A novel application of passive GPS signals (GNSS-R) picked up by cube satellites to detect the location and age of Antarctic sea ice. We conducted an intercomparison of explainable machine learning and deep learning (
tabnet) algorithms to understand which GNSS-R variables are used by the models with the highest ice detection skill. In collaboration with
Spire Global, thanks to the UK-Australia Spacebridge grant organised by
SmartSat CRC.