Deep clustering in subglacial radar reflectance reveals subglacial lakes

DOI number:10.5194/tc-18-1241-2024

Affiliation of Author(s):中国科学技术大学地球和空间科学学院

Journal:The Cryosphere

Place of Publication:德国

Abstract:Ice-penetrating radar (IPR) imaging is a valuable tool for observing the internal structure and bottom of ice sheets. Subglacial water bodies, also known as subglacial lakes, generally appear as distinct, bright, flat, and continuous reflections in IPR images. In this study, we use available IPR images from the Gamburtsev Subglacial Mountains to extract one-dimensional reflector waveform features of the ice–bedrock interface. We apply a deep-learning method to reduce the dimension of the reflector features. An unsupervised clustering method is then used to separate different types of reflector

First Author:Sheng Dong

Co-author:Lei Fu, Xueyuan Tang,Zefeng Li, Xiaofei Chen

Indexed by:Journal paper

Correspondence Author:Lei Fu, Xueyuan Tang

Document Code:32

Discipline:Natural Science

First-Level Discipline:Geophysics

Document Type:SCI

Volume:18

Issue:3

Page Number:1241-1257

ISSN No.:1994-0424

Translation or Not:no

Date of Publication:2024-03-19

Links to published journals:https://doi.org/10.5194/tc-18-1241-2024