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The Pope, Smith, and Kohler glaciers, in the Amundsen Sea Embayment of West Antarctica, have experienced enhanced ocean-induced ice-shelf melt, glacier acceleration, ice thinning, and grounding line retreat in the past thirty years. Here we present observations of the grounding line retreat of these glaciers since 2014 using a constellation of interferometric radar satellites combined with precision surface elevation data. We find that the grounding lines develop spatially-variable, kilometre-scale, tidally-induced migration zones. After correction for tidal effects, we detect a sustained pattern of retreat coincident with high melt rates of un-grounded ice, marked by episodes of more rapid retreat. In 2017, Pope Glacier retreated 3.5 km in 3.6 months, or 11.7 km/yr. In 2016-2018, Smith West retreated at 2 km/yr and Kohler at 1.3 km/yr. While the retreat slowed down in 2018-2020, these retreat rates are faster than anticipated by numerical models on yearly time scales. We hypothesize that the rapid retreat is caused by un-represented, vigorous ice-ocean interactions acting within newly-formed cavities at the ice-ocean boundary.

Sea-level measurements from radar satellite altimetry have reached a high level of accuracy and precision, which enables detection of global mean sea-level rise and attribution of most of the rate of rise to greenhouse gas emissions. This achievement is far beyond the original objectives of satellite altimetry missions. However, recent research shows that there is still room for improving the performance of satellite altimetry. Reduced uncertainties would enable regionalization of the detection and attribution of the anthropogenic signal in sea-level rise and provide new observational constraints on the water–energy cycle response to greenhouse gas emissions by improving the estimate of the ocean heat uptake and the Earth energy imbalance.Satellite radar altimetry enables the detection of sea-level changes by collecting data that have exceeded early expectations. This Perspective discusses potential advances that would enhance the data, allowing regional detection and attribution of sea-level change and improving ocean heat uptake estimates.

A continuously operating GNSS station within a lake interior is uncommon, but advantageous for testing the GNSS Interferometric Reflectometry (GNSS-IR) technique. In this research, GNSS-IR is used to estimate ten years of lake surface heights for Lake Taupō in New Zealand. This is achieved using data collected from station TGHO, approximately 4 km from the lake’s shoreline. Its reliability is assessed by comparisons with shoreline gauges and satellite radar altimetry lake surface heights. Relative RMS differences between the daily averaged lake gauge and GNSS-IR lake surface heights range from ± 0.027 to ± 0.028 m. Relative RMS differences between the satellite radar altimetry lake surface heights and the GNSS-IR lake surface heights are ± 0.069 m and ± 0.124 m. The results show that the GNSS-IR technique at Lake Taupō can provide reliable lake surface height estimates in a terrestrial reference frame. A new ground-based absolute satellite radar altimetry calibration/validation approach based on GNSS-IR is proposed and discussed.

Slope failures frequently occur in open-pit mines, resulting in significant losses. Identifying the precursory displacements and triggering factors for detecting unstable slopes is critical for reducing and preventing their impact. This study proposes combining satellite radar interferometry and infrared thermography with numerical simulation to determine unstable slopes in an open-pit mine. First, interferometric synthetic aperture radar (InSAR) is utilized to capture deformation information in a line-of-sight direction in terms of velocity to locate the long-time movement on a large scale. The application of infrared thermography enables the detection of peculiar features based on the different thermal patterns occurring along the slope and the interpretation of critical sectors matching with the instability zones highlighted by the InSAR. In particular, areas with various surface temperatures were associated with vegetated spots, new benches, bare sectors, and contact between different lithologies. By means of three-dimensional stability analyses, the associated interferometry movement confirmed the slope instability, and a critical failure surface was found using two-dimensional numerical simulation. The efficacy of the proposed approach is verified through a massive slope failure in the Qidashan open-pit mine in Liaoning, China. It predicts the slope failures caused by intense rainfall and reveals the progressive failure mechanism. The practical application has demonstrated the feasibility and accuracy of the proposed approach for detecting failure precursors, providing a novel procedure for remotely identifying critical slopes in an open-pit with frequent mining activity.

