Abstract There is limited research focusing on Interferometric Synthetic Aperture Radar (InSAR) applications in the Great Lakes coastal wetlands with large water level fluctuations. In this study, we investigated the potential of using C-band SAR data to characterize marsh wetland and monitor water level changes along the coast of the Great Lakes. InSAR analysis was conducted using Radarsat-2 and Sentinel-1 data collected at Long Point, Ontario, Canada over the period of 2016–2018. Observations indicated that both backscattering coefficients and coherence from tall plants (e.g. cattail/Phragmites), short plants (e.g. grass), and water varied with different sensor modes (incidence angles and polarizations) in response to changes in phenology, disturbance, and water level. InSAR phase changes were closely related to fluctuations in water level and flow direction. We evaluated InSAR time series observations using measurements from water level loggers based on correlation and root mean square error (RMSE). It was found that correlation between InSAR measurements and water level changes in the field varied depending on the site, type of wetland vegetation, incidence angle and polarization. Although results from some sensor modes provided good correlation at a few locations, the low fringe rate and RMSE between 9 and 28 cm indicated that InSAR observations of water level changes were generally underestimated.

中文翻译：

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利用 C 波段 InSAR 观测表征五大湖盆地的沼泽湿地

摘要 干涉合成孔径雷达 (InSAR) 在水位波动较大的五大湖沿岸湿地中的应用研究有限。在这项研究中，我们调查了使用 C 波段 SAR 数据表征沼泽湿地和监测五大湖沿岸水位变化的潜力。InSAR 分析是使用 2016-2018 年期间在加拿大安大略省 Long Point 收集的 Radarsat-2 和 Sentinel-1 数据进行的。观察表明，高大植物（如香蒲/芦苇）、矮小植物（如草）和水的反向散射系数和相干性随着不同传感器模式（入射角和极化）的变化而变化，以响应物候、干扰和水位的变化. InSAR 相位变化与水位和流向的波动密切相关。我们使用基于相关性和均方根误差 (RMSE) 的水位记录仪的测量值来评估 InSAR 时间序列观测值。结果表明，InSAR 测量值与现场水位变化之间的相关性因地点、湿地植被类型、入射角和极化而异。尽管一些传感器模式的结果在少数位置提供了良好的相关性，但低边缘率和 9 至 28 cm 之间的 RMSE 表明 InSAR 对水位变化的观测普遍被低估。结果表明，InSAR 测量值与现场水位变化之间的相关性因地点、湿地植被类型、入射角和极化而异。尽管一些传感器模式的结果在少数位置提供了良好的相关性，但低边缘率和 9 至 28 cm 之间的 RMSE 表明 InSAR 对水位变化的观测普遍被低估。结果表明，InSAR 测量值与现场水位变化之间的相关性因地点、湿地植被类型、入射角和极化而异。尽管一些传感器模式的结果在少数位置提供了良好的相关性，但低边缘率和 9 至 28 cm 之间的 RMSE 表明 InSAR 对水位变化的观测普遍被低估。