial coverage. The active clayey Harmalière landslide, located 30 km south of Grenoble in the French Alps, exhibits two types of behavior: in its upper part, decameter-sized clay blocks slide along a listric slip surface, while a flow-like mechanism is observed in a clayey remolded material a few hundred meters below the headscarp. The landslide underwent a major retrogression affecting 45 ha in March 1981 and has experienced multiple reactivations since then. The last major event took place on the 26 th of June 2016, and a large investigation survey was conducted to better understand the reactivation mechanism. A multi-method investigation was carried out at different temporal and spatial scales, including aerial photograph and light detection and ranging processing, correlation of optical satellite images, global navigation satellite system monitoring, continuous seismic monitoring, and passive seismic survey. The morphological evolution of the landslide was traced over the last 70 years, showing a headscarp retrogression of 700 m during multiple reactivations and a total mass transfer of more than 6 × 10 6 m 3 . The detailed study of the 2016 event allowed to track and understand the mechanism of a mass transfer of 1 × 10 6 m 3 in 5 weeks, from a sliding mechanism at the headscarp to an earthflow at the toe.

Continuous ambient seismic monitoring of potentially unstable sites is increasingly attracting the attention of researchers for precursor recognition and early warning purposes. Twelve cases of long-term continuous noise monitoring have been reported in the literature between 2012 and 2020. Only in a few cases rupture was achieved and irreversible drops in resonance frequency values or shear wave velocity extracted from noise recordings were documented. On the other hand, all monitored sites showed clear reversible fluctuations of the seismic parameters on a daily and seasonal scale due to changes in external weather conditions (air temperature and precipitation). A quantitative comparison of these reversible modifications is used to gain insight into the mechanisms driving the site seismic response. Six possible mechanisms were identified, including three temperature-driven mechanisms (temperature control on fracture opening/closing, superficial stress conditions and bulk rigidity), one precipitation-driven mechanism (water infiltration effect) and two mechanisms sensitive to both temperature and precipitation (ice formation and clay behavior). The reversible variations in seismic parameters under the meteorological constraints are synthesized and compared to the irreversible changes observed prior to failure in different geological conditions.

Electrical Restivity Tomography (ERT) is one of the most employed geophysical technique to monitor landslide evolution. The measured variations of resistivity can be related to changes in underground moisture, porosity, water chemistry, etc. With electrodes installed on the moving mass, resistivity variations may also be related to changes in electrode location relative to each other (the so-called geometric factor K). As such, ERT monitoring should also require the monitoring of electrode location. Wilkinson et al. (2010, 2015) were able to track movements of electrodes by measuring variations of resistivity. However, this approach needs the strong assumption that resistivity variations are caused by changes in the geometric factor without any underground change. For example, Gance et al. (2015) showed the significant effect of surface fissures on ERT measurements. In this work we tested ERT monitoring of an earthslide (the Pont-Bourquin Landslide in the Swiss Alps) with electrodes located immediately outside the unstable zone. The setup was composed of 36 electrodes (24 on the right bank and 12 on the left bank) acquiring 1654 measurements per day in a dipole-dipole configuration (half direct and half reciprocal measurements). 235 daily sequences were acquired between February and November 2015. Data were filtered and then processed with the BERT package (Günther et al., 2006). Several time-lapse approaches were tested with different starting models originating from the 3D inversion of 4, 2D profiles and the results were analyzed in terms of resistivity and sensitivity variations. The resulting 3D models were then split in distinct zones (transport and accumulation zones) and the ERT time-series were then correlated with environmental time-series (e.g. rainfall). Results indicate that, despite a lack of sensitivity in the unstable zone because of the monitoring set-up, ERT is sensitive to environmental variations but no distinct behaviour could be observed within the zones. However, correlations provide informations in agreement with passive seismic monitoring (Bièvre et al., 2018) and suggest that resistivity (along with shear wave velocity) is strongly affected by rainfall with an effect that does not last more than 2 to 3 days. These results confirm that the superficial layers (first metres) have a major influence on resistivity measurements. More generally these results, along with many published works, question the added value of ERT to monitor landslides for depths greater than the superficial phreatic water table. References Bièvre G et al. (2018) Eng. Geol. 245, 248 - 257. doi:10.1016/j.enggeo.2018.08.01 Gance J et al. (2015) Geophy. J. Int. 200, 1118-1135. doi:10.1093/gji/ggu453 Günther T et al. (2006) Geophy. J. Int. 166, 506-517. doi:10.1111/j.1365-246X.2006.03011.x Wilkinson P B et al. (2010) Geophy. J. Int. 183, 543-556. doi:10.1111/j.1365-246X.2010.04760.x Wilkinson P B et al. (2015) Geophy. J. Int. 200, 1566-1581. doi:10.1093/gji/ggu483

