Detecting precursors to slope destabilisation with sufficient lead time and accuracy remains a challenging and unresolved issue in landslide hazard assessment and prediction. This is key, as catastrophic landslides often go unnoticed until immediately before or after failure, limiting opportunities for intervention. While in situ methods offer high accuracy at point locations, they are costly and require prior knowledge of instability. Satellite-based synthetic aperture radar differential interferometry (InSAR) has shown promise in identifying unknown landslides over large areas and has been proposed as a potentially useful tool for failure prediction. Typically valued for retrieving displacement time series, InSAR time series reliability depends heavily on successful interferogram unwrapping, which often leads to severe underestimations over landslides. Here, we analyse the deformation process of the Achoma landslide in Peru and demonstrate that the InSAR signal contains precursors based on alternative markers, even without displacement time series. Interferometric coherence shows the formation of gravitational structures up to 5 years before failure, as well as a critical shift in landslide behaviour 3 months prior to failure. Additionally, a marker based on the wrapped phase reveals and quantifies alternating periods of quiescence and motion, the latter becoming more frequent in the 2 years before failure. Our findings highlight the potential to use alternative InSAR signal markers to observe the deformation process and progressive failure leading up to the event, and to detect landslide precursors across extensive areas, providing valuable lead time for intervention and disaster prevention.

Landslides in glacial and periglacial environments are increasingly affected by climate change, with sudden failures reported in high mountain regions and the Arctic. The complex mechanisms behind these events are often poorly understood due to a lack of dense in situ data. We investigate two slow-moving landslides in Arctic Norway (70° N), the Jettan and Gámanjunni landslides, located approximately 10 km apart: Jettan, a complex slide in micaschist and calcite marble situated below the permafrost boundary, and Gámanjunni, a rotational slide in micaschist situated above the permafrost boundary. Using over a decade of multi-physics observations, including geodetic, borehole, seismic, and hydrological data, we examine surface and subsurface deformation. Both landslides display similar seasonal surface velocity patterns, with peaks in spring and autumn, likely influenced by pore-water infiltration. At Jettan, twelve years of inclinometer data in boreholes reveal a transition from steady state to seasonal deformation in two shear zones. Since 2020, spring accelerations have intensified in years coinciding with deeper snowpacks and associated melt. These observations, together with statistical modeling, suggest that the shear-zones are becoming increasingly localized and sensitive to pore-water pressure. Conversely, autumn acceleration is not seen in localized shear zones but manifests as distributed volumetric deformation. Seismic velocity variations within the landslide body also exhibit seasonal patterns that correspond with geodetic velocity, interpreted as changes in landslide rigidity due to water infiltration. This integrated analysis of surface and subsurface data offers new insights into the evolving deformation of Arctic landslides, emphasizing the influence of hydrological forcings on both seasonal and long-term deformation processes.

During earthquakes, a high degree of spatial variation in damage distribution, encompassing both structural damage to buildings and co-seismic landslides, is commonly observed in mountainous regions near the seismic source. Among other factors, this spatial variability can be partly attributed to the amplification of seismic waves caused by surface topography. Our study focuses on predicting ground-motion amplification due to topography in close proximity to earthquakes and examining its potential influence on co-seismic landslide distribution patterns. To achieve this goal, we employ neural network analysis on previously available synthetic data from 3D finite-differences simulations of seismic wave propagation. The analysis aims at developing a physics-based estimator of topographic site effects in close distances to the source, referred to as the i-FSC proxy (Illuminated Frequency Scaled Curvature). This proxy depends on the S-wavelength, the curvature of the topographic surface, and a new parameter called the "normalized seismic illumination angle", which quantifies the slope's exposure to the incoming wavefield. The inclusion of the illumination parameter substantially decreases the uncertainties of the proxy by a factor of 2 compared to estimators that rely solely on curvature as a key parameter. The i-FSC proxy is a user-friendly tool that does not require high computational resources; it utilizes only a digital elevation map and the position of the seismic source to predict amplification factors at any point on the surface topography. This estimator allows exploring the spatial variations in topographic amplification caused by nearby seismic sources, representing a significant breakthrough as areas closest to the fault typically sustain the most damage during earthquakes. Subsequently, the i-FSC proxy is used to investigate the correlation between ground-motion amplification and the spatial distribution of earthquake-induced landslides triggered by large events such as the 2015 Gorkha earthquake (MW 7.8). The results indicate that more than 71% of co-seismic landslides tend to be localized in amplified areas. Different physical controls on the landslide triggering at different frequencies have been identified. The results also highlight the crucial importance of considering the effect of topographic amplification, together with other classical factors such as slope steepness, for a better understanding of the complex mechanisms governing the spatial distribution of earthquake-induced landslides at local and regional scales. The obtained results could provide valuable insights for future researches, guiding efforts towards more effective risk assessment and mitigation strategies in mountainous regions.

