This research is part of an exciting advancement in the field of glaciology, driven by machine learning. The study focuses on crevasse detection, a highly relevant topic from a scientific and logistic perspective. Crevasses may aid surface meltwater to penetrate through the ice thus impacting ice dynamics. Crevasses also pose a logistical challenge for fieldwork in the polar regions. In this study, the authors are able to automatically spot grounded crevasses using a Convolutional Neural Networks algorithm. One of the focus areas is the Thwaites Glacier, an area that has recently been subject to extensive scientific research due to its importance for the stability of the West Antarctic Ice Sheet.