Two satellite datasets are used to characterize winter landfast first-year sea-ice (FYI), deformed FYI (DFYI) and multiyear sea-ice (MYI) roughness in the Canadian Arctic Archipelago (CAA): (1) optical Multi-angle Imaging SpectroRadiometer (MISR) and (2) synthetic aperture radar Sentinel-1. The Normalized Difference Angular Index (NDAI) roughness proxy derived from MISR, and backscatter from Sentinel-1 are intercompared. NDAI and backscatter are also compared to surface roughness derived from an airborne LiDAR track covering a subset of FYI and MYI (no DFYI). Overall, NDAI and backscatter are significantly positively correlated when all ice type samples are considered. When individual ice types are evaluated, NDAI and backscatter are only significantly correlated for DFYI. Both NDAI and backscatter are correlated with LiDAR-derived roughness (r = 0.71 and r = 0.74, respectively). The relationship between NDAI and roughness is greater for MYI than FYI, whereas for backscatter and ice roughness, the relationship is greater for FYI than MYI. Linear regression models are created for the estimation of FYI and MYI roughness from NDAI, and FYI roughness from backscatter. Results suggest that using a combination of Sentinel-1 backscatter for FYI and MISR NDAI for MYI may be optimal for mapping winter sea-ice roughness in the CAA.

中文翻译：

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使用 Sentinel-1 合成孔径雷达和多角度成像光谱辐射计表征加拿大北极群岛的冬季陆地海冰表面粗糙度

两个卫星数据集用于表征加拿大北极群岛 (CAA) 的冬季陆上第一年海冰 (FYI)、变形 FYI (DFYI) 和多年海冰 (MYI) 粗糙度：(1) 光学多角度成像SpectroRadiometer (MISR) 和 (2) 合成孔径雷达 Sentinel-1。来自 MISR 的归一化差异角指数 (NDAI) 粗糙度代理和来自 Sentinel-1 的反向散射进行了相互比较。NDAI 和反向散射也与来自机载 LiDAR 轨道的表面粗糙度进行了比较，该轨道覆盖了 FYI 和 MYI（无 DFYI）的子集。总体而言，当考虑所有冰型样本时，NDAI 和反向散射显着正相关。当评估单个冰类型时，NDAI 和反向散射仅与 DFYI 显着相关。NDAI 和反向散射都与 LiDAR 衍生的粗糙度相关（r= 0.71 和r= 0.74，分别）。MYI 的 NDAI 和粗糙度之间的关系大于 FYI，而对于反向散射和冰粗糙度，FYI 的关系大于 MYI。创建线性回归模型用于估计来自 NDAI 的 FYI 和 MYI 粗糙度，以及来自反向散射的 FYI 粗糙度。结果表明，将 Sentinel-1 反向散射用于 FYI 和 MISR NDAI 用于 MYI 可能是绘制 CAA 冬季海冰粗糙度的最佳选择。