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The recent calving of Astrolabe Glacier on the Adélie Coast (East Antarctica) in November 2021 presents an opportunity to better understand the processes leading to ice tongue fracturing. To document the fractures and rift evolution that led to the calving, we used the archive of Sentinel-2 optical images to measure the ice motion and strain rates from 2017 to 2021. The long-term evolution of the Astrolabe ice tongue is mapped using airborne and satellite imagery from 1947 to November 2021. These observations are then compared with measurements of sea-ice extent and concentration. We show that calving occurs almost systematically at the onset of or during the melting season. Additionally, we observe a significant change in the periodicity of sea ice surrounding Astrolabe Glacier in the last decade (2011–2021) compared to previous observations (1979–2011), which has resulted in a change in the Astrolabe calving cycle. Indeed, one can observe a decrease in the duration of sea-ice-free conditions during the austral summers after 2011 in the vicinity of the glacier, which seems to have favoured spatial extension of the ice tongue. However, the analysis of strain rate time series revealed that the calving of November 2021 (20 km 2) occurred at the onset of sea-ice melting season but resulted from the glacier dislocation that took place suddenly in June 2021 in the middle of the winter. These observations indicate that while sea ice can protect and promote the spatial extension of a glacier ice tongue, its buttressing is not sufficient to inhibit rifting and ice fracturing. [ABSTRACT FROM AUTHOR]

On February 6, 2023, southern Türkiye was struck by two large earthquakes at 01:17 UTC (Mw=7.8, Pazarcık, Kahramanmaraş) and 10:30 UTC (Mw = 7.6, Elbistan, Kahramanmaraş), causing severe damage at the complex junction of the Dead Sea Fault (DSF), the Cyprus Arc and the East Anatolian Fault Zone (EAFZ). The ruptures propagated along several known strands of the southwestern termination of the EAFZ, the main Pazarcık and Karasu valley faults, and the Çardak-Sürgü fault. Here we present the high-resolution mapping of the entire coseismic surface rupture and an estimate of the rupture width, total and on-fault offset, and diffuse deformation obtained a few days to three months after the two mainshocks. The mapping is derived from image correlation of Sentinel-2 optical satellite imagery and validated with offset measurements collected on the ground. We find that the ruptures extend over lengths of 310 km and 140 km for the Mw 7.8 and Mw 7.6 mainshocks, respectively. The maximum offsets reach 7.5 ± 0.8 m and 8.7 ± 0.8 m near the epicenters of the Mw 7.8 and Mw 7.6 events, respectively. We propose a segmentation of the two ruptures based on these observations, and further discuss the location of the potential supershear rupture. The use of optical image correlation, complemented by field investigations along earthquake faults, provides new insights into seismic hazard assessment. [ABSTRACT FROM AUTHOR]

Monitoring the endogenous seismicity of volcanoes helps to forecast eruptions and prevent their related risks, and also provides critical information on the eruptive processes. Due the high number of events recorded during pre-eruptive periods by the seismic monitoring networks, cataloging each event can be complex and time-consuming if done by human operators. Automatic seismic signal processing methods are thus essential to build consistent catalogs based on objective criteria. We evaluated the performance of the “Random Forests” (RF) machine-learning algorithm for classifying seismic signals recorded at the Piton de la Fournaise volcano, La Réunion Island (France). We focused on the discrimination of the dominant event types (rockfalls and volcano-tectonic earthquakes) using over 19,000 events covering two time periods: 2009–2011 and 2014–2015. We parametrized the seismic signals using 60 attributes that were then given to RF algorithm. When the RF classifier was given enough training samples, its sensitivity (rate of good identification) exceeded 99%, and its performance remained high (above 90%) even with few training samples. The sensitivity collapsed when using an RF classifier trained with data from 2009 to 2011 to classify data from 2014 to 2015 catalog, because the physical characteristics of the rockfalls and hence their seismic signals had evolved between the two time-periods. The main attribute families (waveform, spectrum, spectrogram or polarization) were all found to be useful for event discrimination. Our work validates the performance of the RF algorithm and suggests it could be implemented at other volcanic observatories to perform automatic, near real-time, classification of seismic events. [ABSTRACT FROM AUTHOR]

Measuring terrain deformation over several spatial and temporal scales is relevant for many applications in Earth Sciences (i.e. active faults, volcanoes, landslides or glaciers understanding). The growing volume of freely available data represents nowadays a challenge in terms of storage capacity and computing resources which, together with the complexity of the processing (code parameterization, combination of the image sequences, co-registration of the images) may prevent the exploitation of long time series. We propose here a new version of the Multiple-Pairwise Image Correlation toolbox for processing OPTical images (MPIC-OPT). The toolbox proposes an end-to-end solution to compute the horizontal sub-pixel ground deformation time series from large Sentinel-2 datasets. In addition to time series inversion, several corrections and filtering options are integrated to reduce the noise and improve the accuracy and precision of the measurements. In particular, an automatic jitter correction based on wavelet filtering is proposed. Moreover, the MPIC-OPT service is deployed on the Tier 1.5 High-Performance Computing cluster (e.g. Datacentre/EOST-A2S) of the University of Strasbourg and is accessible on-line through the ESA Geohazards Exploitation Platform (GEP) and the ForM@Ter Solid Earth computing infrastructure with a user-friendly environment to query the satellite data catalogues, parameterize the processing and visualize the outputs. We test the performances of MPIC-OPT on several use cases: the measurement of the co-seismic ground deformation of the 2019 Ridgecrest earthquake sequence (USA), of the rapid motion of the Slumgullion landslide (USA) and of the glaciers of the Mont-Blanc massif (France/Italy). We show that the results of MPIC-OPT are in agreement with in-situ data. The jitter correction significantly improves the precision (RMSE jitter =0.3 m vs. RMSE nojitter =0.5 m) and the accuracy (RMSE jitter =0.3 m vs. RMSE nojitter =1.3 m) of the measurement of the co-seismic displacement of the Rigdecrest seismic deformation. We show that the precision and accuracy of the terrain deformation estimation depend mainly on the correlation threshold and the temporal matching range parameters and we quantify and discuss their impacts. This work opens new perspectives to monitor automatically surface displacements/velocities of natural hazards over large scales and large periods of time. [Display omitted] [ABSTRACT FROM AUTHOR]

