利用l波段干涉合成孔径雷达(InSAR)估算积雪和消融

IF 4.4 2区 地球科学 Q1 GEOGRAPHY, PHYSICAL Cryosphere Pub Date : 2023-05-12 DOI:10.5194/tc-17-1997-2023
John M Tarricone, R. Webb, H. Marshall, A. Nolin, F. Meyer
{"title":"利用l波段干涉合成孔径雷达(InSAR)估算积雪和消融","authors":"John M Tarricone, R. Webb, H. Marshall, A. Nolin, F. Meyer","doi":"10.5194/tc-17-1997-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent (SWE). The goal was to develop a more comprehensive understanding of where and when L-band InSAR can provide SWE change estimates, allowing the snow community to leverage the upcoming NASA–ISRO (NASA–Indian Space Research Organization) SAR (NISAR) mission. Our study analyzed three InSAR image pairs from the Jemez Mountains, NM, between 12 and 26 February 2020. We developed a snow-focused multi-sensor method that uses UAVSAR InSAR data synergistically with optical fractional snow-covered area (fSCA) information. Combining these two remote sensing datasets allows for atmospheric correction and delineation of snow-covered pixels within the radar swath. For all InSAR pairs, we converted phase change values to SWE change estimates between the three acquisition dates. We then evaluated InSAR-derived retrievals using a combination of fSCA, snow pits, meteorological station data, in situ snow depth sensors, and ground-penetrating radar (GPR). The results of this study show that repeat-pass L-band InSAR is effective for estimating both snow accumulation and ablation with the proper measurement timing, reference phase, and snowpack conditions.\n","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)\",\"authors\":\"John M Tarricone, R. Webb, H. Marshall, A. Nolin, F. Meyer\",\"doi\":\"10.5194/tc-17-1997-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent (SWE). The goal was to develop a more comprehensive understanding of where and when L-band InSAR can provide SWE change estimates, allowing the snow community to leverage the upcoming NASA–ISRO (NASA–Indian Space Research Organization) SAR (NISAR) mission. Our study analyzed three InSAR image pairs from the Jemez Mountains, NM, between 12 and 26 February 2020. We developed a snow-focused multi-sensor method that uses UAVSAR InSAR data synergistically with optical fractional snow-covered area (fSCA) information. Combining these two remote sensing datasets allows for atmospheric correction and delineation of snow-covered pixels within the radar swath. For all InSAR pairs, we converted phase change values to SWE change estimates between the three acquisition dates. We then evaluated InSAR-derived retrievals using a combination of fSCA, snow pits, meteorological station data, in situ snow depth sensors, and ground-penetrating radar (GPR). The results of this study show that repeat-pass L-band InSAR is effective for estimating both snow accumulation and ablation with the proper measurement timing, reference phase, and snowpack conditions.\\n\",\"PeriodicalId\":56315,\"journal\":{\"name\":\"Cryosphere\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2023-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cryosphere\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/tc-17-1997-2023\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cryosphere","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/tc-17-1997-2023","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 4

摘要

摘要雪是美国西部和全球许多地区的重要水资源。然而,我们通过卫星遥感准确测量和监测雪量变化的能力,特别是其水当量,仍然是一个挑战。为了应对这些挑战,美国宇航局启动了SnowEx计划,这是一项为期多年的努力,旨在解决积雪遥感方面的知识差距。在SnowEx 2020期间,无人飞行器合成孔径雷达(UAVSAR)团队获得了l波段干涉合成孔径雷达(InSAR)数据时间序列,以评估重复通过l波段InSAR跟踪雪水当量(SWE)变化的能力和局限性。目标是更全面地了解l波段InSAR何时何地可以提供SWE变化估计,从而使雪界能够利用即将到来的NASA-ISRO (nasa -印度空间研究组织)SAR (NISAR)任务。我们的研究分析了2020年2月12日至26日期间来自NM Jemez山脉的三对InSAR图像。我们开发了一种积雪聚焦多传感器方法,该方法将UAVSAR InSAR数据与光学分数积雪覆盖面积(fSCA)信息协同使用。结合这两个遥感数据集,可以在雷达带内进行大气校正和雪覆盖像素的圈定。对于所有InSAR对,我们将三个采集日期之间的相变值转换为SWE变化估计值。然后,我们使用fSCA、雪坑、气象站数据、原位雪深传感器和探地雷达(GPR)的组合来评估insar衍生的检索结果。研究结果表明,在适当的测量时间、参考相位和积雪条件下,重复通过l波段InSAR可以有效地估计积雪和消融。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)
Abstract. Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent (SWE). The goal was to develop a more comprehensive understanding of where and when L-band InSAR can provide SWE change estimates, allowing the snow community to leverage the upcoming NASA–ISRO (NASA–Indian Space Research Organization) SAR (NISAR) mission. Our study analyzed three InSAR image pairs from the Jemez Mountains, NM, between 12 and 26 February 2020. We developed a snow-focused multi-sensor method that uses UAVSAR InSAR data synergistically with optical fractional snow-covered area (fSCA) information. Combining these two remote sensing datasets allows for atmospheric correction and delineation of snow-covered pixels within the radar swath. For all InSAR pairs, we converted phase change values to SWE change estimates between the three acquisition dates. We then evaluated InSAR-derived retrievals using a combination of fSCA, snow pits, meteorological station data, in situ snow depth sensors, and ground-penetrating radar (GPR). The results of this study show that repeat-pass L-band InSAR is effective for estimating both snow accumulation and ablation with the proper measurement timing, reference phase, and snowpack conditions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Cryosphere
Cryosphere GEOGRAPHY, PHYSICAL-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
8.70
自引率
17.30%
发文量
240
审稿时长
4-8 weeks
期刊介绍: The Cryosphere (TC) is a not-for-profit international scientific journal dedicated to the publication and discussion of research articles, short communications, and review papers on all aspects of frozen water and ground on Earth and on other planetary bodies. The main subject areas are the following: ice sheets and glaciers; planetary ice bodies; permafrost and seasonally frozen ground; seasonal snow cover; sea ice; river and lake ice; remote sensing, numerical modelling, in situ and laboratory studies of the above and including studies of the interaction of the cryosphere with the rest of the climate system.
期刊最新文献
Greenland and Canadian Arctic ice temperature profiles database The stability of present-day Antarctic grounding lines – Part 2: Onset of irreversible retreat of Amundsen Sea glaciers under current climate on centennial timescales cannot be excluded The stability of present-day Antarctic grounding lines – Part 1: No indication of marine ice sheet instability in the current geometry Phase-field models of floe fracture in sea ice Relevance of warm air intrusions for Arctic satellite sea ice concentration time series
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1