Characterising the ice sheet surface in Northeast Greenland using Sentinel-1 SAR data

IF 2.8 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL
Qingying Shu, Rebecca Killick, A. Leeson, C. Nemeth, X. Fettweis, A. Hogg, David Leslie
{"title":"Characterising the ice sheet surface in Northeast Greenland using Sentinel-1 SAR data","authors":"Qingying Shu, Rebecca Killick, A. Leeson, C. Nemeth, X. Fettweis, A. Hogg, David Leslie","doi":"10.1017/jog.2023.64","DOIUrl":null,"url":null,"abstract":"\n 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.","PeriodicalId":15981,"journal":{"name":"Journal of Glaciology","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Glaciology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1017/jog.2023.64","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 1

Abstract

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.
利用Sentinel-1 SAR数据表征格陵兰东北部冰盖表面
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Glaciology
Journal of Glaciology 地学-地球科学综合
CiteScore
5.80
自引率
14.70%
发文量
101
审稿时长
6 months
期刊介绍: Journal of Glaciology publishes original scientific articles and letters in any aspect of glaciology- the study of ice. Studies of natural, artificial, and extraterrestrial ice and snow, as well as interactions between ice, snow and the atmospheric, oceanic and subglacial environment are all eligible. They may be based on field work, remote sensing, laboratory investigations, theoretical analysis or numerical modelling, or may report on newly developed glaciological instruments. Subjects covered recently in the Journal have included palaeoclimatology and the chemistry of the atmosphere as revealed in ice cores; theoretical and applied physics and chemistry of ice; the dynamics of glaciers and ice sheets, and changes in their extent and mass under climatic forcing; glacier energy balances at all scales; glacial landforms, and glaciers as geomorphic agents; snow science in all its aspects; ice as a host for surface and subglacial ecosystems; sea ice, icebergs and lake ice; and avalanche dynamics and other glacial hazards to human activity. Studies of permafrost and of ice in the Earth’s atmosphere are also within the domain of the Journal, as are interdisciplinary applications to engineering, biological, and social sciences, and studies in the history of glaciology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信