Rock glacier velocity is now widely acknowledged as an Essential Climate Variable for permafrost. However, representing decadal regional spatiotemporal velocity patterns remains challenging due to the limited availability of high-resolution (<5 m) remote sensing data. In contrast, medium-resolution satellite data (10–15 m) covering several decades are globally available but have not been widely used for rock glacier kinematics. This study presents a robust methodological approach combining pairwise feature-tracking image correlation with medium-resolution Landsat 7/Landsat 8 optical imagery, surface displacement time-series inversion and the automatic detection of persistent moving areas (PMAs). Applied to rock glacier monitoring in the semiarid Andes of South America, this methodology enables the detection and quantification of the surface kinematics of 153 rock glaciers, 124 landslides and 105 unclassified landforms over 24 years across a 2250 km2 area. This is the first time that Landsat images have been used to quantify rock glacier displacement time series. The study estimates an average velocity of 0.30±0.07 m yr−1 for all PMAs, with rock glaciers moving 23 % faster (0.37 m yr−1) over the 24-year period. Some large rock glaciers and debris-frozen landforms exhibit surface velocities exceeding 2 m yr−1. The results align well with high-resolution imagery, recent Global Navigation Satellite System measurements and previous inventories. However, the Landsat 7/Landsat 8 (L7/8) imagery-derived velocities are underestimated by approximately 20 %–30 % on average. High uncertainties between consecutive image pairs limit the reliability of interpreting annual velocity variations. However, decadal velocity changes exceeding the uncertainties were observed in only 2 % of PMAs, with two (one) rock glaciers exhibiting significant acceleration (deceleration) over the past two decades. Our calculations show that decadal velocity changes <0.4 m yr−1 are generally within the uncertainty range when using L7/8 data, with sensitivity depending on the reference period. Despite these limitations, our results highlight the correlation between velocity trends and topographic parameters such as PMA size, orientation, slope and elevation. These relationships suggest that permafrost thaw may influence the occurrence of high-altitude landslides. Overall, this study demonstrates the feasibility of using medium-resolution optical satellite imagery for monitoring rock glacier velocity over several decades.

Our study focuses on predicting topographic amplification of ground motion in the near-source region, where seismic rays reach the free-surface at varying incidence angles. We rely on data from previous 3D numerical simulations conducted on a topographic relief with a homogeneous medium. First, using neural networks, we identify which key parameters, describing the geometric characteristics of the relief relative to the seismic source position, control ground motion amplification. Then, we determine the functional form that relates these parameters to the simulated amplifications. Subsequently, we conduct a regression study to develop a model of topographic amplification, referred to as the i-FSC proxy (Illuminated Frequency-Scaled Curvature). Our estimator depends on the frequency-scaled (1) curvature, a parameter that accounts for the occurrence of amplifications over convex topographies and de-amplification over concave ones; (2) normalized illumination angle, a newly defined parameter that quantifies the slope exposure to the incoming wavefield, accounting for high amplification on slopes oriented opposite to the seismic source. The illumination parameter reduces the uncertainties of the proxy by a factor of 2 compared to estimators that rely solely on curvature. The proxy does not require high computational resources. It uses a digital elevation map and a seismic source position to predict amplification factors (without lithological effects) for an S-wave at any site on the surface topography. It allows exploration of variations in topographic amplification near seismic sources, representing a significant breakthrough as areas closest to the fault typically sustain the highest damages. A MATLAB script performing the i-FSC calculations is provided.