Using the images of the Sentinel-1A satellite, taken from May 1 to September 22, 2023, and the differential interferometry method (DInSAR) we calculated successive displacement fields in time, which clearly show a dome-shaped uplift on the western slope of Shiveluch volcano, 8‒8.5 km west of its active crater. The uplift grew especially intensely at the satellite acquisition intervals of May 1‒13, 2023; May 13‒25, 2023; and May 25‒June 6, 2023. To confirm the hypothesis on the formation of the displacement region due to magma intrusion beneath the western slope of the volcano, numerical modeling was carried out and the parameters of the sill-like magma body, which forms the displacements on the surface that best match the displacement observed from satellite radar interferometry data, were determined. It is assumed that, after the eruption on April 11, 2023, magma rose from a depth of 20‒25 km through a fissure formed under the western slope of the volcano and intruded horizontally beneath the slope at a depth of 1‒2 km in the north-northwesterly direction. Within the precision of data on slope displacements, the size of the magma body varies from 6.0 × 3.0 km at 1 km depth to 5.25 × 1.4 km at 2 km depth, while its height ranges from 0.5 to 1.75 m and its volume, from 0.009 to 0.0129 km 3 . Thus, based on radar interferometry data together with the data on the distribution of seismic activity accompanying the movement of magma, the model of the magma body that intruded beneath the western slope of Shiveluch volcano in the postparoxysmal phase of the eruption on April 11, 2023, was constructed. The formation of a new extrusive dome on the western slope of Shiveluch volcano at the end of April 2024 confirms the hypothesis about the intrusion of magmatic material beneath the western slope of the volcano and allows estimating the rate of magma rise to the surface.

Slope failures occur in open-pit mining areas worldwide, producing considerable damage in addition to economic loss. Identifying the triggering factors and detecting unstable slopes and precursory displacements —which can be achieved by exploiting remote sensing data— are critical for reducing their impact. Here we present a methodology that combines digital photogrammetry, satellite radar interferometry, and geo-mechanical modeling, to perform remote analyses of slope instabilities in open-pit mining areas. We illustrate this approach through the back analysis of a massive landslide that occurred in an active open-pit mine in southwest Spain in January 2019. Based on pre- and post-event high-resolution digital elevation models derived from digital photogrammetry, we estimate an entire sliding mass volume of around 14 million m3. Radar interferometry reveals that during the year preceding the landslide, the line of sight accumulated displacement in the slope reached − 5.7 and 4.6 cm in ascending and descending geometry, respectively, showing two acceleration events clearly correlated with rainfall in descending geometry. By means of 3D and 2D stability analyses we located the slope instability, and remote sensing monitoring led us to identify the likely triggers of failure. Las Cruces event can be attributed to delayed and progressive failure mechanisms triggered by two factors: (i) the loss of historical suction due to a pore-water pressure increase driven by rainfall and (ii) the strain-softening behavior of the sliding material. Finally, we discuss the potential of this methodological approach either to remotely perform post-event analyses of mining-related landslides and evaluate potential triggering factors or to remotely identify critical slopes in mining areas and provide pre-alert warning.

Ice shelves regulate the flow of the Antarctic ice sheet toward the ocean and its contribution to sea-level rise. Accurately monitoring the basal and surface melting of ice shelves is therefore essential for predicting the ice sheet's response to climatic warming. In this study, we utilize Sentinel-1A synthetic aperture radar satellite imagery combined with shipboard measurements of water temperature and salinity to investigate the presence of surficial meltwater plumes along the Antarctic coastline. Our approach reveals a strong correlation between areas of pronounced low radar backscatter extending from ice shelves and significant decreases in water temperature and salinity, suggesting meltwater-enriched ocean waters. We propose that the low radar backscatter signature of meltwater outflows is caused by stable stratification of the upper water column, driven by density contrasts from buoyant, low-salinity meltwater and surface current shear that reduce Bragg scattering waves. The resulting smooth water surfaces were observed adjacent to the surface expression of deep basal channels, documented in a helicopter survey along part of the Bellingshausen Sea ice edge. We present high-temporal resolution satellite radar as a tool for identifying meltwater release from beneath ice shelves, capable of all-weather, day-and-night imaging.