Remote sensing techniques are leading methodologies for landslide characterization and monitoring. However, they may be limited in highly vegetated areas and do not allow for continuously tracking the evolution to failure in an early warning perspective. Alternative or complementary methods should be designed for potentially unstable sites in these environments. The results of a six-month passive seismic monitoring experiment on a prone-to-fall quartzite tower are here presented. Ambient seismic noise and microseismicity analyses were carried out on the continuously recorded seismic traces to characterize site stability and monitor its possible irreversible and reversible modifications driven by meteorological factors, in comparison with displacement measured on site. No irreversible modifications in the measured seismic parameters (i.e., natural resonance frequencies of the tower, seismic velocity changes, rupture-related microseismic signals) were detected in the monitored period, and no permanent displacement was observed at the tower top. Results highlighted, however, a strong temperature control on these parameters and unusual preferential vibration directions with respect to the literature case studies on nearly 2D rock columns, likely due the tower geometric constraints, as confirmed by 3D numerical modeling. A clear correlation with the tower displacement rate was found in the results, supporting the suitability of passive seismic monitoring systems for site characterization and early waning purposes.

Billions of passive radiofrequency tags are produced by the Radio-Frequency Identification (RFID) industry every year to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing for earth science. Indeed, the cost of tags is often several orders of magnitudes below conventional outdoor sensors used in earth science, allowing to deploy up to thousands of tags with minimal investment. Furthermore, passive wireless tags require little maintenance, which fits well for years-long monitoring. This study reviews the earth science applications that are being developed today, that use RFID devices available on the market, i.e., 900 MHz far-field tags and 125 kHz near-field tags. Ground displacements of centimeters to hundreds of meters can be monitored using RFID location techniques. Indeed, RFID tags were firstly used in earth science to track the displacement of riverine and coastal sediments due to bedloading. Near-field tags inserted in pebbles can be identified typically up to 0.5 m from the reading device even when buried. The tags are read either by fixed portals or by a mobile device, obtaining either high space or time resolution data, respectively. Very recently, measuring the phase difference of arrival of far-field tags allowed to estimate displacements with centimetric accuracy, with a tag-reader distance up to 50 m. That allowed measuring the ground displacements continuously relatively to a fixed reader, or to estimate tags location placed on the ground by carrying a reader over a drone using the synthetic aperture radar method. Alternatively, RFID tags can also be used for sensing the evolution over time of the temperature, moisture level, vibrations, resonant frequency or crack opening of a geologic object. This review presents multiple applications for monitoring unstable rock/earth structures using RFID. First, slow landslides can be monitored with accurate displacement monitoring and with soil moisture sensors. Then, prone-to-failure rock columns could be monitored by sensing crack opening or resonant frequency, using the same tags as with the concrete structure applications. Finally, sediment loading due to rapid mass movements such as floods, debris flows, tsunami or typhoons, have been studied largely using tags placed into pebbles. Author’s published work on the topic: * Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D., Guyoton, F., 2017. Outdoor UHF RFID: Phase Stabilization for Real-World Applications. IEEE Journal of Radio Frequency Identification 1, 279–290. * Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D., Guyoton, F., Jaboyedoff, M., 2019. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Engineering Geology 250, 1–10. * Le Breton, M., 2019. Suivi temporel d’un glissement de terrain à l’aide d’étiquettes RFID passives, couplé à l’observation de pluviométrie et de bruit sismique ambiant (PhD Thesis). Université Grenoble Alpes, ISTerre, Grenoble, France.

