Velocities within an icefall are typically the fastest within a glacier system and experience complex flow. The combination of convergent and fast flow, and steep slope generate a quickly changing and intensely fractured surface. This complicates velocity extraction from repeat satellite images, especially when common pattern matching procedures are used. In this study, we exploit the high temporal revisit of medium-resolution satellite images using a novel image matching technique, ensemble matching, making it possible to generate a high-resolution (30 m) velocity field from high-repeat image sequences despite challenging image conditions. We demonstrate this technique for the first time in the glaciology domain using repeat Sentinel-2 optical data over the famous Khumbu icefall, situated on the southern slopes of Mount Everest. Estimates of velocity go just over 1 m d−1, which is slower than summer velocities from noisy single pair image matching. This icefall is frequently crossed by high-altitude mountaineers who use a route confined by fixed ropes and ladders set out every season. The mountain climbers typically record their trajectory on their personal satellite navigation device. We use such volunteered geographic information to verify our velocity estimates, confirming our underestimation with ensemble matching. Besides unprecedented remotely sensed surface velocities over the icefall, we also note that the generated velocity field can aid with the planning of a safe passage through this icefall.

中文翻译：

---

用于测量快速变化的冰流的重复卫星图像的整体匹配，并通过珠穆朗玛峰昆布冰瀑上的登山者轨迹进行了验证

冰瀑内的速度通常是冰川系统内最快的，并且会经历复杂的流动。汇流与快流与陡坡相结合，形成了快速变化和强烈断裂的表面。这使得从重复卫星图像中提取速度变得复杂，尤其是在使用常见的模式匹配程序时。在这项研究中，我们利用一种新的图像匹配技术，集成匹配，利用中分辨率卫星图像的高时间重访，使得尽管具有挑战性的图像，仍然可以从高重复图像序列中生成高分辨率 (30 m) 速度场状况。我们在位于珠穆朗玛峰南坡的著名 Khumbu 冰瀑上使用重复的 Sentinel-2 光学数据首次在冰川学领域展示了这项技术。-1，这比来自嘈杂的单对图像匹配的夏季速度要慢。高海拔登山者经常穿越这个冰瀑，他们使用的路线由每个季节设置的固定绳索和梯子限制。登山者通常在他们的个人卫星导航设备上记录他们的轨迹。我们使用这些自愿提供的地理信息来验证我们的速度估计，通过集合匹配确认我们的低估。除了史无前例的在冰瀑上遥感地表速度外，我们还注意到生成的速度场可以帮助规划通过该冰瀑的安全通道。