Conference Agenda

BIOMASS ice flow mapping

Antarctic ice flow mapping from satellite SAR is a well-established technique, with several products available for users [1][2]. These products rely heavily on Sentinel-1 data, but the C-band wavelength means that phase-based InSAR techniques fail on fast moving glaciers due to loss of coherence from excessive fringe rates and high sensitivity to surface conditions. The fallback technique, amplitude-based offset-tracking, results in noisier velocity maps. For BIOMASS, only InSAR methods are expected to work, due to the coarse range resolution resulting from the 6MHz bandwidth.

The acquisition scenario and radar parameters of BIOMASS represent opportunities but also potential challenges when using BIOMASS for ice flow mapping. During the tomographic and InSAR phases, a given ground track is acquired in sets of images with 3-day temporal separation (7 images in each set in the tomographic phase, 3 in the InSAR phase) and a spatial separation of 15% of the critical baseline[3] in the tomographic phase and even larger baselines in the InSAR phase, so unlike Sentinel-1, a consistent dense temporal sampling cannot be achieved.

Compared to existing sensors, the increased penetration of the 70 cm wavelength reduces the adverse impact of changes in surface conditions, and in combination with the short temporal baselines, this is expected to result in reduced temporal decorrelation. Also, the long wavelength reduces fringe rates and simplifies phase unwrapping, although the low range resolution to some extent counteracts this benefit.

On the other hand, the increased penetration can result in increased volume decorrelation for baselines much smaller than the critical baseline, and this might well be an issue, considering the relatively large spatial baselines mentioned above. The long wavelength also means a significant sensitivity to ionospheric scintillations.

In this contribution, we present InSAR ice velocity maps generated from BIOMASS data acquired over Antarctica during the commissioning phase and investigate the impact of spatial baseline drift by comparing velocity maps generated from 0-baseline data with velocity maps generated from larger baseline data. Also, the impact of residual ionospheric signal on ice flow mapping is investigated.

References

[1] Rignot, E., J. Mouginot, and B. Scheuchl. 2017. MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/D7GK8F5J8M8R.

[2] J. Wuite, M. Hetzenecker, T. Nagler and S. Scheiblauer, ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly velocity from 2017 to 2020, derived from Sentinel-1, v1, NERC EDS Centre for Environmental Data Analysis, 2021.

[3] Shaun Quegan, et.al, The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space,Remote Sensing of Environment, Volume 227, 2019, Pages 44-60, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2019.03.032.

Microwave remote sensing has become an indispensable tool for monitoring polar regions, as its ability to penetrate dry snow and ice makes Synthetic Aperture Radar (SAR) particularly sensitive to subsurface structures. This sensitivity increases with decreasing frequency, enabling the detection of internal layers and features that remain invisible at higher frequencies.

ESA’s BIOMASS mission marks a significant milestone as the first spaceborne SAR system operating at P-band (435 MHz), providing unprecedented penetration depths and the potential to observe structural information from tens or even hundreds of meters below the surface [1]. Beyond its primary objective of global forest observation, BIOMASS offers new opportunities for cryospheric research through its fully polarimetric mode, which enables detailed characterization of scattering mechanisms within the Antarctic ice sheet.

This study focuses on an in-depth polarimetric analysis of BIOMASS data over Antarctica [2]. A dedicated test site will be selected based on the availability of ground reference measurements, such as sounder data, ground-penetrating radar (GPR) profiles, and ice core observations, which will be essential for validation and physical interpretation of the satellite data.

The analysis builds on previous experience with P-band SAR data in polar environments, gained during an airborne campaign with DLR’s F-SAR sensor in Greenland. There, multiple test sites across distinct glacial zones revealed key insights into polarimetric signatures. In the percolation zone, the anisotropic microstructure of the firn was shown to induce significant co-polar phase differences (CPD), and a corresponding CPD-based model established a quantitative relationship between polarimetric SAR measurements and firn thickness [3]. In the ablation zone, a Pauli decomposition in combination with entropy and the mean alpha angle distinguished areas with potential subtle differences in water content and density [4]. Furthermore, crevasses were effectively detected through characteristic combinations of volume and dihedral scattering, with polarization-dependent contrasts aiding their detection and characterization.

