Characterising the ice sheet surface in Northeast Greenland using Sentinel-1 SAR data
Characterising the ice sheet surface in Northeast Greenland using Sentinel-1 SAR data
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DOI：
10.1017/jog.2023.64
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发表时间：
2023-08
影响因子：
3.4
通讯作者：
Qingying Shu;Rebecca Killick;A. Leeson;C. Nemeth;X. Fettweis;A. Hogg;David Leslie
中科院分区：
文献类型：
--
作者：
Qingying Shu;Rebecca Killick;A. Leeson;C. Nemeth;X. Fettweis;A. Hogg;David Leslie
格陵兰冰盖最近一半以上的质量损失及其对全球海平面上升的相关贡献可归因于地表融水径流的增加，其余部分则是冰裂和冰排放等动力过程的结果。因此，如果我们要充分了解过去的冰盖变化并对未来作出预测，那么量化冰盖融化的分布是很重要的。在本文中，我们提出了一种新的半经验方法，利用来自Sentinel-1卫星的高分辨率合成孔径雷达（SAR）后向散射数据来表征冰盖表面状况。我们将状态空间模型应用于格陵兰东北部的9个站点，以确定SAR后向散射的变化，并根据光学卫星图像和气象数据将这些变化归因于不同的地表类型。根据这一分析确定了一套标记冰盖融化状态的决策规则，并随后将其应用于以前未见过的地点。我们表明，我们的方法在(1)识别一些冰盖表面类型（如雪和暗冰）和(2)确定表面是否正在融化方面表现良好。Sentinel-1 SAR数据空间分辨率高；因此，在开发一种从这些数据中识别地表状态的方法时，我们提高了了解冰盖融化随时间和空间变化的能力。
Over half of the recent mass loss from the Greenland ice sheet, and its associated contribution to global sea level rise, can be attributed to increased surface meltwater runoff, with the remainder a result of dynamical processes such as calving and ice discharge. It is therefore important to quantify the distribution of melting on the ice sheet if we are to adequately understand past ice sheet change and make predictions for the future. In this article, we present a novel semi-empirical approach for characterising ice sheet surface conditions using high-resolution synthetic aperture radar (SAR) backscatter data from the Sentinel-1 satellite. We apply a state-space model to nine sites within North-East Greenland to identify changes in SAR backscatter, and we attribute these to different surface types with reference to optical satellite imagery and meteorological data. A set of decision-making rules for labelling ice sheet melting states are determined based on this analysis and subsequently applied to previously unseen sites. We show that our method performs well in (1) recognising some of the ice sheet surface types such as snow and dark ice and (2) determining whether the surface is melting or not melting. Sentinel-1 SAR data are of high spatial resolution; thus, in developing a method to identify the state of the surface from these data, we improve our capability to understand the variation of ice sheet melting across time and space.