Search Results (61)

As a heavily glaciated region, the Eastern Pamir plays a crucial role in regional water supply. However, considerable ambiguity surrounds the distribution of glacier ice thickness and the details of ice volume. Accurate data at the local scale are largely insufficient. In this study, ground-penetrating radar (GPR) was applied to assess the ice thickness at Muztagh Glacier No.16 (MG16) in Muztagh Ata, Eastern Pamir, for the first time, detailing findings from four distinct profiles, bridging the gap in regional measurements. We utilized a total of five different methods based on basic shear stress, surface velocity, and mass conservation, aimed at accurately delineating the ice volume and distribution for MG16. Verification was conducted using measured data, and an aggregated model outcome provided a unified view of ice distribution. The different models showed good agreement with the measurements, but there were differences in the unmeasured areas. The composite findings indicated the maximum ice thickness of MG16 stands at 115.87 ± 4.55 m, with an ice volume calculated at 0.27 ± 0.04 km³. This result is relatively low compared to the findings of other studies, which lies in the fact that the GPR measurements somewhat constrain the model. However, the model parameters remain the primary source of uncertainty. The results from this study can be used to enhance water resource assessments for future glacier change models. Full article

TanDEM-X bistatic interferometric system successfully generated a high-precision, high-resolution global digital elevation model (DEM). However, in forested areas, two core problems make it difficult to obtain sub-canopy topography: (1) the penetrability of short-wave signals is limited, and the DEM obtained in dense forest areas contains a significant forest signal, that is, the scattering phase center (SPC) height; and (2) the single-baseline and single-polarization TanDEM-X interferometric synthetic aperture radar (InSAR) data cannot provide sufficient observations to make the existing physical model reversible for estimating the real surface phase, whereas the introduction of optical data makes it difficult to ensure data synchronization and availability of cloud-free data. To overcome these problems in accurately estimating sub-canopy topography from TanDEM-X InSAR data, this study proposes a practical method of sub-canopy topography estimation based on the following innovations: (1) An orthogonal polynomial model was established using TanDEM-X interferometric coherence and slope to estimate the SPC height. Interferometric coherence records forest height and dielectric property information from an InSAR perspective and has spatiotemporal consistency with the InSAR-derived DEM. (2) Introduce Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) data to provide more observational information and automatically screen ICESat-2 control points with similar forest and slope conditions in the local area to suppress forest spatial heterogeneity. (3) A weighted least squares criterion was used to solve this model to estimate the SPC height. The results were validated at four test sites using high-precision airborne light detection and ranging (LiDAR) data as a reference. Compared to the InSAR-derived DEM, the accuracy of the sub-canopy topography was improved by nearly 60%, on average. Furthermore, we investigated the necessity of local modeling, confirming the potential of the proposed method for estimating sub-canopy topography by relying only on TanDEM-X and ICESat-2 data. Full article

Ice thickness has a significant effect on the physical and biogeochemical processes of a lake, and it is an integral focus of research in the field of ice engineering. The Qinghai–Tibetan Plateau, known as the Third Pole of the world, contains numerous lakes. Compared with some information, such as the area, water level, and ice phenology of its lakes, the ice thickness of these lakes remains poorly understood. In this study, we used an unmanned aerial vehicle (UAV) with a 400/900 MHz ice-penetrating radar to detect the ice thickness of Qinghai Lake and Gahai Lake. Two observation fields were established on the western side of Qinghai Lake and Gahai Lake in January 2019 and January 2021, respectively. Based on the in situ ice thickness and the propagation time of the radar, the accuracy of the ice thickness measurements of these two non-freshwater lakes was comprehensively assessed. The results indicate that pre-processed echo images from the UAV-borne ice-penetrating radar identified non-freshwater lake ice, and we were thus able to accurately calculate the propagation time of radar waves through the ice. The average dielectric constants of Qinghai Lake and Gahai Lake were 4.3 and 4.6, respectively. This means that the speed of the radar waves that propagated through the ice of the non-freshwater lake was lower than that of the radio waves that propagated through the freshwater lake. The antenna frequency of the radar also had an impact on the accuracy of ice thickness modeling. The RMSEs were 0.034 m using the 400 MHz radar and 0.010 m using the 900 MHz radar. The radar with a higher antenna frequency was shown to provide greater accuracy in ice thickness monitoring, but the control of the UAV’s altitude and speed should be addressed. Full article

