Multi-Channel Coherent Radar Depth Sounder Research Articles

TransSounder: A Hybrid TransUNet-TransFuse Architectural Framework for Semantic Segmentation of Radar Sounder Data

Radar Sounders (RSs) are nadir-looking sensors operating in high frequency (HF) or very high frequency (VHF) bands that profile subsurface targets to retrieve miscellaneous scientific information. Due to complex electromagnetic interaction between back-scattered returns, the interpretation of RS data is challenging. The investigations of ice-sheet subsurface structures require automatic techniques to account for both the sequential spatial distribution of subsurface targets and relevant statistical properties embedded in RS signals. Automatic techniques exist for characterizing these targets either related to probabilistic inference models or convolutional neural network (CNN) deep learning methods. Unfortunately, CNN-based methods capture local spatial context and merely model the global spatial context. In contrast to CNN, the Transformer-based models are reliable architectures for capturing long-range sequence-to-sequence global spatial contextual prior. Motivated by the aforementioned fact, we propose a novel Transformer-based semantic segmentation architecture named TransSounder to effectively encode the sequential structures of the RS signals. The TransSounder was constructed on a hybrid TransUNet-TransFuse architectural framework to systematically augment the modules from TransUNet and TransFuse architectures. Experimental results obtained using the Multichannel Coherent Radar Depth Sounder (MCoRDS) dataset confirms the robustness and capability of Transformers to accurately characterize the different subsurface targets.

A Deep Learning Architecture for Semantic Segmentation of Radar Sounder Data

During the last decades, radar sounders provided direct measurements (radargrams) of the Earth’s polar caps’ subsurface. Radargrams are of critical importance for a better understanding of glaciologic structures and processes of the ice sheet in the framework of climate change. This article aims to automatically extract information on basal boundary conditions given their substantial relevance for modeling the ice-sheet processes, such as the sliding. We introduce a novel automatic method based on deep learning to detect the basal layer and basal units in radargrams acquired in the inland of icy areas. Radargrams are segmented into englacial layers, bedrock, basal units, and noise-limited regions; the latter includes the echo-free zone (EFZ), thermal noise, and signal perturbation. The network is a U-Net with attention gates and the Atrous Spatial Pyramid Pooling (ASPP) module that automatically extract semantically meaningful features at different scales. Experimental results on two datasets acquired in north Greenland and west Antarctica by the Multichannel Coherent Radar Depth Sounder (MCoRDS3) indicate a high overall segmentation accuracy. The accuracy of basal ice and signal perturbation detection is high, and that of the other classes is comparable with the literature techniques based on handcrafted features. The results show the effectiveness of the proposed method in automatically extracting semantically meaningful features to segment radargrams and map the basal layer and basal units.

Brief communication: Mapping Greenland's perennial firn aquifers using enhanced-resolution L-band brightness temperature image time series

Abstract. Enhanced-resolution L-band brightness temperature (TB) image time series generated from observations collected over the Greenland Ice Sheet by NASA's Soil Moisture Active Passive (SMAP) satellite are used to map Greenland's perennial firn aquifers from space. Exponentially decreasing L-band TB signatures are correlated with perennial firn aquifer areas identified via the Center for Remote Sensing of Ice Sheets (CReSIS) Multi-Channel Coherent Radar Depth Sounder (MCoRDS) that was flown by NASA's Operation IceBridge (OIB) campaign. An empirical algorithm to map extent is developed by fitting these signatures to a set of sigmoidal curves. During the spring of 2016, perennial firn aquifer areas are found to extend over ∼66 000 km2.

A Polarimetric Coherence Method to Determine Ice Crystal Orientation Fabric From Radar Sounding: Application to the NEEM Ice Core Region

Ice crystal orientation fabric (COF) records information about past ice-sheet deformation and influences the present-day flow of ice. Polarimetric radar sounding provides a means to infer anisotropic COF patterns due to the associated birefringence of polar ice. Here, we develop a polarimetric coherence (phase-based) method to determine horizontal properties of the COF. The method utilizes the azimuth and depth dependence of the vertical gradient of the hhvv coherence phase to infer the dielectric principal axes and birefringence, which are then related to the second-order fabric orientation tensor. Specifically, under the assumption that one of the orientational eigenvectors is vertical, we can determine the horizontal eigenvectors and the difference between the horizontal eigenvalues (a measure of horizontal fabric asymmetry). The method exploits single-polarized data acquired with varying antenna orientation. It applies to ground-based “multi-polarization” surveys and is demonstrated using data acquired by Center for Remote Sensing of Ice Sheets (CReSIS) using Multi-Channel Coherent Radar Depth Sounder (MCRDS) from the North Greenland Eemian Ice Drilling (NEEM) ice core region in Greenland. The analysis is validated using a combination of polarimetric matrix backscatter simulations and comparison with COF data from the NEEM ice core. The results are consistent with a conventional model of ice deformation at an ice divide where a lateral tension component is present, with minor horizontal COF asymmetry and the greatest horizontal concentration of crystallographic axes orientated near parallel to the ice divide.