Landslides pose a significant hazard worldwide. Despite advances in landslide monitoring, predicting their size, timing, and location remains a major challenge. We revisit the 2017 Mud Creek landslide in California using radar interferometry, pixel tracking, and elevation change measurements from satellite and airborne radar, lidar, and optical data. Our analysis shows that pixel tracking of optical imagery captured the transition from slow motion to runaway acceleration starting ~ 1 month before catastrophic failure—an acceleration undetected by satellite InSAR alone. Strain rate maps revealed a new slip surface formed within the landslide body during acceleration, likely a key weakening mechanism. Failure forecast analysis indicates the acceleration followed a hyperbolic trend, suggesting failure time could have been predicted at least 6 days in advance. We also inverted for the landslide thickness during the slow-moving phase and found variations from < 1 to 36 m. While thickness inversions provide important first-order information on landslide size, more work is needed to better understand how landslide subsurface properties and deforming volumes may evolve during the transition from slow-to-fast motion. Our findings underscore the need for integrated remote sensing techniques to improve landslide monitoring and forecasting. Future advancements in operational monitoring systems and big data analysis will be critical for tracking slope instability and improving regional-scale failure predictions.

The steep Himalayan slopes are highly exposed to landslides, primarily triggered by earthquakes and monsoon intense precipitation. Along the Himalayan southern slopes, a specific landslide type involves old slided hillslope, characterized by intense internal fracturing, and prone to rapid retrogressive erosion through deep gullies incision, ultimately leading to catastrophic collapse of secondary landslides. Anticipating such events requires understanding if subsiding slices at the edge of the deeply incised talweg exhibit signs of acceleration preceding their rapid collapse and establishing a potential relationship between triggering factors (such as rain) and displacement amplitude. While optical images are commonly used for rapid landslides (with displacements superior to 20 cm/yr), their effectiveness is hindered by cloud cover during monsoon period, limiting sampling frequency and impeding the identification of transient deformation signals.In this study, we integrated satellite-based optical and radar remote sensing data with high spatial and temporal resolution to characterize the dynamics of a slow-moving landslide located in the Marsyandi valley (84.418° E ; 28.411° N ; 1900m a.s.l.) in Nepal, and to understand how it responds to monsoon rainfall. We developed a processing chain to apply sub-pixel image correlation to a data set comprising spotlight TerraSAR-X and PAZ radar images (1m spatial resolution), as well as medium resolution Sentinel-2 (10m), and high-resolution Pleiades (1m) amplitude optical images. We derived time series of ground displacements in range, azimuth, east-west, and north-south directions. Vertical displacements were additionally produced by comparing high-resolution Digital Surface Models (DSM) obtained from tri-stereo Pleiades images. The displacement time series revealed metric transient ground displacements in the upper part of the landslide at the end of the monsoon, along with linear displacements in downstream gullies. Field observations validated our satellite measurements, indicating that during the monsoon, the south-eastern part of the landslide remained relatively stable and revegetated, while the north-western part experienced downward sliding. By comparing these displacements with precipitation data, we characterized the response of the slow-moving landslide to seasonal forcing and gained insights into the mechanisms of collapsed hillslopes.

Rock glacier velocity is increasingly recognised as a critical essential climatic variable (ECV) for monitoring permafrost dynamics. However, the representation of decadal regional spatio-temporal velocity patterns remains challenging due to the scarcity of high resolution (

Les glissements de terrain lents sont des objets géomorphologiques qui se déplacent à des vitesses allant de mm/an à plusieurs m/an. Bien qu’ils soient trop lents pour faire des victimes, ces mouvements de terrain peuvent être précurseurs de mouvements plus rapides pouvant avoir des conséquences catastrophiques. La télédétection par satellite s’est avérée très utile pour détecter et surveiller les glissements de terrain lents dans des zones étendues et parfois éloignées. Le lancement de plusieurs générations de satellites au cours des 20 dernières années, avec de très hautes résolutions et des fréquences de revisite élevées, et le développement de techniques InSAR et de corrélation d’images appliquées à la fois aux images optiques et SAR nous ont permis de surmonter certains des défis posés par ces objets, qui sont à la fois petits et cinématiquement variables dans le temps. Ces nouvelles données et méthodes ont permis de mesurer précisément les déplacements de glissements de terrain à évolution lente avec différents objectifs : détection, surveillance, caractérisation et compréhension des processus physiques sous-jacents. Dans ce chapitre, nous passons en revue ces méthodes et leurs applications.