Many regions of the world are exposed to landslides in clay deposits, which poses major problems for land management and population safety. In recent years, optical satellite imaging has emerged as a major and inexpensive tool for understanding and monitoring the kinematics of slow moving landslides, such as earthflows/earthslides, through easy access of data and reliable calibration. The Sentinel-2 optical satellites provide a global coverage of land surfaces with a 5-day revisit time at the Equator. We studied the ability of these freely available optical images to detect landslide reactivations in a zone of 25 km2 around the Harmalière landslide in the Trièves area (western Alps, France). This area is characterized by the presence of a thick lacustrine clay layer that is affected by numerous landslides. Using a 9-month time-series of displacement derived from Sentinel-2 data, Lacroix et al. 2018 recently evidenced a precursor displacement of a major reactivation of the Harmalière landslide that occurred in June 2016. In this study, we attempted to detect following reactivations using the medium resolution high frequency satellite images (Sentinel 2) coupled with high resolution images (Pléiades) over a longer period (2016- 2019). We used an inversion strategy of redundant cross-correlation images to produce a robust time-series of displacement from Sentinel 2 data (Bontemps et al. 2018). By applying this technique, we were able to identify a reactivation of the same order of magnitude as the previous one, which affected the headscarp in January 2017. The reactivation signal is validated by the cross-correlation of Pléiades images taken at 2 years interval. We quantified this reactivation in time and space. We have also identified an area of 30x103 m2 located at the foot of the landslide, which was simultaneously accelerated by 10 m/month during this event. This information contributes to better understand the dynamics of the landslide that evolves from a solid to fluid behavior from the headscarp to the toe. However, a smaller slide that occurred in January 2018 at the headscarp was not detected by this method despite its significant size (10x103 m2). We attribute this non-detection to a major reshaping of the surface following reactivation. This study identified the possibilities and limitations of the proposed treatment method to detect and monitor landslides on a low-slope area located in clayey soils in a temperate climate. Bontemps, N., Lacroix, P. & Doin, M.-P. (2018) Inversion of deformation fields time-series from optical images, and application to the long term kinematics of slow-moving landslides in Peru. Remote Sensing of Environment, 210, 144–158. doi:10.1016/j.rse.2018.02.023 Lacroix, P., Bièvre, G., Pathier, E., Kniess, U. & Jongmans, D. (2018) Use of Sentinel-2 images for the detection of precursory motions before landslide failures. Remote Sensing of Environment, 215, 507–516. doi:10.1016/j.rse.2018.03.042

Many regions of the world are exposed to landslides in clayey deposits, which pose major problems for land management and human safety. Clayey landslide activity is complex, showing a succession of periods of inactivity and reactivation phases that can evolve into sudden acceleration and catastrophic landslides and/or flows. Understanding the processes that control this activity therefore requires the continuous monitoring of specific parameters. At the end of June 2016, the Harmalière clayey landslide (located 30 km south of the city of Grenoble in the French Alps) was dramatically reactivated at the headscarp after 35 years of continuous but limited activity. The total volume involved, which moved in the form of tilted blocks of different sizes, was estimated at about 3,106 m3. Several sensors, including seismometers and GNSS stations, were installed immediately behind the main escarpment in early August 2016. They recorded a rupture involving a block of a few hundred cubic meters in November 2016. Additional data (seismology, meteorology, piezometer, etc.) were provided by a permanent observatory located a few hundred meters away in the nearby Avignonet landslide (RESIF2006). Two three-component seismic sensors were placed on the collapsed block and 10 meters aft on the stable part respectively. Thus, four seismic parameters were monitored for 4 months until the clay block rupture: the cumulative number of microseisms, the resonance frequency of the block, the relative variation in Rayleigh wave velocity (dV/V) and the correlation coefficient (CC) in the range 1-12 Hz. All these parameters showed a significant precursor signal before the rupture, but at very different times. During the monitoring period, they also showed different responses to environmental parameters and in particular to precipitation. The resonance frequency increased slightly but steadily from 8 to 9 Hz (+12%) during the pre-break period, then decreased from 9 Hz to 7 Hz (-22%) just one hour before the break. However, the other three parameters showed significant variations a few weeks before failure. The dV/V and CC parameters reacted 1.5 month before the failure, during a very heavy rain event. The CC showed a general decrease over time, first affecting the high frequencies, then gradually spreading to the low frequencies. Finally, seismic activity is almost constant during the first three months, with only slight temporary increases during precipitation. One month before the rupture, a significant increase in the number of events is observed. This study shows the potential of monitoring different seismic parameters over time in order to predict the slip of blocks in a clay material.

