DynIceData: a gridded ice–water classification dataset at short-time intervals based on observations from multiple satellites over the marginal ice zone ...

• Main Authors: Huang, Lin, Qiu, Yubao, Li, Yang, Yu, Shuwen, Zhong, Wanyang, Dou, Changyong
• Format: Text
• Language: unknown
• Published: Taylor & Francis 2023
• Subjects: Medicine; Environmental Sciences not elsewhere classified; Chemical Sciences not elsewhere classified; Ecology; FOS Biological sciences; Biological Sciences not elsewhere classified; Inorganic Chemistry; FOS Chemical sciences; Beaufort Sea; Greenland; Greenland Sea; Kara Sea; Sea ice
• Online Access: https://dx.doi.org/10.6084/m9.figshare.23618701; https://tandf.figshare.com/articles/journal_contribution/DynIceData_a_gridded_ice_water_classification_dataset_at_short-time_intervals_based_on_observations_from_multiple_satellites_over_the_marginal_ice_zone/23618701

High-resolution observations of short-term changes in sea ice are critical to understanding ice dynamics and also provide important information used in advice to shipping, especially in the Arctic. Although individual satellite sensors provide periodic sea ice observations with spatial resolutions of tens of meters, information regarding changes that occur over short time intervals of minutes or hours is limited. In this study, a gridded ice–water classification dataset with a high temporal resolution was developed based on observations acquired by multiple satellite sensors in the Marginal Ice Zone (MIZ). This dataset – DynIceData – which combines Sentinel-1 Synthetic Aperture Radar (SAR) data with Gaofen-3 (GF-3) SAR and SDGSAT-1 thermal infrared imagery was used to obtain observations of the MIZ with a range of temporal resolutions ranging from minutes to tens of hours. The areas of the Arctic covered include the Kara Sea, Beaufort Sea, and Greenland Sea during the period from August 2021 to August 2022. ...