Abstract. The importance of monitoring rock glacier dynamics is now widely acknowledged within the scientific community following the designation of rock glacier velocity as a parameter of the Essential Climatic Variable permafrost. However, the representation of long-term spatio-temporal patterns of rock glaciers velocity at regional scale remains challenging due to the unavailability of high-resolution remote sensing datasets. This study presents a robust methodological approach based on the redundancy of information, joint with the inversion of surface displacement time series and the automatic detection of persistent moving areas (PMA) applied to rock glacier monitoring, using annual open-access, medium-resolution Landsat 7/8 optical imagery. This methodology enables the detection, quantification and analysis of surface kinematics of 382 gravitational slope movements over a 24-years, of which 153 corresponds to rock glaciers. This is the first time that Landsat images were used to quantify rock glacier displacements and derived velocities. The results demonstrate an average velocity of 0.37 ± 0.07 m y-1 overall 24-year for all rock glaciers, with some exceptions where large rock glaciers and debris frozen landform exhibit surface velocities exceeding 2 m y-1. The results of this study shows a good agreement with high-resolution imagery and recent GNSS measurements. L7/8 imagery tends to underestimate surface velocity by approximately 10–20 %. The intrinsic limitations of Landsat imagery make it challenging to interpret annual velocity variations. Notwithstanding, decadal velocity changes can be depicted for the fastest and largest rock glaciers, revealing 10 % of the accelerations in one decade. Our study suggests a correlation between surface velocity and local topographic parameters (orientation, slope, elevation) as possible controlling factors. In conclusion, this study demonstrates the feasibility of using medium-resolution optical imagery, providing an alternative to InSAR, for monitoring rock glacier kinematics anywhere over the World.

Creeping landslides may fail catastrophically, posing significant threats to infrastructure and lives. Landslides weaken over time through rock mass damage processes that may occur by steady-state creep or transient accelerations of slip, called creep bursts. Creep bursts may control landslide stability by inducing short-term damage and strain localization. This study focuses on the & Aring;knes landslide in Norway, which moves up to 6 cm per year and could potentially trigger a large tsunami in the fjord below. An 11-year data set is compiled and analyzed, including kinematic, seismic, and hydrogeological data acquired at the landslide surface and in a series of boreholes. An annual average of two creep bursts with millimeter amplitude has been recorded within the shear zone in each borehole, accounting for approximately 11% of the total displacement. Creep bursts detected simultaneously in multiple boreholes are preceded by increased seismic activity and rising water pressure. However, most creep bursts are observed in only one or a few boreholes. These bursts often happen during seasonal high and low groundwater levels in autumn and spring, respectively, correlating with local peaks in water pressure. No such correlation is observed during summer. We propose that creep bursts can have different causes and hypothesize that rock degradation leads to some creep bursts independent of water pressure variations. In contrast, the largest creep bursts are correlated with variations in absolute water pressure or gradients of water pressure within the shear zone. Our findings emphasize the complexity of a dense data set requiring multiple mechanisms to explain creep burst dynamics.

Slow-creeping landslides may fail catastrophically, posing significant threats to infrastructure and lives. Landslides weaken over time through rock mass damage processes that may occur by slow steady-state creep or transient accelerations of slip, called creep bursts. Creep bursts may control landslide stability by inducing short-term damage and strain localization. This study focuses on the Åknes landslide in Norway, which moves up to 6 centimetres per year and could potentially trigger a large tsunami in the fjord lying below. Here, an eleven-year dataset is compiled and analyzed, including kinematic, seismic, and hydrogeological data acquired at the landslide surface and in a series of boreholes. Creep bursts with millimetre amplitude are detected in the landslide’s shear zone. An annual average of two creep burst events have been recorded within the shear zone in each borehole, accounting for approximately 11% of the total displacement. Creep bursts phased over multiple boreholes are preceded by increased seismic activity and water pressure increase. However, most creep bursts are observed in only one or a few boreholes. Creep bursts often occur during the seasonal high and low levels of groundwater, correlating with local peaks in water pressure, but no such correlation is observed during summer. We propose that on one side, the progressive wear of asperities leads to creep bursts being uncorrelated to water pressure changes. Conversely, enhanced stress corrosion causes creep bursts to correlate to water level fluctuations. Our findings offer unique insights into landslide mechanics, correlating shear zone dynamics with surface displacement and environmental parameters.