Monitoring landslides is essential to understand their dynamics and to reduce the risk of human losses by detecting precursors before failures. In general, surface observations need to be complemented by observation at depth, in the bulk of the material. A decade ago, the ambient seismic noise interferometry method was proposed to monitor changes in the seismic surface wave velocity. As seismic wave velocities are directly related to the rigidity of the material, any reduction of seismic velocity can be associated to a loss of rigidity with high probability (a route toward soil liquefaction or to high fracturation). This technique led to detect a velocity decrease several days before the failure of a clayey landslide [1], paving the way to a novel precursor signal that could serve for alert or early warning systems. Here we report at least five different landslides that have been monitored, over several years [2]. In this paper, we detail the standard experimental configuration, the basic signal processing procedure, the sensitivity and resolution of the method, together with its advantages and possible limitations. Environmental effects on the relative seismic velocity change are discussed. In order to make the technology operational for decision makers, we built an online application with web portal displaying daily evolution of seismic velocity variation. This portal also integrates other available observations like environmental parameters (weather, precipitations) or surface observation (photogrammetry, gps, extensometers…). [1] G. Mainsant, E. Larose, C. Brönnimann, D. Jongmans, C. Michoud, M. Jaboyedoff, Ambient seismic noise monitoring of a clay landslide : toward failure prediction, J. Geophys. Res. 117, F01030 (2012). [2] M. Le Breton, N. Bontemps, A. Guillemot, L. Baillet, E. Larose, Landslide Monitoring Using Seismic Ambient Noise In-terferometry: Challenges and Applications, Earth Science Review (under review) (2020)

Many regions of the world are exposed to landslides in clay deposits, which poses major problems for land management and population safety. In recent years, optical satellite imaging has emerged as a major and inexpensive tool for understanding and monitoring the kinematics of slow moving landslides, such as earthflows/earthslides, through easy access of data and reliable calibration. The Sentinel-2 optical satellites provide a global coverage of land surfaces with a 5-day revisit time at the Equator. We studied the ability of these freely available optical images to detect landslide reactivations in a zone of 25 km2 around the Harmalière landslide in the Trièves area (western Alps, France). This area is characterized by the presence of a thick lacustrine clay layer that is affected by numerous landslides. Using a 9-month time-series of displacement derived from Sentinel-2 data, Lacroix et al. 2018 recently evidenced a precursor displacement of a major reactivation of the Harmalière landslide that occurred in June 2016. In this study, we attempted to detect following reactivations using the medium resolution high frequency satellite images (Sentinel 2) coupled with high resolution images (Pléiades) over a longer period (2016- 2019). We used an inversion strategy of redundant cross-correlation images to produce a robust time-series of displacement from Sentinel 2 data (Bontemps et al. 2018). By applying this technique, we were able to identify a reactivation of the same order of magnitude as the previous one, which affected the headscarp in January 2017. The reactivation signal is validated by the cross-correlation of Pléiades images taken at 2 years interval. We quantified this reactivation in time and space. We have also identified an area of 30x103 m2 located at the foot of the landslide, which was simultaneously accelerated by 10 m/month during this event. This information contributes to better understand the dynamics of the landslide that evolves from a solid to fluid behavior from the headscarp to the toe. However, a smaller slide that occurred in January 2018 at the headscarp was not detected by this method despite its significant size (10x103 m2). We attribute this non-detection to a major reshaping of the surface following reactivation. This study identified the possibilities and limitations of the proposed treatment method to detect and monitor landslides on a low-slope area located in clayey soils in a temperate climate. Bontemps, N., Lacroix, P. & Doin, M.-P. (2018) Inversion of deformation fields time-series from optical images, and application to the long term kinematics of slow-moving landslides in Peru. Remote Sensing of Environment, 210, 144–158. doi:10.1016/j.rse.2018.02.023 Lacroix, P., Bièvre, G., Pathier, E., Kniess, U. & Jongmans, D. (2018) Use of Sentinel-2 images for the detection of precursory motions before landslide failures. Remote Sensing of Environment, 215, 507–516. doi:10.1016/j.rse.2018.03.042

