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Seasonal surface velocities of a Himalayan glacier derived by automated correlation of unmanned aerial vehicle imagery

机译:通过自动关联无人机图像得出的喜马拉雅冰川的季节性表面速度

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Debris-covered glaciers play an important role in the high-altitude water cycle in the Himalaya, yet their dynamics are poorly understood, partly because of the difficult fieldwork conditions. In this study we therefore deploy an unmanned aerial vehicle (UAV) three times (May 2013, October 2013 and May 2014) over the debris-covered Lirung Glacier in Nepal. The acquired data are processed into orthomosaics and elevation models by a Structure from Motion workflow, and seasonal surface velocity is derived using frequency cross-correlation. In order to obtain optimal surface velocity products, the effects of different input data and correlator configurations are evaluated, which reveals that the orthomosaic as input paired with moderate correlator settings provides the best results. The glacier has considerable spatial and seasonal differences in surface velocity, with maximum summer and winter velocities 6 and 2.5 m a(-1), respectively, in the upper part of the tongue, while the lower part is nearly stagnant. It is hypothesized that the higher velocities during summer are caused by basal sliding due to increased lubrication of the bed. We conclude that UAVs have great potential to quantify seasonal and annual variations in flow and can help to further our understanding of debris-covered glaciers.
机译:覆盖有碎屑的冰川在喜马拉雅山的高海拔水循环中起着重要作用,但对它们的动力学却知之甚少,部分原因是野外作业条件艰苦。因此,在本研究中,我们在尼泊尔被残骸覆盖的Lirung冰川上部署了3次无人飞行器(UAV)(2013年5月,2013年10月和2014年5月)。通过Motion的“结构”工作流将获取的数据处理为正交拼音和高程模型,并使用频率互相关来导出季节性表面速度。为了获得最佳的表面速度乘积,对不同输入数据和相关器配置的影响进行了评估,这表明将正马赛克作为输入与适度的相关器设置配对可提供最佳结果。冰川的表层速度具有明显的空间和季节差异,在舌的上部,夏季和冬季的最大速度分别为6和2.5 m a(-1),而下部则几乎停滞。据推测,夏季较高的速度是由于床的润滑增加而引起的基础滑动引起的。我们得出的结论是,无人机具有量化流量的季节性和年度变化的巨大潜力,并且可以帮助我们进一步了解覆盖有碎屑的冰川。

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