L’alpinisme est une pratique sportive qui dépend fortement des conditions des milieux physiques dans lesquels elle se développe. Les alpinistes doivent ainsi faire face à des aléas glaciaires et périglaciaires importants, tels que ceux qui affectent les deux principaux itinéraires d’ascension du mont Blanc (4808 m ; Alpes européennes occidentales) : les chutes de pierres dans le Grand Couloir de l’aiguille du Goûter sur la Voie Royale et les chutes de séracs sur le versant NNO du mont Blanc du Tacul sur l’itinéraire des Trois Monts. Les aléas dans ces deux secteurs ainsi que la fréquentation ont été mesurés grâce à un dispositif multicapteurs et à des acquisitions photographiques automatiques, respectivement. Sur le premier site, où l'on déplore une très forte accidentalité avec en moyenne 3,7 décès par an, 17 768 passages ont été comptabilisés au cours de l’été 2019 et 2 648 signaux sismiques ont été classés comme des chutes de pierres ayant affecté le Grand Couloir. Le risque de décès associé à ces chutes de pierres, dont la fréquence est dépendante des températures et de la présence d’eau liquide dans le terrain, serait de 1,7 × 10-4. Au Tacul, où en moyenne 0,6 décès se produit chaque année, 6 770 passages ont été relevés au cours de l’été 2017, ainsi que 31 chutes de séracs sans lien avec les températures. Le risque de décès y est de 8,3 × 10-5. L'aléa est également quantifié pour chacune des traces faites sur le versant glaciaire. Les résultats obtenus permettent de préciser les risques encourus par les alpinistes et de favoriser des stratégies de réduction des risques.

Introduction This repository contains the data used for the study of the slope instability of Achoma, Peru, described in Lacroix et al. (submitted). Specifically, the repository contains a time series of horizontal ground displacements, obtained from high frequency PlanetScope satellite between 2017 and 2020. It also contains two Digital Elevation Models, one from before the Achoma failure obtained with Pléaides stero images, and the other from just after the Achoma failure obtained with drone imagery. The data and methods used for the elaboration of this data repository are described in detail in Lacroix et al. (submitted). In this repository we also provide a short summary and overview of the data and methods used. Data A total of 79 PlanetScope scenes were used to produce the time series of horizontal horizontal ground displacements maps. Table 1 provides an overview of these data. Table1: Data used for the creation of this repository Application Platforms Acquisition dates Pre-failure DEM Pléiades 2017/05/13 Post-failure DEM Drone 2020/06/19 Horizontal ground displacement PlanetScope 79 scenes from 2017/11/27 to 2020/06/17 Methods The horizontal ground displacement maps, both along the NS and the EW directions (file names NSxxxxxxxx.tif and Ewxxxxxxxx.tif, where xxxxxxxx is the date in the format yyyymmdd) were created using the offset tracking methodology described in Bontemps et al. (2018), consisting of: (1) correlation of all the pairs of images using Mic-Mac (Rupnik et al., 2017), (2) masking the low correlation coefficient values (CC<0.7), (3) mosaicking correction, similar to stripe corrections (Bontemps et al., 2018), that we obtained by subtracting the median value of the stacked profile in the along-stripe direction, taking into account only stable areas, (4) least square inversion of the redundant system per pixel, weighted by the time separation between pairs (Bontemps et al., 2018), (5) correction of illumination effects (Lacroix et al., 2019), based on the 2 years of data between November 2017 and December 2019. The pre-failure DEM was computed from Ames Stereo Pipeline (Shean et al. 2016) and the methodology developed in (Lacroix, 2016) applied to the Pléiades stereo images (file name DEM_20170513_shifted_vertical2.tif ). The post-failure DEM was processed using the Structure from Motion-Multi View Stereo (SfM-MVS) methodology with the Agisoft Metashape Professional 1.5.5 software applied on 1824 pictures taken from the drone (file name Achoma_DEM_2020.06.20_UTM19S_50cm.tif ). Acknowledgements P.L. acknowledge the support from the French Space Agency (CNES) through the TOSCA, PNTS, and ISIS programs. Dataset attribution This dataset is licensed under a Creative Commons CC BY 4.0 International License. Dataset Citation Lacroix, P., Huanca, J., Angel, L., Taipe, E.: Data Repository: Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites. Dataset distributed on Zenodo: 10.5281/zenodo.7866962

