A comparison of automated approaches to extracting englacial-layer geometry from radar data across ice sheets

Richard Delf, Dustin Schroeder, Andrew Curtis, Antonios Giannopoulos, Robert G. Bingham

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Radar surveys across ice sheets typically measure numerous englacial layers that can often be regarded as isochrones. Such layers are valuable for extrapolating age–depth relationships away from ice-core locations, reconstructing palaeoaccumulation variability, and investigating past ice-sheet dynamics. However, the use of englacial layers in Antarctica has been hampered by underdeveloped techniques for characterising layer continuity and geometry over large distances, with techniques developed independently and little opportunity for inter-comparison of results. In this paper, we present a methodology to assess the performance of automated layer-tracking and layer-dip-estimation algorithms through their ability to propagate a correct age–depth model. We use this to assess isochrone-tracking techniques applied to two test case datasets, selected from CreSIS MCoRDS data over Antarctica from a range of environments including low-dip, continuous layers and layers with terminations. We find that dip-estimation techniques are generally successful in tracking englacial dip but break down in the upper and lower regions of the ice sheet. The results of testing two previously published layer-tracking algorithms show that further development is required to attain a good constraint of age–depth relationships away from dated ice cores. We recommend that auto-tracking techniques focus on improved linking of picked stratigraphy across signal disruptions to enable accurate determination of the Antarctic-wide age–depth structure.
Original languageEnglish
JournalAnnals of Glaciology
Publication statusPublished - 17 Jun 2020


Dive into the research topics of 'A comparison of automated approaches to extracting englacial-layer geometry from radar data across ice sheets'. Together they form a unique fingerprint.

Cite this