TY - DATA T1 - A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning PY - 2024/07/10 AU - Sophie de Roda Husman AU - Stef Lhermitte AU - Jordi Bolibar AU - Zhongyang Hu AU - Shashwat Shukla AU - Maaike Izeboud AU - Marijn van der Meer AU - David Long AU - Bert Wouters UR - DO - 10.4121/8a8934ef-9407-406f-8bfb-573eb182ec54.v2 KW - Antarctica KW - Surface melt KW - Deep learning KW - U-Net KW - Ice shelves KW - High-resolution KW - Google Earth Engine N2 - <p>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". </p><p><br></p><p>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). </p><p><br></p><p>The data is available for download in two formats: </p><p>1. "Timeseries": This format provides the data at a twice-daily resolution, allowing for detailed analysis over time.</p><p>2. "MeltFraction": This format offers a yearly, summed product, providing a consolidated representation of the melt fraction.</p><p><br></p><p>Feel free to access and explore the dataset to gain valuable insights into surface melt dynamics on Antarctic ice shelves.</p> ER -