The planet Mars is the most probable among the terrestrial planets in our solar system to support human settlement or colonization in the future. The detection of water ice or liquid water on the shallow subsurface of Mars is a crucial scientific objective for both the Chinese Tianwen-1 and United States Mars 2020 missions, which were launched in 2020. Both missions were equipped with Rover-mounted ground-penetrating radar (GPR) instruments, specifically the RoPeR on the Zhurong rover and the RIMFAX radar on the Perseverance rover. The in situ radar provides unprecedented opportunities to study the distribution of shallow subsurface water ice on Mars with its unique penetrating capability. The presence of water ice on the shallow surface layers of Mars is one of the most significant indicators of habitability on the extraterrestrial planet. A considerable amount of evidence pointing to the existence of water ice on Mars has been gathered by previous researchers through remote sensing photography, radar, measurements by gamma ray spectroscopy and neutron spectrometers, soil analysis, etc. This paper aims to review the various approaches utilized in detecting shallow subsurface water ice on Mars to date and to sort out the past and current evidence for its presence. This paper also provides a comprehensive overview of the possible clues of shallow subsurface water ice in the landing area of the Perseverance rover, serving as a reference for the RIMFAX radar to detect water ice on Mars in the future. Finally, this paper proposes the future emphasis and direction of rover-mounted radar for water ice exploration on the Martian shallow subsurface. Full article

Planetary radar observations have provided invaluable information on the solar system through both ground-based and space-based observations. In this overview article, we summarize how radar observations have contributed in planetary science, how the radar technology as a remote-sensing method for planetary exploration and the methods to interpret the radar data have advanced in the eight decades of increasing use, where the field stands in the early 2020s, and what are the future prospects of the ground-based facilities conducting planetary radar observations and the planned spacecraft missions equipped with radar instruments. The focus of the paper is on radar as a remote-sensing technique using radar instruments in spacecraft orbiting planetary objects and in Earth-based radio telescopes, whereas ground-penetrating radar systems on landers are mentioned only briefly. The key scientific developments are focused on the search for water ice in the subsurface of the Moon, which could be an invaluable in situ resource for crewed missions, dynamical and physical characterization of near-Earth asteroids, which is also crucial for effective planetary defense, and a better understanding of planetary geology. Full article

Gigantic aufeis fields serve as indicators of water exchange processes within the permafrost zone and are important in assessing the state of the cryosphere in a changing climate. The Anmangynda aufeis, located in the upstream of the Kolyma River basin, is present in the mountainous regions of Northeast Eurasia. Recent decades have witnessed significant changes in aufeis formation patterns, necessitating a comprehensive understanding of cryospheric processes. The objective of the study, conducted in 2021–2022, was to examine the structure of the Anmangynda aufeis and its glade, aiming to understand its genesis and formation processes. The tasks included identifying above- and intra-frozen taliks, mapping groundwater (GW) discharge channels, determining permafrost base depth, and assessing ice thickness distribution. Soundings using ground-penetrating radar (GPR), capacitively coupled electrical resistivity tomography (CCERT), and the transient electromagnetic (TEM) method were employed. GW discharge channels originating from alluvial deposits and extending to the aufeis surface within river channels were identified through GPR and verified through drilling. Deep-seated sources of GW within the bedrock were inferred. CCERT data allowed us to identify large and localized frozen river taliks, from which water is forced onto the ice surface. According to the TEM data, the places of GW outlets spatially coincide with the zones interpreted as faults. Full article

With global warming, Arctic sea ice, as one of the important factors regulating climate, has put forward new requirements for research. At present, the ground penetrating radar (GPR) is a powerful tool to obtain the structure of Arctic sea ice. Traditional offset imaging techniques no longer meet research requirements, and the two-parameter full waveform inversion (FWI) method has received widespread attention. To solve the high nonlinearity and ill-posed problem of FWI, the L-BFGS optimization algorithm and Wolfe criterion of inexact line search were used to update the model. The parameter scale factor, multiscale inversion strategy, and total variation (TV) regularization were introduced to optimize the inversion results. Finally, the inversion of anomalous bodies with different scales and different physical parameters is carried out, which verifies the reliability of the proposed method for dual-parameter imaging of Arctic sea ice and provides a powerful tool for the study of Arctic sea ice. Full article

