Convolutional neural network training dataset and results of AWI-ICENet1 retracker

• Main Author: Helm, Veit
• Format: Dataset
• Language: English
• Published: PANGAEA 2024
• Subjects: AI-CORE; altimetry; Antarctica; Artificial Intelligence for Cold Regions; Binary Object; Binary Object (File Size); CNN_AWI-ICENet1_CY_LRM_ANT; CNN_AWI-ICENet1_CY_LRM_GRE; CNN_AWI-ICENet1_training; DATE/TIME; elevation change; File content; Greenland; Location; netCDF file; netCDF file (File Size); Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; simulated Cryosat-2 waveforms; SPP1158; Antarctic; Arctic; The Antarctic; Antarc*; Ice Sheet; Sea ice
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.964596; https://doi.org/10.1594/PANGAEA.964596

This data set include the simulated and corresponding reference data in binary format used for the training of the AWI-ICENet1 retracker algorithm, which is a convolutional neural network (CNN). The simulation is carried out at 1000 randomly selected locations spread over the Antarctic ice sheet. At...