An inventory of supraglacial lakes and channels across the West Antarctic Ice Sheet

Corr, Diarmuid; Leeson, Amber; McMillan, Malcolm; Zhang, Ce; Barnes, Thomas

doi:https://doi.org/10.5194/essd-14-209-2022

Articles | Volume 14, issue 1

https://doi.org/10.5194/essd-14-209-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Benchmark datasets and machine learning algorithms for Earth...

https://doi.org/10.5194/essd-14-209-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 1

Data description paper

|

24 Jan 2022

Data description paper |

| 24 Jan 2022

An inventory of supraglacial lakes and channels across the West Antarctic Ice Sheet

Diarmuid Corr, Amber Leeson, Malcolm McMillan, Ce Zhang, and Thomas Barnes

Data sets

Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 Diarmuid Corr, Amber Leeson, Mal McMillan, Ce Zhang, and Thomas Barnes https://doi.org/10.5281/zenodo.5642755

Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product (http://earthexplorer.usgs.gov) E. Vermote, C. Justice, M. Claverie, and B. Franch https://doi.org/10.1016/j.rse.2016.04.008

Sentinel-2 and Landsat-8 data Google Cloud Storage https://cloud.google.com/storage/docs/public-datasets/

Model code and software

Sentinel-2 and Landsat-8 SGL and Channel Classifier Diarmuid Corr https://doi.org/10.5281/zenodo.4906097

olivierhagolle/LANDSAT-Download O. Hagolle https://github.com/olivierhagolle/LANDSAT-Download/tree/v1.0.0

olivierhagolle/Sentinel-download O. Hagolle https://github.com/olivierhagolle/Sentinel-2-download

vascobnunes/fetchLandsatSentinelFromGoogleCloud, V. Nunes https://github.com/vascobnunes/fetchLandsatSentinelFromGoogleCloud

Short summary

We identify 119 km² of meltwater area over West Antarctica in January 2017. In combination with Stokes et al., 2019, this forms the first continent-wide assessment helping to quantify the mass balance of Antarctica and its contribution to global sea level rise. We apply thresholds for meltwater classification to satellite images, mapping the extent and manually post-processing to remove false positives. Our study provides a high-fidelity dataset to train and validate machine learning methods.