Metrics for the Quality and Consistency of Ice Layer Annotations

Date

2023-07

Department

Program

Citation of Original Publication

Tack, Naomi, Bayu Adhi Tama, Atefeh Jebeli, Vandana P. Janeja, Don Engel, and Rebecca Williams. “Metrics for the Quality and Consistency of Ice Layer Annotations.” In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 4935–38, 2023. https://doi.org/10.1109/IGARSS52108.2023.10283420.

Rights

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Abstract

Ice layers in glaciers, such as those covering Greenland and Antarctica, are deformed over time. The deformations of these layers provide a record of climate history and are useful in predicting future ice flow and ice loss. Cross sectional images of the ice can be captured by airborne radar and layers in the images then annotated by glaciologists. Recent advances in semi-automated and automated annotation allow for significantly more annotations, but the validity of these annotations is difficult to determine because ground-truth (GT) data is scarce. In this paper, we (1) propose GT-dependent and GT-independent metrics for layer annotations and (2) present results from our implementation and initial testing of GT-independent metrics, such as layer breakpoints, local layer density, spatial frequency, and layer orientation agreement.