Preprints
https://doi.org/10.5194/egusphere-2024-374
https://doi.org/10.5194/egusphere-2024-374
22 Feb 2024
 | 22 Feb 2024

Improved records of glacier flow instabilities using customized NASA autoRIFT applied to PlanetScope imagery

Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle

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 and failure of standard feature-tracking parameters (e.g., search range, chip size, estimated displacement, etc.) to capture rapid changes in glacier velocity. Here, we present a pipeline for pre-processing commercial high-resolution PlanetScope surface reflectance images (available daily) and for gen- erating 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 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., change of > 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 dramatic changes in flow speed with uncertainties of only ∼ 0.5 m/d. Additionally, the PlanetScope image record approximately doubles the amount of 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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Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-374', Anonymous Referee #1, 18 Mar 2024
  • RC2: 'Comment on egusphere-2024-374', Anonymous Referee #2, 05 May 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-374', Anonymous Referee #1, 18 Mar 2024
  • RC2: 'Comment on egusphere-2024-374', Anonymous Referee #2, 05 May 2024
Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle

Model code and software

CryoGARS-Glaciology/planet_tile2img: Initial release (v0.1.1) Jukes Liu, Madeline Gendreau, Ellyn Enderlin, and Rainey Aberle https://doi.org/10.5281/zenodo.10632745

jukesliu/SK-surge-mapping: v1.1 (v1.1). Jukes Liu and Ellyn Enderlin https://doi.org/10.5281/zenodo.10616628

Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle

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Short summary
There are sometimes gaps in global glacier velocity records produced using satellite image feature-tracking algorithms during times of rapid glacier acceleration, which hinders the study of glacier flow processes. We present an open-source pipeline for customizing the feature-tracking parameters and for including images from an additional source. We applied it to 5 glaciers and found that it produced accurate velocity data that supplemented their velocity records during rapid acceleration.