The subglacial landscape and hydrology of Antarctica mapped from space

• Main Author: Wei Ji Leong
• Format: Thesis
• Language: unknown
• Published: 2021
• Subjects: Glaciology; Earth Sciences not elsewhere classified; Knowledge Representation and Machine Learning; Computer Vision; Pattern Recognition and Data Mining; Antarctica; remote sensing; deep learning; digital elevation model; ice sheet modelling; laser altimetry; subglacial hydrology; Siple Coast; School: School of Geography; Environment and Earth Sciences; Unit: Antarctic Research Centre; 040602 Glaciology; 049999 Earth Sciences not elsewhere classified; 080104 Computer Vision; 080109 Pattern Recognition and Data Mining; 170203 Knowledge Representation and Machine Learning; 960901 Antarctic and Sub-Antarctic Land and Water Management; 960306 Effects of Climate Change and Variability on Antarctic and Sub-Antarctic Environments (excl. Social Impacts); Degree Discipline: Physical Geography; Degree Level: Doctoral; Degree Name: Doctor of Philosophy; Antarctic; New Lakes; Pine Island Glacier; Siple; The Antarctic; West Antarctic Ice Sheet; Antarc*; Ice Sheet; Pine Island
• Online Access: https://doi.org/10.26686/wgtn.14956062.v1; https://figshare.com/articles/thesis/The_subglacial_landscape_and_hydrology_of_Antarctica_mapped_from_space/14956062

To narrow uncertainties in the Antarctic ice sheet's contribution to sea level rise, we present a collection of novel machine learning and automated satellite remote sensing methods which use ice surface observations to infer the subglacial nature of Antarctica. A super-resolution deep neural n...