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Abstract. En masse application of feature tracking algorithms to satellite image pairs has produced records of glacier surface velocities with global coverage, revolutionizing the understanding of global glacier change. However, glacier velocity records are sometimes incomplete due to gaps in the cloud-free satellite image record (for optical images) and failure of standard feature tracking parameters, e.g., search range, chip size, or estimated displacement, to capture rapid changes in glacier velocity. Here, we present a pipeline for pre-processing commercial high-resolution daily PlanetScope surface reflectance images and for generating georeferenced glacier velocity maps using NASA's autonomous Repeat Image Feature Tracking (autoRIFT) algorithm with customized parameters. We compare our velocity time series to the NASA Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) global glacier velocity dataset, which is produced using autoRIFT, with regional-scale feature tracking parameters. Using five surge-type glaciers as test sites, we demonstrate that the use of customized feature tracking parameters for each glacier improves upon the velocity record provided by ITS_LIVE during periods of rapid glacier acceleration (i.e., changes greater than several meters per day over 2–3 months). We show that ITS_LIVE can fail to capture velocities during glacier surges but that both the use of custom autoRIFT parameters and the inclusion of PlanetScope imagery can capture the progression of order-of-magnitude changes in flow speed with median uncertainties of <0.5 m d−1. Additionally, the PlanetScope image record approximately doubles the amount of optical cloud-free imagery available for each glacier and the number of velocity maps produced outside of the months affected by darkness (i.e., polar night), augmenting the ITS_LIVE record. We demonstrate that these pipelines provide additional insights into speedup behavior for the test glaciers and recommend that they are used for studies that aim to capture glacier velocity change at sub-monthly timescales and with greater spatial detail.
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GLAcier Feature Tracking testkit (GLAFT): a statistically and physically based framework for evaluating glacier velocity products derived from optical satellite image feature tracking
Abstract. 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 evaluate velocity maps derived from optical satellite images of Kaskawulsh Glacier, Yukon, Canada, using a range of existing feature-tracking workflows. 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).
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- PAR ID:
- 10465082
- Publisher / Repository:
- European Geosciences Union
- Date Published:
- Journal Name:
- The Cryosphere
- Volume:
- 17
- Issue:
- 9
- ISSN:
- 1994-0424
- Page Range / eLocation ID:
- 4063 to 4078
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/tc-17-4063-2023
