Integrated Field and Synthetic Aperture Radar-Based Dataset for Arctic Lake Ice and Under-Ice Water Salinity Classification, Northern Alaska, 2024
收藏DataONE2025-04-03 更新2025-05-24 收录
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https://search.dataone.org/view/doi:10.18739/A25M6288G
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This dataset provides a comprehensive, field-validated Synthetic Aperture Radar (SAR) dataset for Arctic lake ice classification, with a particular emphasis on under-ice water salinity. It includes in situ measurements from 104 lakes (132 measurement sites) across northern Alaska collected in May 2024, capturing data on lake ice thickness, snow depth, lake depth, and specific conductance of unfrozen water beneath the ice. These field observations are integrated with multi-season Sentinel-1 SAR imagery from early winter (January) to late winter (May), along with additional geospatial datasets such as Interferometric Synthetic Aperture Radar (IfSAR)-derived elevation models and summer ice-off timing. The dataset enables improved differentiation of bedfast and floating ice lakes, particularly identifying lakes with brackish to saline water that were previously misclassified as bedfast ice lakes using traditional SAR-based remote sensing approaches. This resource supports research in permafrost stability, Arctic hydrology, climate change impacts, and winter water resource availability. This work was supported by grants from the U.S. National Science Foundation (OPP-2336164 and OPP-2336165) and the European Research Council project No. 951288 (Q-Arctic). Additional support was provided under a Broad Agency Announcement award from ERDC-CRREL, PE 0603119A.
本数据集提供一套经过野外验证的综合合成孔径雷达(Synthetic Aperture Radar,SAR)数据集,用于北极湖冰分类,尤其侧重于冰下水体盐度。该数据集包含2024年5月在阿拉斯加北部104个湖泊(共计132个测量点位)采集的原位实测数据,涵盖湖冰厚度、积雪深度、湖泊水深以及冰下未冻水的比电导率。上述野外实测数据已与多季哨兵一号(Sentinel-1)SAR影像进行融合,影像覆盖时段为初冬(1月)至晚冬(5月);此外还包含干涉合成孔径雷达(Interferometric Synthetic Aperture Radar,IfSAR)生成的高程模型、夏季冰融时间等多类地理空间数据集。本数据集可优化基岩附着冰湖泊与漂浮冰湖泊的区分精度,尤其能够识别出传统基于SAR的遥感方法曾误归类为基岩附着冰湖泊的微咸水至咸水湖泊。该数据集可为多年冻土稳定性、北极水文、气候变化影响以及冬季水资源可利用性等相关研究提供支撑。本研究得到美国国家科学基金会(U.S. National Science Foundation,项目编号OPP-2336164与OPP-2336165)以及欧洲研究委员会(European Research Council)项目No.951288(Q-Arctic)的资助,同时还获得了ERDC-CRREL根据《广泛机构公告》授予的项目PE 0603119A的额外支持。
创建时间:
2025-05-19