Mountaineering is a sport highly dependent on the conditions of the physical environments in which it takes place. As a result, mountaineers have to deal with major glacial and periglacial hazards, such as those affecting the two main routes used to climb Mont Blanc (4808 m a.s.l.; Western European Alps): rockfalls in the Grand Couloir du Goûter on the Voie Royale and serac falls on the NNW slope of Mont Blanc du Tacul on the Trois Monts route. Hazards in these two sectors and the number of climbers were measured using a multi-sensor system and automatic photographic acquisition, respectively. On the first site, which has a very high accident rate with an average of 3.7 deaths per year, 17,768 passages were recorded during the summer of 2019 and 2,648 seismic signals were classified as rockfalls affecting the Grand Couloir. The average risk of death associated with these rockfalls, the frequency of which depends on temperatures and the presence of liquid water in the ground, is estimated at 1.7 × 10-4. At Tacul, where an average of 0.6 deaths occur each year, 6,770 passages were recorded during the summer of 2017, as well as 31 serac falls unrelated to temperatures. The risk of death is 8.3 × 10-5. The risk is also quantified for each track made on the glacier. The results obtained makes it possible to specify the risks experienced by climbers and to promote risk reduction strategies.

Most seismic risk assessment methods focus on estimating the damages to the built environment and the consequent socioeconomic losses without fully taking into account the social aspect of risk. Yet, human behaviour is a key element in predicting the human impact of an earthquake, therefore, it is important to include it in quantitative risk assessment studies. In this study, an interdisciplinary approach simulating pedestrians' evacuation during earthquakes at the city scale is developed using an agent-based model. The model integrates the seismic hazard, the physical vulnerability as well as individuals' behaviours and mobility. The simulator is applied to the case of Beirut, Lebanon. Lebanon is at the heart of the Levant fault system that has generated several Mw>7 earthquakes, the latest being in 1759. It is one of the countries with the highest seismic risk in the Mediterranean region. This is due to the high seismic vulnerability of the buildings due to the absence of mandatory seismic regulation until 2012, the high level of urbanization, and the lack of adequate spatial planning and risk prevention policies. Beirut as the main residential, economic and institutional hub of Lebanon is densely populated. To accommodate the growing need for urban development, constructions have almost taken over all of the green areas of the city; squares and gardens are disappearing to give place to skyscrapers. However, open spaces are safe places to shelter, away from debris, and therefore play an essential role in earthquake evacuation. Despite the massive urbanization, there are a few open spaces but locked gates and other types of anthropogenic barriers often limit their access. To simulate this complex context, pedestrians' evacuation simulations are run in a highly realistic spatial environment implemented in GAMA [1]. Previous data concerning soil and buildings in Beirut [2, 3] are complemented by new geographic data extracted from high-resolution Pleiades satellite images. The seismic loading is defined as a peak ground acceleration of 0.3g, as stated in Lebanese seismic regulations. Building damages are estimated using an artificial neural network trained to predict the mean damage [4] based on the seismic loading as well as the soil and building vibrational properties [5]. Moreover, the quantity and the footprint of the generated debris around each building are also estimated and included in the model. We simulate how topography, buildings, debris, and access to open spaces, affect individuals' mobility. Two city configurations are implemented: 1. Open spaces are accessible without any barriers; 2. Access to some open spaces is blocked. The first simulation results show that while 52% of the population is able to arrive to an open space within 5 minutes after an earthquake, this number is reduced to 39% when one of the open spaces is locked. These results show that the presence of accessible open spaces in a city and their proximity to the residential buildings is a crucial factor for ensuring people's safety when an earthquake occurs.