Preliminary investigations of BIOMASS P-band data indicate similar scattering mechanisms to those observed in the airborne campaign. However, several signatures identified in the BIOMASS polarimetry cannot yet be explained. To address this, the planned analysis will incorporate complementary decomposition techniques (e.g., eigenvalue-based and model-based approaches) to better characterize the dominant scattering mechanisms and retrieve their glaciological origin. A particular focus will be on investigating subsurface structures and exploring unusual scattering behaviors that may reveal previously unknown processes within the ice.

By integrating polarimetric analysis with reference data and advanced decomposition methods, this work aims to improve the physical understanding of P-band interactions with Antarctic ice. The resulting framework will provide the basis for fully exploiting BIOMASS P-band observations in cryospheric remote sensing and advancing the study of subsurface structures and ice-sheet dynamics.

[1] Rignot, E., et al. (2001). Penetration depth of interferometric synthetic-aperture radar signals in snow and ice. Geophysical Research Letters, 28(18), Art. no. 18.

[2] Cloude, S. (2010). Polarisation: applications in remote sensing (1st ed.). Oxford: Oxford University Press.

[3] Fischer, G. et al. (2019). Modeling Multifrequency Pol-InSAR Data from the Percolation Zone of the Greenland Ice Sheet. IEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 4

[4] Schlenk, S. et al. (2025). Characterization of Ice Features in the Southwest Greenland Ablation Zone Using Multi-Modal SAR Data. The Cyrosphere

Ice mapping is one of the secondary objectives of ESA's fully polarimetric P-band SAR mission, BIOMASS, recently launched on 29 April 2025 [1]. The use of P-band allows for deeper penetration into ice sheets and glaciers than what has been possible with the higher frequency spaceborne systems, used until now. The BIOMASS mission potentially allows for the mapping of subsurface features such as ice inclusions in the firn-pack, aquifers, and firn depths though the employment of advanced SAR techniques, namely Polarimetric SAR Interferometry (PolInSAR) and SAR Tomography (TomoSAR). Over the course of the BIOMASS mission, data will be acquired in two acquisition phases with orbits designed specifically for each of the two techniques. Furthermore, during the BIOMASS commissioning (COM) phase, data will be gathered with large spatial baselines over the Antarctic continent, potentially allowing for TomoSAR mapping of ice sheets with high vertical resolution.

From 11 December 2023 to 14 February, the Technical University of Denmark completed an airborne radar campaign in Antarctica. The primary objective was to gather airborne P-band data from the Antarctic continent in support of BIOMASS. Data was acquired with the POLARIS instrument, which was developed by the university, and commissioned by ESA [2]. The POLARIS instrument is a fully polarimetric P-band radar capable of operating both as an ice sounder and in a SAR configuration. During the campaign, PolInSAR data was acquired around the Dome C region in the dry snow zone, where no summer melt occurs. Also, both PolInSAR, TomoSAR, and ice sounder data was acquired at the Shackleton ice shelf in the percolation zone, where summer melt percolates down through the firn-pack, thus forming ice inclusions.

Previously, PolInSAR and TomoSAR analyses of ice sheets have been carried out in Greenland. However, this was in the ablation and percolation zone [3][4][5]. However, 90% of the Antarctic ice sheet is in the dry snow zone. Furthermore, the Antarctic continent is subject to specific meteorological conditions, which are not present in other snow-covered regions. Most notably, the surface at the Dome C region is dominated by longitudinal snow dunes [6]. These surface features lead to highly anisotropic backscatter while also potentially impacting the polarimetric signature of SAR images [7].

In this contribution, we present polarimetric analysis and PolInSAR results for both sites based the Uniform Volume under Surface (UVuS) model [8] (Dome C) and a more complex coherence model, accounting for both a surface and a subsurface scattering layer [3] (Shackleton). Furthermore, the presence of both PolInSAR, TomoSAR, and ice sounder data at the Shackleton site allows for a very thorough assessment of the feasibility of subsurface mapping of ice sheets through PolInSAR and TomoSAR techniques. At this site, subsurface structures observable in TomoSAR and ice sounder profile was predicted by PolInSAR model inversion, signifying an excellent level of cohesion between techniques. Finally, degradation of airborne P-band data allows for the direct assessment of BIOMASS feasibility regarding the subsurface mapping of ice sheets through the employment of TomoSAR and PolInSAR techniques.

