%0 Generic
%A de Roda Husman, Sophie
%A Lhermitte, Stef
%A Bolibar, Jordi
%A Hu, Zhongyang
%A Shukla, Shashwat
%A Izeboud, Maaike
%A van der Meer, Marijn
%A Long, David
%A Wouters, Bert
%D 2023
%T A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning
%U 
%R 10.4121/8a8934ef-9407-406f-8bfb-573eb182ec54.v1
%K Antarctica
%K Surface melt
%K Deep learning
%K U-Net
%K Ice shelves
%K High-resolution
%K Google Earth Engine
%X <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" (DOI to be announced!).&nbsp;</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).&nbsp;</p><p><br></p><p>The data is available for download in two formats:&nbsp;</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>
%I 4TU.ResearchData