摘要 11 次 GNNS（2006-2018）和 6 次无人机运动（2016-2018）在活动岩石冰川 Lazaun 上测量了流速，以更好地了解流动模式及其可能的原因。这个中等规模的活动岩石冰川位于奥茨塔尔阿尔卑斯山南部（意大利北部南蒂罗尔）的 Schnals/Senales 山谷的库尔兹拉斯/马索科尔托西侧。无人机数据用于通过图像相关技术生成位移图，分析地表下降和堆积过程，并根据阴影地貌图像解释地貌。即使基于 UAV 的水平位移分析不太精确，来自 UAV 的空间信息也更有助于理解岩石冰川流动模式，因为基于点的 GNSS 测量也是如此。由无人机数据的图像相关性得出的绝对水平位移的检测水平 (LoD) 范围在 0.05 和 0.15 m 之间。位移长度的比较表明，UAV 导出的位移矢量与 GNSS 测量的位移长度平均偏差约 ±0.05 m。当绝对位移较高时，位移方向的偏差较小，并且范围在绝对位移高于 0.3 m 的区域内，这取决于 0 到 4° 之间的数据质量。因此，在规划基于无人机的岩石冰川监测时，必须考虑可实现的数据精度、岩石冰川流速和时间跨度。GNSS 和 UVA 数据对岩石冰川速度的分析表明，计算出的水平平均速度从 2006 年的 2 毫米/天显着增加到 2012 年至 2016 年期间的 6 毫米/天，然后下降到 3-4 毫米/天的值。直到 2018 年。我们假设内部结构和水文地质是控制 Lazaun 岩石冰川流动机制的基本参数，特别是由存在于永久冻土体底部的碎屑和带状冰以及未冻结的地下水组成的剪切层- 剪切层和基岩之间的承载沉积层。我们得出结论，气候变暖导致融水渗入剪切层的增加，这是岩石冰川运动的主要驱动力。由于气候变暖，融水渗透增加导致流速增加，直到 2016 年。在岩石冰川前部附近观察到的厚度损失表明，永久冻土冰融化增加，导致过去几年永久冻土冰的大量损失。这种特别发生在岩石冰川下部的过程被认为是自 2017 年以来流速下降的原因。
Abstract Flow velocities were measured on the active rock glacier Lazaun by eleven GNNS (2006–2018) and six UAV campaigns (2016–2018) to better understand the flow pattern and its possible causes. This medium-sized, active rock glacier is located W of Kurzras/Maso Corto in the Schnals/Senales Valley in the southern Otztal Alps (South Tyrol, northern Italy). The UAV data were used to generate displacement maps by image correlation techniques, to analyse surface lowering and accumulation processes, and to interpret the geomorphology base on shaded relief images. The spatial information from UAV contributes much more to the understanding of the rock glacier flow patterns as the point based GNSS measurements even when the UAV based horizontal displacement analyses are less precise. The level of detection (LoD) for the absolute horizontal displacements derived by image correlation from UAV data ranges between 0.05 and 0.15 m. A comparison of the displacement lengths shows that the UAV derived displacement vectors deviate in average about ±0.05 m from the GNSS measured displacement lengths. The deviation in the displacement directions is smaller when the absolute displacement is higher and ranges in zones with an absolute displacement higher than 0.3 m in dependence to the data quality between 0 and 4°. Consequently, when planning a UAV based rock glacier monitoring, the achievable data accuracy, rock glacier flow velocity and the time span must be considered. Analyses of the rock glacier velocities from GNSS and UVA data show that the calculated horizontal mean velocity increased significantly from 2 mm/day in 2006 up to 6 mm/day in the period 2012 to 2016 and then decreased to values of 3–4 mm/day until 2018. We assume that internal structures and hydrogeology are essential parameters that control the flow mechanism of rock glacier Lazaun, particularly the shear horizon composed of debris and banded ice that is present at the base of the permafrost body, and the unfrozen, groundwater-bearing sediment layer between the shear horizon and the bedrock. We conclude that climate warming caused increased infiltration of meltwater into the shear horizon and that this is the main driving force for the movement of the rock glacier. Increased meltwater infiltration as result of climate warming caused an increase of flow velocity until 2016. The observed thickness loss near the front of the rock glacier indicates increased melting of permafrost ice resulting in a significant loss of permafrost ice during the last years. This process that particularly occurs in the lower part of the rock glacier is believed to be responsible for the decrease in flow velocity since 2017.