References

[1] Shaun Quegan et al. “The European Space Agency BIOMASS mission: Measuring forest above-

ground biomass from space”. eng. In: Remote Sensing of Environment 227 (2019), pp. 44–60. ISSN:

18790704, 00344257. DOI: 10.1016/j.rse.2019.03.032.

[2] Jørgen Dall et al. “ESA’S POLarimetric Airborne Radar Ice Sounder (POLARIS): design and first

results”. eng. In: I E T Radar, Sonar and Navigation 4.3 (2010), pp. 488–496. ISSN: 17518784,

17518792. DOI: 10.1049/iet-rsn.2009.0035.

[3] Georg Fischer, Konstantinos P Papathanassiou, and Irena Hajnsek. “Modeling multifrequency pol-

InSAR data from the percolation zone of the Greenland ice sheet”. In: IEEE Trans. Geosci. Remote

Sens. 57.4 (Apr. 2019), pp. 1963–1976.

[4] Georg Fischer et al. “Modeling the Vertical Backscattering Distribution in the Percolation Zone of

the Greenland Ice Sheet With SAR Tomography”. eng. In: Ieee Journal of Selected Topics in Applied

Earth Observations and Remote Sensing 12.11 (2019), pp. 4389–4405. ISSN: 19391404, 21511535.

DOI: 10.1109/JSTARS.2019.2951026.

[5] Francesco Banda, Jørgen Dall, and Stefano Tebaldini. “Single and multipolarimetric P-band SAR

tomography of subsurface ice structure”. In: IEEE Trans. Geosci. Remote Sens. 54.5 (May 2016),

pp. 2832–2845.

[6] Marine Poizat et al. “Widespread longitudinal snow dunes in Antarctica shaped by sintering”. en. In:

Nat. Geosci. 17.9 (Sept. 2024), pp. 889–895.

[7] Jayanti J Sharma et al. “Polarimetric decomposition over glacier ice using long-wavelength airborne

PolSAR”. In: IEEE Trans. Geosci. Remote Sens. 49.1 (Jan. 2011), pp. 519–535.

[8] Jørgen Dall, Konstantinos Papathanassiou, and Henning Skriver. “Polarimetric SAR interferometry

applied to land ice: modeling”. eng. In: Proceedings of the Eusar 2004 Conference (2004), pp. 247–

250.

Understanding structure and dynamics of ice sheets and glaciers is of crucial importance [1], as ice masses represent a major storage of freshwater and influence global water circulation. Loss of ice masses is exacerbated by warming climate, with a negative impact on sea level rise. There is thus an urgent need for globally improving knowledge about ice sheets and glaciers, which is difficult to achieve only with in situ studies, due to limited coverage and often access difficulties. Satellite remote sensing can provide a bridge, with Synthetic Aperture Radar (SAR) able to acquire information in all-weather, day and night conditions. SAR interferometry (InSAR) and tomography (TomoSAR) at long wavelengths (P and L bands) give access to the internal structure of ice by combining multiple SAR surveys from slightly different viewpoints [2].

ESA’s BIOMASS [3], successfully launched April 29, 2025, features the first spaceborne P-band SAR with fully polarimetric capabilities and orbits enabling InSAR and TomoSAR. BIOMASS primary target are world’s forests, though the long wavelength of about 70 cm is an unprecedented opportunity for more and equally important applications, among which the investigation of subsurface structures, including icy regions. In particular, orbits deployed for antenna pattern characterization over BIOMASS transponder during In-Orbit Commissioning (IOC) phase are suitable for TomoSAR imaging over Antarctica.

In this contribution we present preliminary BIOMASS TomoSAR results over Antarctica. We processed a dataset acquired in the July/August 2025 IOC phase over the Shackleton Ice Shelf System [4], an increasingly studied site gaining attention due to its vulnerability and important role played in stabilizing part of the East Antarctic ice sheet. Contextually, we extended Multi-Squint InSAR (MS-InSAR) presented in a companion contribution [6] to multi-baseline, to phase calibrate the data stack and counteract coherence losses due to severe ionosphere at high latitudes.