The "Pas de l’Ours" landslide, located in the Queyras valley (Southeast France) reactivated inthe Spring 2017. The total moving mass is estimated at 17 million cubic meters, with a widthof 1 km and a length of 600 m, which makes it currently one of the largest active landslides inthe French Alps. In addition to the large deforming mass, numerous rockfalls and mudflowshave occurred and have severely damaged the road that is located at the foot of thelandslide. Ground-based instruments including Ground-based radar (GBSAR), GPS, andseismometers have been deployed on-site to monitor the landslide evolution. In addition, weare monitoring the landslide motion using SAR and optical data from the Sentinel-1 (S1) and-2 (S2) satellites. These datasets are processed separately: a) the Sentinel-1 (ascending anddescending) data are processed with the InSAR Scientific Computing Environment (ISCE), b)the Sentinel-2 are processed by Multiple-Pair Image Correlation (MPIC) and c) the GBSARdata are processed with IBIS Guardian, a persistent scatterer interferometry algorithm. Theanalysis of the landslide deformation pattern measured by the different techniques shows thatthe landslide is undergoing periods of rapid acceleration (> 0.5 m.d−1) and deceleration(m.yr−1). These complementary datasets are exploited to invert for the 3D surface displacement fora small section of the landslide where all three datasets overlap using a Weighted LeastSquare (WLS) inversion. The retrieved 3D displacements are compared to GNSS datasets atthree different locations. Our work highlights how complementary monitoring techniques canbe combined to retrieve the evolution of slope instabilities with various kinematicregimes, and offers a new perspective into the physical processes controlling landslidedynamics. [ABSTRACT FROM AUTHOR]

Seismic monitoring of mass movements can significantly help to mitigate the associated hazards; however, the link between event dynamics and the seismic signals generated is not completely understood. To better understand these relationships, we conducted controlled releases of single blocks within a soft-rock (black marls) gully of the Rioux-Bourdoux torrent (French Alps). A total of 28 blocks, with masses ranging from 76 to 472 kg, were used for the experiment. An instrumentation combining video cameras and seismometers was deployed along the travelled path. The video cameras allow reconstructing the trajectories of the blocks and estimating their velocities at the time of the different impacts with the slope. These data are compared to the recorded seismic signals. As the distance between the falling block and the seismic sensors at the time of each impact is known, we were able to determine the associated seismic signal amplitude corrected for propagation and attenuation effects. We compared the velocity, the potential energy lost, the kinetic energy and the momentum of the block at each impact to the true amplitude and the radiated seismic energy. Our results suggest that the amplitude of the seismic signal is correlated to the momentum of the block at the impact. We also found relationships between the potential energy lost, the kinetic energy and the seismic energy radiated by the impacts. Thanks to these relationships, we were able to retrieve the mass and the velocity before impact of each block directly from the seismic signal. Despite high uncertainties, the values found are close to the true values of the masses and the velocities of the blocks. These relationships allow for gaining a better understanding of the physical processes that control the source of high-frequency seismic signals generated by rockfalls. [ABSTRACT FROM AUTHOR]

We conducted controlled releases of single blocks within a soft-rock (black marls) gully of the Rioux Bourdoux torrent (French Alps). 28 blocks, with masses ranging from 76 kg to 472 kg, were used for the experiment. An instrumentation combining video cameras and seismometers was deployed along the traveled path. The video cameras allow to reconstruct the trajectories of the blocks and to estimate their velocities at the time of the different impacts with the slope. These data are compared to the recorded seismic signals. As the distance between the falling block and the seismic sensors at the time of each impact is known, we were able to determine the associated seismic signal amplitude corrected from propagation and attenuation effects. We compared the velocity, the loss of potential energy, the kinetic energy and the momentum of the block at each impact to the true amplitude and the energy of the corresponding part of the seismic signal. Our results suggest that the amplitude of the seismic signal scales with the momentum of the block at the impact. We also found a scaling law between the potential energy lost, the kinetic energy and the energy of the seismic radiation generated by the impacts. By combining these scaling laws, we inferred the mass and the velocity before impact of each block directly from the seismic signal. Despite high uncertainties, the values found are close to the true values of the mass and the velocities of the blocks. These relationships also provide new insights to understand the source of high-frequency seismic signals generated by rockfalls. [ABSTRACT FROM AUTHOR]