The estimation of seismic damages and debris at the urban scale-at a building-by-building level- is challenging for several reasons. First, commonly used methodologies for seismic damage estimation rarely take into account the local site effects, precisely at the building-level. Second, the available methods for debris estimation fail to estimate at the same time the quantity of debris generated per building according to its damage level and the distribution of the debris (extent and height) around buildings. Finally, the lack of comprehensive data on the building stock and the relevant building properties and their taxonomy further increases the complexity of assessing possible earthquake consequences at an urban scale. This paper addresses these challenges and proposes improvements to the assessment of seismic damages and debris from building-level simulations, along with the development of a 3D building model based on satellite images and heterogeneous data. These developments, applied to the city of Beirut, Lebanon, highlight the control of the site effects on the seismic damage's spatial distribution throughout the city and the large volume and extent of debris to be expected in the city for a strong earthquake.

Abstract Landslide time‐of‐failure prediction is crucial in natural hazards, often requiring precise measurements from in situ instruments. This instrumentation is not always possible, and remote‐sensing techniques have been questioned for detecting precursors and predicting landslides. Here, based on high frequency acquisitions of the PlanetScope satellite constellation, we study the kinematics of a large landslide located in Peru that failed in June 2020. We show that the landslide underwent a progressive acceleration in the 3 months before its failure, reaching at most 8 m of total displacement. The high frequency of satellite revisit allows us to apply the popular Fukuzono method for landslide time‐of‐failure prediction, with sufficient confidence for faster moving areas of the landslide. These results open new opportunities for landslide precursors detection from space, but also show the probable seldom applicability of the optical satellites for landslide time‐of‐failure prediction.

In the last few decades, InSAR has been used to identify ground deformation related to slope instability and to retrieve time series of landslide displacements. In some cases, retrospective retrieval of time series revealed acceleration patterns precursory to failure. This suggests that, the higher temporal sampling of new generation satellites, may indeed offer the opportunity to detect motion precursory to failure with viable lead time. However, the possibility to retrieve continuous time series over landslides is often impaired by factors such as unfavourable orientation or landcover and fast movements, which make phase unwrapping difficult if not, in certain cases, impossible. One way to retrieve precursors of destabilisation for landslides that present characteristics unfavourable to unwrapping and to time series inversion is to analyse in detail changes in successive interferograms in the phase domain in combination with interferometric coherence. We generated and analysed 102 Sentinel-1 interferograms, covering the period between April 2015 and February 2021, at high spatial resolution (8 and 2 looks in range and azimuth respectively) over the Achoma landslide in the Colca valley, Peru. This large, deep-seated landslide, covering an area of about 40 hectares, previously unidentified, failed on 18th June 2020, damming the Rio Colca and giving origin to a lake. We developed a method to analyse the changes through time of the unwrapped phase difference between a stable point and points within the landslide. In combination with this, we investigated patterns of coherence loss both within the landslide and in the surrounding area. We observed that, in the weeks prior to the landslide, there was an increase of the phase difference between a stable reference and points within the landslide, indicating an acceleration of the downslope displacements. In addition to that, seasonal coherence loss is seen both within the landslide and in the surrounding area, in correspondence with wet periods. However, we observed also significant, local coherence loss outlining the scarp and the southeastern flank of the landslide, intermittently in the years before failure, in periods in which coherence was overall higher. Moreover, we observe a sharp decrease in the ratio between the coherence within the landslide and in the surrounding area, roughly six months before the failure. This type of approach is promising with respect to the extraction of relevant information from interferometric data when the generation of accurate and continuous time series of displacements is hindered by the nature of landcover or of the landslide studied, such in the case of the Achoma landslide. The combination of key, relevant parameters and their changes through time obtained with this methodology may prove necessary for the identification of precursors over a wider range of landslides than with time series generation alone.