MODIS sea ice leads detections using a U-Net
View DatasetDescription
Sea ice leads are long and narrow sea ice fractures. Despite accounting for a small fraction of the Arctic surface area, leads play a critical role in the energy flux between the ocean and atmosphere. As the volume of sea ice in the Arctic has declined over recent decades, it is increasingly important to monitor the corresponding changes in sea ice leads. An approach described in Hoffman et al. 2021 uses artificial intelligence (AI) to detect sea ice leads using satellite thermal infrared window data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The AI used to detect sea ice leads in satellite imagery is a particular kind of convolutional neural network, a U-Net. The originally published dataset included only a small case study of results. Here, the dataset is expanded to include the daily detection of leads since 2002 for the season between November through April.
Citations (6)
- https://doi.org/10.5194/tc-17-2829-2023DataCite OpenAlex
Cited on 14 July 2023
Weight: 1.00
- https://doi.org/10.1080/20964471.2023.2230714DataCite OpenAlex
Cited on 03 July 2023
Weight: 1.00
Cited on 09 March 2023
Weight: 1.00
- https://doi.org/10.3390/rs14225763DataCite
Cited on 15 November 2022
Weight: 1.00
Cited on 02 September 2022
Weight: 1.00
- https://doi.org/10.3390/rs13224571DataCite MDC
Cited on 13 November 2021
Weight: 1.00
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Publication Details
Subfield
Atmospheric Science
Field
Earth and Planetary Sciences
Domain
Physical Sciences
Confidence Score
51%
Source
Scholar Data Model