For the July 29, 2025 Mw 8.8 Kamchatka earthquake, a seismic rupture surface model is constructed and a displacement field on it is determined, using coseismic displacements at the stations of the Kamchatka GNSS network and a displacement map based on satellite radar interferometry data. The model consists of four rectangular segments, dipping at 8° in the upper part and 21° deeper than 20 km. The main displacements on the rupture surface up to 11.5 m are obtained in the area of the southern part of the Kamchatka Peninsula and near Shumshu and Paramushir islands. In the area of Avacha Bay, they are twice as small. Such a distribution of displacements on the seismic rupture is completely consistent with the available GNSS and InSAR data and with the height of tsunami waves. The average displacement on the rupture surface is 6.5 m, which corresponds to the displacement deficit accumulated since the recent major earthquake in this area in 1952. The comparison of the displacement fields on the rupture surface of the 2025 earthquake with the 1952 rupture surface model, constructed using the data of tsunamigenic deposits, shows that the displacements complement each other: where large displacements occurred in 1952, the displacements were smaller in 2025 and vice versa.

Information on the spatial distribution of triggered landslides following an earthquake is invaluable to emergency responders. Manual mapping using optical satellite imagery, which is currently the most common method of generating this landslide information, is extremely time consuming and can be disrupted by cloud cover. Empirical models of landslide probability and landslide detection with satellite radar data are two alternative methods of generating information on triggered landslides that overcome these limitations. Here we assess the potential of a combined approach, in which we generate an empirical model of the landslides using data available immediately following the earthquake using the random forest technique and then progressively add landslide indicators derived from Sentinel-1 and ALOS-2 satellite radar data to this model in the order they were acquired following the earthquake. We use three large case study earthquakes and test two model types: first, a model that is trained on a small part of the study area and used to predict the remainder of the landslides and, second, a preliminary global model that is trained on the landslide data from two earthquakes and used to predict the third. We assess model performance using receiver operating characteristic analysis and r2, and we find that the addition of the radar data can considerably improve model performance and robustness within 2 weeks of the earthquake. In particular, we observed a large improvement in model performance when the first ALOS-2 image was added and recommend that these data or similar data from other L-band radar satellites be routinely incorporated in future empirical models.

The paper presents the results of the processing of satellite radar images acquired by the TerraSAR-X satellite using the persistent scatterer method for analyzing the subsidence of the earth’s surface over potash mines in the city of Berezniki, Perm Krai. A sequence of processing procedures in the GAMMA Software package (Gamma Remote Sensing AG, Switzerland) is presented, which showed good results in the conditions of this territory. A comparison is made with the results obtained earlier by summation of interferograms. In contrast to the methods of persistent scatterers, the summation is performed without analyzing displacements in time. The noisy time series obtained by the summation are not rejected, so the displacement maps cover the study area more evenly. In the persistent scatterer method, the time series is analyzed using a variety of criteria, so the subsidence rates are estimated more reliably. In the areas where the results were obtained by summation and the persistent scatterer method, the subsidence rates are in good agreement. The persistent scatterer method has made it possible to estimate displacements in certain areas separated by vast incoherent woodlands, on which interferograms lose their coherence. At the same time, a new subsidence area was identified with an average rate of subvertical displacements up to 75 mm/year and, in some areas, up to 100 mm/year, which, according to data for 2020 and 2018, was not detected. The subsidence here should be clarified based on the images for subsequent years or using surface thechniques. The time series also show the deceleration of subsidence in spring on persistent scatterers located on buildings and infrastructure. We associate the total spring deceleration of subsidence by 3–5 cm not with underground but with seasonal factors, specifically with the heating of buildings in the spring. Other reasons are also possible, but the main one is that, in areas with a moderate subsidence rate, this effect can lead to some underestimation of the average subsidence rate. A detailed study of the time series for subsidence makes it possible to identify areas requiring special attention. Most of the subsidence occurs more or less evenly; in a significant part of the territory, the subsidence rate in 2021 has decreased. This indicates the effectiveness of the measures taken to protect the ground infrastructure. Within the city area, the acceleration of subsidence was found only at the beginning of Lenin Avenue. SAR interferometry is an effective tool for studying subsidence processes in the city of Berezniki. This method significantly complements geodetic works, since it provides data on vast areas that cannot be covered by detailed ground measurements. In addition, part of the closed territories becomes dangerous for ground works, so there is no alternative to satellite technologies.