GLAcier Feature Tracking testkit (GLAFT): a statistically and physically based framework built on top of open science workflows for evaluating glacier velocity maps
Abstract
Accurate assessments of glacier velocity are essential for understanding ice flow mechanics, monitoring natural hazards, and projecting future sea-level rise. However, the most commonly used method for deriving glacier velocity maps, known as feature tracking, relies on empirical parameter choices that rarely account for glacier physics or uncertainty. The GLAcier Feature Tracking testkit (GLAFT) aims to assess velocity maps using two statistically and physically based metrics. 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. Consequently, these metric ranges are suitable for refining feature-tracking workflows and evaluating the resulting velocity products. GLAFT provides modulized workflows for calculating these metrics and the associated visualization, facilitating the velocity map assessments. To ensure the package is available, reusable, and redistributable to the maximum extent, GLAFT adopts several open science practices including the narrative documentation and demos using Jupyter Book and cloud access using Ghub. By providing the benchmarking framework for evaluating the quality of glacier velocity maps procedure, GLAFT enables the cryospheric sciences and natural hazards communities to leverage the rich glacier velocity data now available, whether they are sourced from public archives or made through custom feature-tracking processes.