Articles | Volume 19, issue 4
https://doi.org/10.5194/tc-19-1675-2025
https://doi.org/10.5194/tc-19-1675-2025
Research article
 | 
24 Apr 2025
Research article |  | 24 Apr 2025

Automated snow cover detection on mountain glaciers using spaceborne imagery and machine learning

Rainey Aberle, Ellyn Enderlin, Shad O'Neel, Caitlyn Florentine, Louis Sass, Adam Dickson, Hans-Peter Marshall, and Alejandro Flores

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Cited articles

Aberle, R., Enderlin, E., O'Neel, S., Florentine, C., Sass, L., Dickson, A., Marshall, H.-P., and Flores, A.: Dataset for Automated Snow Cover Detection on Mountain Glaciers Using Space-Borne Imagery, CryoGARS Glaciology Data [data set], https://doi.org/10.18122/cryogars_data.4.boisestate, 2024a. 
Aberle, R., Enderlin, E., and Liu, J.: RaineyAbe/glacier-snow-cover-mapping: Second release (v0.2), Zenodo [code], https://doi.org/10.5281/zenodo.10616385, 2024b. 
Anderson, B. T., McNamara, J. P., Marshall, H.-P., and Flores, A. N.: Insights into the physical processes controlling correlations between snow distribution and terrain properties, Water Resour. Res., 50, 4545–4563, https://doi.org/10.1002/2013WR013714, 2014. 
Bahadur K. C., K.: Improving Landsat and IRS Image Classification: Evaluation of Unsupervised and Supervised Classification through Band Ratios and DEM in a Mountainous Landscape in Nepal, Remote Sens., 1, 1257–1272, https://doi.org/10.3390/rs1041257, 2009. 
Berman, E. E., Bolton, D. K., Coops, N. C., Mityok, Z. K., Stenhouse, G. B., and Moore, R. D. (Dan): Daily estimates of Landsat fractional snow cover driven by MODIS and dynamic time-warping, Remote Sens. Environ., 216, 635–646, https://doi.org/10.1016/j.rse.2018.07.029, 2018. 
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Short summary
Tracking seasonal snow on glaciers is critical for understanding glacier health. Yet previous work has not directly compared machine learning algorithms for snow classification across satellite image products. To address this, we developed a new automated workflow for tracking seasonal snow on glaciers using several image products and machine learning models. Applying this method can help provide insights into glacier health, water resources, and the effects of climate change on snow cover.
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