%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 2024 %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.v2 %K Antarctica %K Surface melt %K Deep learning %K U-Net %K Ice shelves %K High-resolution %K Google Earth Engine %X

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". 


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). 


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.


Feel free to access and explore the dataset to gain valuable insights into surface melt dynamics on Antarctic ice shelves.

%I 4TU.ResearchData