A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning

The dataset provided in this repository corresponds to the original data used in the publication by De Roda Husman et al. (2023) titled "A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning" (DOI to be announced!). <br>The dataset, named UMelt, contains a comprehensive surface melt record for all Antarctic ice shelves. It offers a high spatial resolution of 500 meters and a high temporal resolution of 12 hours, covering the period from 2016 to 2021. Our methodology relies on the utilization of a deep learning model known as U-Net, which integrates microwave remote sensing observations from three sources: Sentinel-1, Special Sensor Microwave Imager/Sounder (SSMIS), and Advanced Scatterometer (ASCAT). <br>The data is available for download in two formats: 1. "Timeseries": This format provides the data at a twice-daily resolution, allowing for detailed analysis over time.2. "MeltFraction": This format offers a yearly, summed product, providing a consolidated representation of the melt fraction.<br>Feel free to access and explore the dataset to gain valuable insights into surface melt dynamics on Antarctic ice shelves.