A New Method for Automatically Tracing Englacial Layers from MCoRDS Data in NW Greenland

Englacial layering reflects ice dynamics within the ice bodies, which improves understanding of ice flow variation, past accumulation rates and vertical flows transferring between the surface and the underlying bedrock. The internal layers can be observed by using Radar Echo Sounding (RES), such as the Multi-channel Coherent Radar Depth Sounder (MCoRDS) used in NASA’s Operation IceBridge (OIB) mission. Since the 1960s, the accumulation of the RES data has prompted the development of automated methods to extract the englacial layers. In this study, we propose a new automated method that combines peak detection methods, namely the CWT-based peak detection or the Automatic Phase Picker (APP), with a Hough Transform (HT) to trace boundaries of englacial layers. For CWT-based peak detection, we test it using two different wavelets. The proposed method is tested with twelve MCoRDS radio echograms, which are acquired south of the Northern Greenland Eemian (NEEM) ice drilling site, where the folding of ice layers was observed. The method is evaluated in comparison to the isochrones that were extracted in an independent study. In comparison, the proposed new automated method can restore more than 70% of the englacial layers. This new automated layer-tracing method is publicly available on github.

EXTRACTION OF ICE SHEET LAYERS FROM TWO INTERSECTED RADAR ECHOGRAMS NEAR NEEM ICE CORE IN GREENLAND

Abstract. Accumulation of snow and ice over time result in ice sheet layers. These can be remotely sensed where there is a contrast in electromagnetic properties, which reflect variations of the ice density, acidity and fabric orientation. Internal ice layers are assumed to be isochronous, deep beneath the ice surface, and parallel to the direction of ice flow. The distribution of internal layers is related to ice sheet dynamics, such as the basal melt rate, basal elevation variation and changes in ice flow mode, which are important parameters to model the ice sheet. Radar echo sounder is an effective instrument used to study the sedimentology of the Earth and planets. Ice Penetrating Radar (IPR) is specific kind of radar echo sounder, which extends studies of ice sheets from surface to subsurface to deep internal ice sheets depending on the frequency utilised. In this study, we examine a study site where folded ice occurs in the internal ice sheet south of the North Greenland Eemian ice drilling (NEEM) station, where two intersected radar echograms acquired by the Multi-channel Coherent Radar Depth Sounder (MCoRDS) employed in the NASA’s Operation IceBridge (OIB) mission imaged this folded ice. We propose a slice processing flow based on a Radon Transform to trace and extract these two sets of curved ice sheet layers, which can then be viewed in 3-D, demonstrating the 3-D structure of the ice folds.

EXTRACTION OF ICE SHEET LAYERS FROM TWO INTERSECTED RADAR ECHOGRAMS NEAR NEEM ICE CORE IN GREENLAND

Accumulation of snow and ice over time result in ice sheet layers. These can be remotely sensed where there is a contrast in electromagnetic properties, which reflect variations of the ice density, acidity and fabric orientation. Internal ice layers are assumed to be isochronous, deep beneath the ice surface, and parallel to the direction of ice flow. The distribution of internal layers is related to ice sheet dynamics, such as the basal melt rate, basal elevation variation and changes in ice flow mode, which are important parameters to model the ice sheet. Radar echo sounder is an effective instrument used to study the sedimentology of the Earth and planets. Ice Penetrating Radar (IPR) is specific kind of radar echo sounder, which extends studies of ice sheets from surface to subsurface to deep internal ice sheets depending on the frequency utilised. In this study, we examine a study site where folded ice occurs in the internal ice sheet south of the North Greenland Eemian ice drilling (NEEM) station, where two intersected radar echograms acquired by the Multi-channel Coherent Radar Depth Sounder (MCoRDS) employed in the NASA’s Operation IceBridge (OIB) mission imaged this folded ice. We propose a slice processing flow based on a Radon Transform to trace and extract these two sets of curved ice sheet layers, which can then be viewed in 3-D, demonstrating the 3-D structure of the ice folds.

Deep radiostratigraphy of the East Antarctic plateau: connecting the Dome C and Vostok ice core sites

ABSTRACTSeveral airborne radar-sounding surveys are used to trace internal reflections around the European Project for Ice Coring in Antarctica Dome C and Vostok ice core sites. Thirteen reflections, spanning the last two glacial cycles, are traced within 200 km of Dome C, a promising region for million-year-old ice, using the University of Texas Institute for Geophysics High-Capacity Radar Sounder. This provides a dated stratigraphy to 2318 m depth at Dome C. Reflection age uncertainties are calculated from the radar range precision and signal-to-noise ratio of the internal reflections. The radar stratigraphy matches well with the Multichannel Coherent Radar Depth Sounder (MCoRDS) radar stratigraphy obtained independently. We show that radar sounding enables the extension of ice core ages through the ice sheet with an additional radar-related age uncertainty of ~1/3–1/2 that of the ice cores. Reflections are extended along the Byrd-Totten Glacier divide, using University of Texas/Technical University of Denmark and MCoRDS surveys. However, core-to-core connection is impeded by pervasive aeolian terranes, and Lake Vostok's influence on reflection geometry. Poor radar connection of the two ice cores is attributed to these effects and suboptimal survey design in affected areas. We demonstrate that, while ice sheet internal radar reflections are generally isochronal and can be mapped over large distances, careful survey planning is necessary to extend ice core chronologies to distant regions of the East Antarctic ice sheet.