A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning
doi: 10.4121/8a8934ef-9407-406f-8bfb-573eb182ec54
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.
- 2023-07-05 first online
- 2024-07-10 published, posted
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
DATA
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