Arctic sea ice cover product based on spaceborne synthetic aperture radar

The Sentinel-1 SAR based sea ice cover data in the Arctic. Based on the U-Net, one kind of architecture of deep learning, we developed a novel method of deriving sea ice cover information from spaceborne SAR data in high spatial resolution. Then we produced the relevant data product based on the ESA Sentinel-1 SAR data acquired in the Arctic using the proposed method. The Sentinel-1A and 1B SAR satellites have been extensively acquired the so-called extra-wide (EW) swath mode data in the polar regions since their launch in 2014 and 2016. The EW data have a wide coverage of approximately 400 by 400 km and a pixel size of 40 by 40 m. The twins can acquired SAR data by approximately 2500 scenes each month in the Arctic. Based on the above-mentioned method, we processed each S1 SAR image acquired in the Arctic and generated the sea ice cover data, which are in the standard CF 1.7 convention of NetCDF. Each S1 image corresponds to a NC file. The spatial resolution of the SAR-derived sea ice cover is 400 m. We have finished processing the S1 data acquired through the year 2019 to 2021 in the Arctic and upload the corresponding sea ice cover data. We are continuing to process the historical data and ongoing acquired data. Therefore, the published data will be updated often.

本数据集为基于哨兵一号（Sentinel-1）合成孔径雷达（Synthetic Aperture Radar，SAR）的北极海冰覆盖数据。本研究基于深度学习架构U-Net，提出了一种可从星载合成孔径雷达数据中提取高空间分辨率海冰覆盖信息的创新方法。随后，依托欧洲空间局（European Space Agency，ESA）在北极区域获取的哨兵一号SAR数据，结合上述方法生成了对应的海冰覆盖数据产品。哨兵一号A、B星分别于2014年、2016年发射升空，此后持续在极地区域获取俗称超宽幅（EW）条带模式的合成孔径雷达数据。该模式数据的单景覆盖范围约为400×400千米，像素尺寸为40×40米。这两颗双星在北极区域每月可获取约2500景合成孔径雷达数据。基于前述创新方法，本研究对所有在北极区域获取的哨兵一号SAR影像进行了处理，生成了符合NetCDF的CF 1.7标准规范的海冰覆盖数据，每景哨兵一号影像对应一个NC格式文件。该合成孔径雷达反演得到的海冰覆盖数据空间分辨率为400米。本研究已完成2019年至2021年北极区域哨兵一号SAR数据的处理，并上传了对应的海冰覆盖数据产品。目前团队仍在持续处理历史存档数据及最新获取的观测数据，因此已发布的数据集将定期更新。

搜集汇总

背景与挑战

背景概述

该数据集是基于Sentinel-1 SAR数据，利用U-Net深度学习架构生成的北极海冰覆盖产品，空间分辨率为400米，覆盖2019年至2021年，以NetCDF格式提供。数据集专注于极地区域的海冰监测，适用于地球科学研究。