Over the last two decades, spaceborne polarimetric synthetic aperture radar (PolSAR) has been widely used to penetrate sea ice surfaces to achieve fully polarimetric high-resolution imaging at all times of day and in a range of weather conditions. Model-based polarimetric decomposition is a powerful tool used to extract useful physical and geometric information about sea ice from the matrix datasets acquired by PolSAR. The volume scattering of sea ice is usually modeled as the incoherent average of scatterings of a large volume of oriented ellipsoid particles that are uniformly distributed in 3D space. This uniform spatial distribution is often approximated as a uniform orientation distribution (UOD), i.e., the particles are uniformly oriented in all directions. This is achieved in the existing literature by ensuring the canting angle $\phi$ and tilt angle $\tau$ of particles uniformly distributed in their respective ranges and introducing a factor $\cos \tau$ in the ensemble average. However, we find this implementation of UOD is not always effective, while a real UOD can be realized by distributing the solid angles of particles uniformly in 3D space. By deriving the total solid angle of the canting-tilt cell spanned by particles and combining the differential relationship between solid angle and Euler angles $\phi$ and $\tau$, a complete expression of the joint probability density function $p\left(\phi ,\tau \right)$ that can always ensure the uniform orientation of particles of sea ice is realized. By ensemble integrating the coherency matrix of $\left(\phi ,\tau \right)$-oriented particle with $p\left(\phi ,\tau \right)$, a generalized modeling of the volume coherency matrix of 3D uniformly oriented spheroid particles is obtained, which covers factors such as radar observation geometry, particle shape, canting geometry, tilt geometry and transmission effect in a multiplicative way. The existing volume scattering models of sea ice constitute special cases. The performance of the model in the characterization of the volume behaviors was investigated via simulations on a volume of oblate and prolate particles with the differential reflectivity $Z_{DR}$, polarimetric entropy $H$ and scattering α angle as descriptors. Based on the model, several interesting orientation geometries were also studied, including the aligned orientation, complement tilt geometry and reflection symmetry, among which the complement tilt geometry is specifically highlighted. It involves three volume models that correspond to the horizontal tilt, vertical tilt and random tilt of particles within sea ice, respectively. To match the models to PolSAR data for adaptive decomposition, two selection strategies are provided. One is based on $Z_{DR}$, and the other is based on the maximum power fitting. The scattering power that reduces the rank of coherency matrix by exactly one without violating the physical realizability condition is obtained to make full use of the polarimetric scattering information. Both the models and decomposition were finally validated on the Gaofen-3 PolSAR data of a young ice area in Prydz Bay, Antarctica. The adaptive decomposition result demonstrates not only the dominant vertical tilt preference of brine inclusions within sea ice, but also the subordinate random tilt preference and non-negligible horizontal tilt preference, which are consistent with the geometric selection mechanism that the c-axes of polycrystallines within sea ice would gradually align with depth. The experiment also indicates that, compared to the strategy based on $Z_{DR}$, the maximum power fitting is preferable because it is entirely driven by the model and data and is independent of any empirical thresholds. Such soft thresholding enables this strategy to adaptively estimate the negative $Z_{DR}$ offset introduced by the transmission effect, which provides a novel inversion of the refractive index of sea ice based on polarimetric model-based decomposition. Full article

After the formation of the bend ice cover, the ice thickness of the bend is not uniformly distributed, and an open-water area is usually formed downstream of the bend. The spatial and temporal variation of the ice thickness in seven cross sections was determined via Unmanned Aerial Vehicle Ground Penetrating Radar (UAV-GPR) technology and traditional borehole measurements. The plane morphology change of the open water was observed by Sentinel-2. The results show that the average dielectric permittivity of GPR was 3.231, 3.249, and 3.317 on three surveys (5 January 2022, 16 February 2022, and 25 February 2022) of the Yellow River ice growing period, respectively. The average ice thickness of the three surveys was 0.402 m, 0.509 m, and 0.633 m, respectively. The ice thickness of the concave bank was larger than that of the convex bank. The plane morphology of the open water first shrinks rapidly longitudinally and then shrinks slowly transversely. The vertical boundary of the open water was composed of two arcs, in which the slope of Arc I (close to the water surface) was steeper than that of Arc II, and the hazardous distance of the open-water boundary was 10.3 m. The increased flow mostly affected the slope change of Arc I. Finally, we discuss the variation of hummocky ice and flat ice in GPR images and the physical factors affecting GPR detection accuracy, as well as the ice-thickness variation of concave and convex banks in relation to channel curvature. Full article

