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
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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。
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.
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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.
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