Melt Season Arctic Sea Ice Type Separability Using Fully and Compact Polarimetric C- and L-Band Synthetic Aperture Radar

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Aikaterini Tavri, Randall Scharien, Torsten Geldsetzer
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引用次数: 0

Abstract

Sea ice mapping using Synthetic Aperture Radar (SAR) in the melt season poses challenges, due to wet snow and melt ponds complicating sea ice type separability. To address this, we analyzed fully polarimetric (FP) and simulated compact polarimetric (CP) C- (RADARSAT-2) and L- (ALOS-2 PALSAR-2) band SAR, in the 2018 melt season in the Canadian Arctic Archipelago, for stage-wise separation of first year ice (FYI) and multiyear ice (MYI). SAR scenes at both near- (19.1–28.3°) and far- (35.8–42.1°) range incidence angles and coincident high-resolution optical scenes were used to assess the impact of surface melt ponds on separability within a landfast ice zone of diverse ice thickness. C-band provided better separability between FYI and MYI during pond onset, while L-band was superior during pond drainage due to MYI volumetric scattering. CP parameters matched FP performance across the melt season. HH and HV, commonly offered in ScanSAR mode for both frequencies, presented good separability during pond onset and drainage. Using both C-band and L-band SAR along with constraining incidence angle ranges, enhances sea ice type identification and separability. Our results can support ice type classification and seasonal stage detection for climate studies and enhance existing frameworks for ice motion vector retrievals.
利用全和紧凑型偏振C波段和l波段合成孔径雷达的融冰季节北极海冰类型可分离性
由于湿雪和融冰池使海冰类型的可分离性复杂化,在融冰季节使用合成孔径雷达(SAR)进行海冰制图带来了挑战。为了解决这个问题,我们分析了2018年加拿大北极群岛融化季节的全极化(FP)和模拟紧凑极化(CP) C- (RADARSAT-2)和L- (ALOS-2 PALSAR-2)波段SAR,以分阶段分离第一年冰(FYI)和多年冰(MYI)。利用近(19.1 ~ 28.3°)和远(35.8 ~ 42.1°)入射角SAR场景和同步高分辨率光学场景,评估了不同冰厚陆相冰带内地表融化池对可分性的影响。在池塘开始时,c波段在FYI和MYI之间具有较好的可分离性,而在池塘排水期间,由于MYI的体积散射,l波段具有较好的可分离性。CP参数与整个融化季节的FP性能相匹配。HH和HV通常在两种频率的ScanSAR模式下提供,在池塘开始和排水期间表现出良好的可分离性。同时使用c波段和l波段SAR,并对入射角范围进行约束,增强了海冰类型识别和可分性。我们的研究结果可以为气候研究的冰类型分类和季节阶段检测提供支持,并增强现有的冰运动矢量检索框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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