GLAcier Feature Tracking testkit (GLAFT): A statistically- and physically-based framework for evaluating glacier velocity products derived from satellite image feature tracking

• Main Authors: Zheng, Whyjay, Bhushan, Shashank, Wyk De Vries, Maximillian, Kochtitzky, William, Shean, David, Copland, Luke, Dow, Christine, Jones-Ivey, Renette, Pérez, Fernando
• Format: Text
• Language: English
• Published: 2023
• Subjects: Canada; Kaskawulsh Glacier; glacier*
• Online Access: https://doi.org/10.5194/tc-2023-38; https://tc.copernicus.org/preprints/tc-2023-38/

Glacier velocity measurements are essential to understand ice flow mechanics, monitor natural hazards, and make accurate projections of future sea-level rise. Despite these important applications, the method most commonly used to derive glacier velocity maps, feature tracking, relies on empirical parameter choices that rarely account for glacier physics or uncertainty. Here we test two statistics- and physics-based metrics to assess velocity maps from a range of existing feature-tracking workflows at Kaskawulsh Glacier, Canada. Based on inter-comparisons with ground-truth data, velocity maps with metrics falling within our recommended ranges contain fewer erroneous measurements and more spatially correlated noise than velocity maps with metrics that deviate from those ranges. Thus, these metric ranges are suitable for refining feature-tracking workflows and evaluating the resulting velocity products. We have released an open-source software package for computing and visualizing these metrics, the GLAcier Feature Tracking testkit (GLAFT).