Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5347-2024
https://doi.org/10.5194/tc-18-5347-2024
Research article
 | 
21 Nov 2024
Research article |  | 21 Nov 2024

Using deep learning and multi-source remote sensing images to map landlocked lakes in Antarctica

Anyao Jiang, Xin Meng, Yan Huang, and Guitao Shi

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Short summary
Landlocked lakes are crucial to the Antarctic ecosystem and sensitive to climate change. Limited research on their distribution prompted us to develop an automated detection process using deep learning and multi-source satellite imagery. This allowed us to accurately determine the landlocked lake open water (LLOW) area in Antarctica, generating high-resolution time series data. We find that the changes in positive and negative degree days predominantly drive variations in the LLOW area.
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