MorphoLayerTrace (MLT): A Modified Automated Radio-Echo Sounding Englacial Layer-tracing Algorithm for Englacial Layer Annotation in Ice Penetrating Radar Data

Abstract

Modeling ice flow is a critical component of sea level rise projections, yet the datasets available to enhance our understanding of large-scale ice dynamics remain limited. Extracting the englacial layer configuration of the Greenland ice sheet offers valuable insights into the age of the ice, which can inform studies of past snow accumulation, glacier sliding, and provide context for modern glacier change. Although these englacial layers have been extensively surveyed using ice-penetrating radar/radio-echo sounding, the resulting radargram imagery, with fine grained ice layers, is often labeled manually or semi-automatically. This is a laborintensive process that hinders integration into glacier models. In this paper, we propose an improved automatic annotation method, MorphoLayerTrace (MLT), building upon the Automated RadioEcho Sounding Englacial Layer-tracing Package ( ARESELP). Our approach enhances englacial layer tracing by utilizing peak distance thresholds and morphological image processing to select reliable seed points, significantly improving layer continuity and reducing discontinuities. Our technique is designed to operate effectively on both individual radargram frames and multi-frame sets, enabling better performance over extended distances. We evaluate the method using 100 radargram frames collected across North Greenland, demonstrating its ability to trace more layers and maintain greater continuity compared to previous methods. Furthermore, we introduce novel validation metrics, such as the Layer Proportion Score (LPS) and the Multi-Frame Layer Consistency (MF LC) score, which provide a more robust and ground truth-independent evaluation of annotation quality. Our results show that while the method excels in short-range layer detection over the prior layer tracing methods, further refinement is needed for maintaining long-range continuity across multiple frames, offering a promising direction for future development in automatic englacial layer annotation