the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improved records of glacier flow instabilities using customized NASA autoRIFT applied to PlanetScope imagery
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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RC1: 'Comment on egusphere-2024-374', Anonymous Referee #1, 18 Mar 2024
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I have reviewed the paper entitled ‘Improved records of glacier flow instabilities using customized NASA autoRIFT applied to PlanetScope imagery’ submitted for consideration for publication in The Cryosphere. Using five test glaciers, this manuscript presents improvements to optically derived glacier velocities using a modified version of the NASA autoRIFT and the inclusion of PlateScope (PS) imagery. Overall, enjoyed reading this manuscript and congratulate the authors on a well written and clearly presented manuscript. The authors provide a detailed description of the processing steps, and their test cases clearly demonstrate the improvement in terms of the temporal density of velocity estimates that can be used to understand variations in glacier flow for surge-type glaciers. The only major comment that I have to improve this manuscript is to encourage the authors to include a comparison between the PS and in situ derived velocities. For example, Figure A3 presents in situ derived GPS displacements, which seem to match up with at least some of the PS derived velocities. This would provide a nice comparison/documentation of how well the PS derived velocities perform in very fast flowing situations. Other than this, I only have minor comments listed below to be addressed.
L2/3: ‘glacier velocity records are sometimes incomplete due to gaps in the cloud-free satellite image record’ – here you may want to tweak the sentence and specify that cloud and night impact glacier velocity records derived from optical imagery. This is not an issue for glacier velocities derived from SAR imagery (although those that are derived from SAR have their own nuances as well).
L12: ‘dramatic changes’ can you quantify this here?
L63: I believe that custom autoRIFT should be in quotation marks.
L72: ‘in the Yukon’ change to ‘in Yukon’ (‘the’ is not necessary)
L70/75: Can you provide a sentence here that rationalizes the choice of these five glaciers?
L161: Can you expand on this? How many images were manually filtered out? How user intensive is this process? I expect that it is rather time consuming.
Figure 2: All the Matlab figures should have colourmap labels.
L163/164: Why is a DEM needed? Please add a sentence to describe why this is needed for completeness. How were the use of different DEMs determined? For example, for the Svalbard site, ArcticDEM was available, so why was it not used instead of GMTED2010? Maybe it doesn’t matter, but there should be some justification for the DEMs used at each location. How much to the resolution of the DEM matter in terms of the quality of the final velocity maps?
L269/270: Can you clarify this sentence; you are comparing median stable surface errors from custom autoRIFT to maximum (SSE?) errors from ITS_LIVE? So, are you comparing the same thing?
Figure 6: It feels to me that the scaling for a)b) and c)/d) and e)/f) should be done independent of each other. For example the maximum of c) and d) should be set to 20 m/day and for e) and f) it should be set to (maybe) 15 m/day. I know that you want consistency to compare across these three glaciers, but to me the more important aspect to showcase is the custom autoRIFT performance at each site. At present, with the current scaling applied, the reader cannot see the variations across the glacier in c) and e) because all the variation falls within the purplish colours.
Citation: https://doi.org/10.5194/egusphere-2024-374-RC1
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
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