Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition.
Melt pond UNet for the segmentation of the Arctic area, Aug-Sept 2005
The dataset contains aerial photographs of Arctic sea ice obtained during the Healy-Oden Trans Arctic Expedition (HOTRAX) captured from a helicopter between 5 August and 30 September, 2005. A total of 1013 images were captured, but only 100 images were labeled. The subset of 100 images was created exclusively for the purpose of segmenting sea ice, meltponds, and open water. Original images, labels, and code for segmentation are included in the above files. For dataset, refer site: Ivan Sudakow, Vijayan Asari, Ruixu Liu, & Denis Demchev. (2022). Melt pond from aerial photographs of the Healy–Oden Trans Arctic Expedition (HOTRAX) (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6602409
Manuscript: I. Sudakow, V. K. Asari, R. Liu and D. Demchev, "MeltPondNet: A Swin Transformer U-Net for Detection of Melt Ponds on Arctic Sea Ice," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 8776-8784, 2022, doi: 10.1109/JSTARS.2022.3213192.
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- Award ID(s):
- 2102906
- PAR ID:
- 10505008
- Publisher / Repository:
- NSF Arctic Data Center
- Date Published:
- Subject(s) / Keyword(s):
- Arctic Arctic meltpond segmentation
- Format(s):
- Medium: X
- Location:
- Arctic Data Center Catalog
- Sponsoring Org:
- National Science Foundation
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