In order to research the special embankment (thermosyphon embankment) damages and the distribution of permafrost under the Qinghai–Tibet Highway (QTH) embankment. The section K2952–K2953, which is a typical representative of the QTH, was chosen for the detection and research of the permafrost and embankment damages in order to determine the sources of the damages. In this study, the performance characteristics of the embankment, the active layer, and the permafrost table found in ground-penetrating radar (GPR) images were researched, combined with multi-source. According to the research findings, the construction of the embankment in this section has stabilized the effect on the permafrost table. Under the embankment of the unemployed thermosyphon section, the permafrost distribution has good structural integrity and continuity, with the permafrost table at a depth of around 5 m. The continuity of the permafrost distribution under the embankment in the thermosyphon section was poor, and there was localized degradation, with the permafrost table being approximately 6 m deep. The main cause of the irregular settlement and other damage in this section is the presence of a loose area at the base of the embankment. Although the thermosyphon on both sides of the embankment also plays a role in lifting the permafrost table, it is not ideal for managing the damage to high embankments where the type of permafrost under the embankment is high-temperature permafrost with a high ice content and where the sunny–shady slope effect is obvious. The research results described in this article can therefore provide a crucial foundation for the detection of highway damage and permafrost under embankments in permafrost regions in the future. Full article

Ice is a rich reservoir of past climate information, and the well-documented increasing rate of glacier retreat represents a great loss for paleoclimate studies. In this framework, the Ice Memory project aims to extract and analyze ice cores from glacier regions worldwide and store them in Antarctica as a heritage record for future generations of scientists. Ice coring projects usually require a focused geophysical investigation, often based on Ground Penetrating Radar (GPR) prospecting to assess the most suitable drilling positions. As a novel approach in the Calderone Glacieret, we integrated the GPR method with Frequency Domain Electromagnetic (FDEM) surveys, a technique not commonly applied in the glacial environment. We used a separated-coils FDEM instrument to characterize the glacieret structure. The acquired FDEM datasets were inverted and compared to the GPR data and borehole information. The results demonstrated the capability of the FDEM technique to define the structure of the glacieret correctly; therefore, the potential to be applied in frozen subsoil environments. This opens new perspectives for the use of the FDEM technique to characterize periglacial environments, such as rock glaciers, where the coarse-blocky surface hinders data acquisition and enhances the problem of signal scattering. Full article

Chang’E-7 will be launched around 2026 to explore resources at the lunar south pole. Glaciers are suitable scenes on the earth for lunar penetrating radar verification. In the verification experiment, ice-penetrating signals are inevitably polluted by noise, affecting the accuracy and reliability of glacier detection. This paper proposes a denoising method for ice-penetrating signals based on the combination of whale optimization algorithm (WOA), variational mode decomposition (VMD), and the improved Bhattacharyya distance (BD). Firstly, a fitness function for WOA is established based on permutation entropy (PE), and the number of decomposition modes K and the quadratic penalty factor $\alpha$ in the VMD are optimized using WOA. Then, VMD is performed on the signal to obtain multiple intrinsic mode functions (IMFs). Finally, according to the BD, the relevant IMFs are selected for signal reconstruction and denoising. The simulation results indicate the strengths of this method in enhancing the signal-to-noise ratio (SNR), and its performance is better than empirical mode decomposition (EMD). Experiments on the detected signals of the Mengke Glacier No. 29 indicate that the WOA-VMD-BD method can efficiently eliminate noise from the data and procure well-defined layered profiles of the glacier. The research in this paper helps observe the layered details of the lunar regolith profile and interpret the data in subsequent space exploration missions. Full article

