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.