Geophysical monitoring of landslides has developed strongly in recent years with the use of electrical resistivity imaging on the one hand, and the application of techniques based on continuous seismic recordings on the other hand. The paper resituates these developments within the general framework of the application of geophysical methods to landslides and focus on the definition of relevant geophysical parameters that can be precursors to activation or reactivation phases. Four recent case studies from the literature illustrate the potential and limitations of geophysics for landslide monitoring. Development prospects, especially for integration into early warning systems, are discussed.

Zagros Mountains form a seismically active fold and thrust belt in western Iran. In addition to the high levels of seismicity, slope failures are common throughout the region, where historical records of very large landslides (> 30 km3) are documented. On the November 12th 2017, the largest earthquake (Mw 7.3) ever recorded in the Zagros occurred near the town of Sarpol-Zahab (NW Zagros/Iraq border). Following the earthquake, only one large co-seismic rockslide and some small rockfalls were documented near the epicenter. This rather small landslide activity for such a large earthquake raises the question of both the observation completeness and the controlling factors of the landslide triggering in this arid mountainous environment. We conducted an original inventory mapping of the landslides induced by this event along 200 km of the Iran-Iraq border. The landslides were detected by different methods: the scars of rapid co-seismic landslides were mapped using a comparison of pre- and post-seismic Planetlab images (3 m resolution), whereas slow-moving landslides (cm/yr-m/yr) were detected by deriving time-series of ground deformation from radar and optical satellite images. Interferometric measurements were constructed for 3 ascending and descending Sentinel-1 SAR tracks, over a time period of 15 months (spanning 6 months before and 9 months after the main shock), allowing the detection and monitoring of very-slow-moving landslides (cm/yr), while slow-moving landslides of higher velocities (m/yr) were detected from correlation of pre and post-earthquake optical satellite images (Planet and SPOT67 imagery; 3 m and 1.5 m resolution, respectively), orthorectified over precise DEMs. We detected 8 giant rotational rockslides (3.106 to 3.107 m2) and 360 small rockfalls (2.102 to 2.104 m2) in our study area. The small slope-failures were concentrated in the steepest areas around the epicenter (within a radius of 45 km) while the giant ones were situated in far fields (150 km far from the epicenter). Geomorphological analysis of the giant landslides revealed the reactivation of huge masses with several hundreds meters scarps at their top and runout distance of several hundreds meters, advancing over a river at their toe. The geodetical analysis of these giant landslides, show their co-seismic acceleration by few cm. Furthermore, the analysis of the displacement time-series of these giant rockslides shows that four of them are destabilized over the longer term. This observation raises question both of the risk posed by these rockslides and the controlling factors of their initiation. A geological and seismological analysis suggests that the triggering of these giant rockslides can be controlled by the geological structure (stratigraphy and folding) and the resulting topography, as well as by the fault mechanism of major earthquakes. Finally, the landslide reactivation mechanism during the Sarpol-Zahab earthquake is discussed.

SUMMARYIn late June 2016, the Harmalière clayey landslide (located 30 km south of the city of Grenoble, French Alps) was dramatically reactivated at the headscarp after a 35-yr-long period of continuous but limited activity. The total involved volume, which moved as sliding blocks of various sizes, was estimated to be about 2 × 10 6 m3. Two seismometers were installed at the rear of the main headscarp in August 2016, on both sides of a developing fracture delineating a block with a volume of a few hundred cubic metres. For 4 months, they continuously recorded seismic ambient vibrations and microearthquakes until the block broke. Five seismic parameters were derived from the monitoring: the cumulative number of microearthquakes (CNe), the seismic energy (SE), the block resonance frequency (fB), the relative variation in Rayleigh wave velocity (dV/V) deduced from noise cross-correlations between the two sensors and the associated correlation coefficient (CC). All parameters showed a significant precursory signal before the rupture, but at very different times, which indicates the complexity of the rupture mechanism in this clay material.