  The increasing threat of sea level rise due to climate change necessitates a
deeper understanding of ice sheet structures. This study addresses the need for
accurate ice sheet data interpretation by introducing a suite of quantitative
metrics designed to validate ice sheet annotation techniques. Focusing on both
manual and automated methods, including ARESELP and its modified version,
MARESELP, we assess their accuracy against expert annotations. Our methodology
incorporates several computer vision metrics, traditionally underutilized in
glaciological research, to evaluate the continuity and connectivity of ice
layer annotations. The results demonstrate that while manual annotations
provide invaluable expert insights, automated methods, particularly MARESELP,
improve layer continuity and alignment with expert labels.
