Glacier velocity is one of the crucial parameters in the research of glacier dynamics. Synthetic aperture radar (SAR), as an active microwave sensor, represents a common method to monitor glacier velocity. However, the changes of glacier surface could cause the data missing of glacier velocity due to incoherence. To meet the demand for glacier velocity monitoring, this paper employs the SAR images of Sentinel-1 in long time series and optical images of Sentinel-2 to investigate the velocity of Petermann glacier in 2021. Firstly, the time series of glacier velocity in the whole year of 2021 is obtained by using SAR images. The glacier velocity extracted from the optical image pairs is used as the initial value of the large missing part of the glacier velocity field. Then the spatiotemporal glacier velocity matrix is constructed and empirical orthogonal function (EOF) analysis is carried out. Among them, the glacier velocity is reconstructed by the glacier velocity estimation method based on confidence, and the complete glacier velocity time series is obtained by iterating to minimize the error of the reconstructed glacier velocity. Finally, the obtained time series of Petermann Glacier velocity in 2021 were statistically analyzed. The statistical results quantified the seasonal differences of Petermann Glacier. In addition, the analysis results show that the temporal and spatial variations of Petermann Glacier velocity are affected by topography and temperature.

中文翻译：

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使用多源遥感影像重建 Petermann 冰川速度时间序列


冰川速度是冰川动力学研究中的关键参数之一。合成孔径雷达 （SAR） 作为一种有源微波传感器，是监测冰川速度的常用方法。然而，冰川表面的变化可能会因不相干性而导致冰川速度数据缺失。为满足冰川速度监测需求，本文利用 Sentinel-1 的长时间序列 SAR 图像和 Sentinel-2 的光学图像，研究了 2021 年彼得曼冰川的速度。首先，利用 SAR 图像获取 2021 年全年冰川速度的时间序列;从光学图像对中提取的冰川速度用作冰川速度场中大缺失部分的初始值。然后构建冰川时空速度矩阵，并进行经验正交函数 （EOF） 分析。其中，采用基于置信度的冰川速度估计方法重建冰川速度，通过迭代获得完整的冰川速度时间序列，以最小化重建冰川速度的误差。最后，对获得的 2021 年 Petermann 冰川速度时间序列进行了统计分析。统计结果量化了彼得曼冰川的季节性差异。此外，分析结果表明，彼得曼冰川速度的时空变化受地形和温度的影响。