Basal melt in the Dome A region will influence the deep-ice-core drilling at Kunlun Station. The melting point (wet bedrock) has a higher reflectivity than the surrounding area, which can be assessed using radar echoes from the bedrock. This paper uses a linear absorption model to determine wet and dry ice–bedrock interfaces around the Kunlun drilling site. In the determination process, an artificial intelligence model was applied to extract the ice–bedrock interface for inferring the ice thickness. Additionally, the various depth-averaged attenuation rates were used to identify the maximal range of basal melting. We mapped the patterns of the wet points on the bottom of the ice sheet and the modeled basal temperature to verify the results of the wet bed conditions. According to these maps of wet bed conditions, the areas with basal melting around the drilling site primarily appear in valley walls with low basal temperatures and are linked with hydraulic potential and bedrock elevation. Identifying the ice–bedrock interface is challenging in the valley bottom area, where the melting points are less than at the valley walls. Additionally, the melting proportions of 11.8% and 3.62% were calculated from two ice-penetrating radar data in this research. The mapped melting points around the site of Kunlun ice core drilling suggest complex ice flow effects and can be used to better interpret archives of old ice for paleoclimate research. Full article

Bed topography and roughness play important roles in numerous ice-sheet analyses. Although the coverage of ice-penetrating radar measurements has vastly increased over recent decades, significant data gaps remain in certain areas of subglacial topography and need interpolation. However, the bed topography generated by interpolation such as kriging and mass conservation is generally smooth at small scales, lacking topographic features important for sub-kilometer roughness. DeepBedMap, a deep learning method combined with multiple surface observation inputs, can generate high-resolution (250 m) bed topography with realistic bed roughness but produces some unrealistic artifacts and higher bed elevation values in certain regions, which could bias ice-sheet models. To address these issues, we present MB_DeepBedMap, a multi-branch deep learning method to generate more realistic bed topography. The model improves upon DeepBedMap by separating inputs into two groups using a multi-branch network structure according to their characteristics, rather than fusing all inputs at an early stage, to reduce artifacts in the generated topography caused by earlier fusion of inputs. A direct upsampling branch preserves large-scale subglacial landforms while generating high-resolution bed topography. We use MB_DeepBedMap to generate a high-resolution (250 m) bed elevation grid product of Antarctica, MB_DeepBedMap_DEM, which can be used in high-resolution ice-sheet modeling studies. Moreover, we test the performance of MB_DeepBedMap model in Thwaites Glacier, Gamburtsev Subglacial Mountains, and several other regions, by comparing the qualitative topographic features and quantitative errors of MB_DeepBedMap, BEDMAP2, BedMachine Antarctica, and DeepBedMap. The results show that MB_DeepBedMap can provide more realistic small-scale topographic features and roughness compared to BEDMAP2, BedMachine Antarctica, and DeepBedMap. Full article

Ground penetrating radar (GPR) has proven to be a very effective method for examining ice thickness. However, two preconditions must be met for this approach to be useful; the round-trip travel time of electromagnetic (EM) waves and radar transmission speed in the ice must be known. These issues are problematic because many factors affect radar transmission speed in ice, including impurities, physical properties such as porosity and density, and temperature. Results show that if these factors are not taken into account and a signal velocity of 0.17 m/ns in pure ice is used to estimate thickness, overestimates will result. We carried out a series of GPR surveys using dual channel host 200 MHz shielded antennas at the Toudaoguai Hydrological Station on the Yellow River, China, and collected samples to analyze ice impurities and physical properties. The results show that the ice crystal types include frazil, granular, and column at the Toudaoguai Hydrologic Station section. Our analysis of ice gas bubble and sediment content showed that the gas bubble volume content is between 11.95 and 13.0% in the frazil ice and between 7.9% and 8.6% in granular and columnar ice. At the same time, the ice sediment content ranged between 0.11‰ and 0.57‰, and the average was 0.24‰ in granular and columnar ice, which was about one-tenth that of the suspended sediment concentration in water. Additionally, a combination of GPR data as well as ice impurities, porosity, density, and temperature enabled us to provide insights on the variability of radar transmission speed and the equivalent dielectric permittivity in river ice. Our extensive observations reveal that radar transmission speed falls between 0.141 m/ns and 0.164 m/ns and that the equivalent dielectric permittivity of river ice increases in concert with ice temperature. Full article