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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.

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.

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.

The amount of sediments transported by a river is difficult to estimate, while this parameter could influence channel geometry. It is possible to derive the bedload transport rate per unit width of the river channel by measuring the migration distance of bedform profiles over time and thickness of bedload layer in motion. Other possible methods include instrumental measurements using bedload traps and empirical formulas. It is possible to use remote-sensing techniques to measure the dynamics of bedform movements and geometries. Landsat images and aerial photographs have been used for this. A new source of remote-sensing information is radar satellite images. Sentinel-1 images have a temporal resolution of 2–3 days and spatial resolution of 25 m at middle latitudes, which make them usable on large rivers. The research area is the 814–820 km reach of the Lower Vistula River, where seven alternate sandbars were selected. The bank lines of the sandbars were delineated on Sentinel-1 images sensed during two low-flow periods of 4 August–26 September 2018 and 1 July–31 August 2019, when discharges at low flow were similar. From water stage observations at gauges, water elevations were assigned to every bank line of the alternate sandbars. The following morphometric parameters were calculated: alternate sandbar centers, volumes and longitudinal profile. Average daily movement of the sandbars in the period 4 August 2018–1 July 2019 was calculated as 0.97 m·day−1. A similar alternate sandbar movement velocity was obtained from a study of Sentinel-2 optical satellite images and hydro-acoustic measurements on the Lower Vistula River. Having depth of bedload in motion and alternate sandbar shift velocities, it was possible to calculate the rate of bedload transport according to the Exner approach formula. Rate of bedload transport was estimated as qb = 0.027 kg·s−1·m−1. This study shows a novel use of Sentinel-1 images to study the 3D geometry and movement rate of sandbars.

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.

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 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.

In the last few decades, with the progress of science and the variety of optical and radar satellites, it has become possible to monitor and classify crops on a large scale. However, one of the main challenges in satellite imagery classification is the number of required training samples. Therefore, this study has been conducted to investigate the relationship between the training sample size and the classification accuracy of rice and non-rice covers. For this purpose, Sentinel-1 and Sentinel-2 images, Random Forest classifier (RF), and Google Earth Engine were used. In total, 2,500 rice samples and 9,500 non-rice samples were prepared in the study area, and 100 different runs were performed with varying training sample sizes. The results showed that the backscatter time series of Sentinel-1 images make it possible to distinguish rice from non-rice covers with high accuracy. So, the inputs to the Random Forest classifier included the Backscatter Slope (BS), the Backscatter Difference (BD) between the maximum and minimum values of the time series, and the Normalized Difference Vegetation Index (NDVI). According to the results, there is a non-linear relationship between the increase in the training sample size and the classification accuracy i.e., the accuracy decreases with the increase in the number of samples. The highest overall accuracy and kappa coefficient were obtained using 50% of the training samples. Therefore, with this sample size, the rice cultivation map was determined and the rice and non-rice areas were obtained 158,384 ha and 2,225,816 ha, respectively. The highest overall accuracy (89%) and kappa coefficient (0.86) were obtained when one training sample per 181 ha of rice fields and one training sample per 669 ha of non-rice cover were used. By doubling the number of samples, the kappa coefficient and overall accuracy were 0.84 and 87%, respectively. Finally, according to the results, increasing the number of training samples does not necessarily increase the classification accuracy.

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.

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.