References

[1] P. L. Whitehouse, N. Gomez, M. A. King, and D. A. Wiens, “Solid Earth change and the evolution of the Antarctic Ice Sheet,” Nature communications, 2019

[2] F. Banda, J. Dall, and S. Tebaldini, “Single and multipolarimetric P-band SAR tomography of subsurface ice structure,” IEEE Transactions on Geoscience and Remote Sensing, 2015

[3] S. Quegan, et al., “The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space,” Remote Sensing of Environment, 2019

[4] Thompson, Sarah S et al., “Glaciological history and structural evolution of the shackleton ice shelf system, east antarctica, over the past 60 years,” The Cryosphere, 2023

[6] S. Tebaldini, F. Salvaterra, F. Banda, and M. Pinheiro, “Multi-layer ionosphere correction in BIOMASS interferometry,” Submitted to POLINSAR 2026

Lakes are common features of arctic lowland permafrost regions. Increasing temperatures and changing precipitation regimes at higher latitudes affect the ice forming seasonally at their surface. In particular, the thinning of this ice layer can lead to a shift from bedfast-ice regime, where the ice reaches the bottom of the lake, to a floating-ice regime, where there still remains liquid water below the ice layer. This in turn can lead to potential greenhouse gas release from the newly unfrozen ground at the lake bottom [1]. Monitoring the ice thickness and the ice regime is therefore crucial. To this end, Synthetic Aperture Radar (SAR) is well adapted because the radar waves penetrate into the ice volume at all bands. Though the polarimetric signature of these lakes has been well studied [2], no study yet has investigated the vertical reflectivity profile from the ice layer which can be retrieved by combining SAR acquisitions coherently, in a SAR interferometry (InSAR) or SAR tomography (TomoSAR) framework. This contribution aims at reconstructing this profile in a number of lakes by exploiting the sensitivity in the height direction of multi-baseline SAR data and at improving the understanding of scattering in the lake ice volume and at its interfaces: air/ice and ice/water interfaces in the floating-ice case; air/ice and ice/frozen-ground interfaces in the bedfast-ice case.

For this analysis, we propose to use the PermASAR19 airborne TomoSAR dataset, which was collected by the German Aerospace Center (DLR) in the Canadian low Arctic in the late winter season of 2019. The acquisitions are fully polarimetric, and were performed at several bands (X-, C- and L-band) with submeter spatial resolution in both range and azimuth directions, within a two-hour time window. The SAR footprint covers several lakes which are known to be shallow (only a few meters depth), and which ice thickness is expected to reach approximately 1 meter [3] [4]. Challenges arise from the thinness of the ice layer with respect to achievable resolution in height from usual beamforming methods, suggesting that high-resolution tomographic techniques like Capon beamforming are required.

First analyses with separated polarizations show that scattering occurring within the ice volume and at interfaces can be observed in the reconstructed profiles, at X-band and C-band over several lakes. Combining polarimetric channels coherently in a polarimetric tomographic SAR (Pol-TomoSAR) framework will improve the physical understanding of the retrieved profiles [5]. A Pol-TomoSAR analysis over several lakes of the testsite will be presented. The results of several bands, in particular X-band and C-band, will be compared. The obtained estimated structure information will be assessed with regards to ground measurements of lake bathymetry and ice thickness [3] [4].

[1] C. D. Arp, B. M. Jones, Z. Lu, and M. S. Whitman (2012), “Shifting balance of thermokarst lake ice regimes across the Arctic Coastal Plain of northern Alaska”, Geophysical Research Letters, vol. 39, L16503, doi: 10.1029/2012GL052518

[2] D. K. Atwood, G. E. Gunn, C. Roussi, J. Wu, C. Duguay, and K. Sarabandi (2015), “Microwave Backscatter From Arctic Lake Ice and Polarimetric Implications”, IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 11, p. 5972-5982

[3] E. J. Wilcox (2025), "Ice thickness, snow depth and lake properties for sampled lakes in and around the Trail Valley Creek watershed, NT", https://doi.org/10.5683/SP3/VP1UMC, Borealis

[4] E. J. Wilcox (2025), "Lake bathymetry measurements for sampled lakes in and around the Trail Valley Creek watershed, NT", https://doi.org/10.5683/SP3/7XADY4, Borealis

[5] L. Ferro-Famil, Y. Huang, and A. Reigber (2012), “High-resolution SAR tomography using full rank polarimetric spectral estimators”, 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, pp. 5194-5197