Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-4657-2025
https://doi.org/10.5194/tc-19-4657-2025
Research article
 | 
20 Oct 2025
Research article |  | 20 Oct 2025

An alternative representation of Synthetic Aperture Radar images as an aid to the interpretation of englacial observations

Álvaro Arenas-Pingarrón, Alex M. Brisbourne, Carlos Martín, Hugh F. J. Corr, Carl Robinson, Tom A. Jordan, and Paul V. Brennan

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Cited articles

Arenas-Pingarrón, Á.: antarctica/sar-rgb-spectral-decomposition: SAR_rgb_spectral_decomposition (v1.0.3), Zenodo [code], https://doi.org/10.5281/zenodo.14962614, 2025. 
Arenas Pingarron, A., Brisbourne, A., Corr, H., Jordan, T., Robinson, C., Martin, C., Nicholls, K., and Smith, A.: Ice-sounding airborne synthetic aperture radar depth profiles from Recovery Ice Stream 2016/17 and Rutford Ice Stream 2019/20 to test the RGB-Doppler-Decomposition method (Version 1.0), NERC EDS UK Polar Data Centre [data set], https://doi.org/10.5285/40c2f86b-1a02-4106-934a-42769682df66, 2023a. 
Arenas-Pingarrón, Á., Corr, H. F. J., Jordan, T. A., Robinson, C., and Brennan, P. V.: Polarimetric airborne scientific instrument, mark 2, an ice-sounding airborne synthetic aperture radar for subglacial 3D imagery, IET Radar Sonar Nav., 1–14, https://doi.org/10.1049/rsn2.12428, 2023b. 
Bindschadler, R., Vornberger, P., Fleming, A., Fox, A., Mullins, J., Binnie, D., Paulson, S., Granneman, B., and Gorodetzky, D.: The Landsat Image Mosaic of Antarctica, Remote Sens. Environ., 112, 4214–4226, https://doi.org/10.1016/j.rse.2008.07.006, 2008. 
Castelletti, D., Schroeder, D., Mantelli, E., and Hilger, A.: Layer optimized SAR processing and slope estimation in radar sounder data, J. Glaciol., 65, 983–988, https://doi.org/10.1017/jog.2019.72, 2019. 
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Short summary
Synthetic Aperture Radar (SAR) imaging is essential for deep englacial observations. Each pixel is formed by averaging the radar echoes within an antenna beamwidth, but the echo diversity is lost after the average. We improve the SAR interpretation if three sub-images are formed with different sub-beamwidths: each is coloured in red, green, or blue, and they are overlapped, creating a coloured image. Interpreters will better identify the slopes of internal layers, crevasses, and layer roughness.
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