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High-accuracy UAV photogrammetry of ice sheet dynamics with no ground control

机译:无需地面控制的高精度无人飞行器冰盖动力学摄影测量

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Unmanned aerial vehicles (UAVs) and structure from motion with multi-view stereo (SfM–MVS) photogrammetry are increasingly common tools for geoscience applications, but final product accuracy can be significantly diminished in the absence of a dense and well-distributed network of ground control points (GCPs). This is problematic in inaccessible or hazardous field environments, including highly crevassed glaciers, where implementing suitable GCP networks would be logistically difficult if not impossible. To overcome this challenge, we present an alternative geolocation approach known as GNSS-supported aerial triangulation (GNSS-AT). Here, an on-board carrier-phase GNSS receiver is used to determine the location of photo acquisitions using kinematic differential carrier-phase positioning. The camera positions can be used as the geospatial input to the photogrammetry process. We describe the implementation of this method in a low-cost, custom-built UAV and apply the method in a glaciological setting at Store Glacier in western Greenland. We validate the technique at the calving front, achieving topographic uncertainties of ±0.12 m horizontally ( ~ 1.1 × the ground sampling distance) and ±0.14 m vertically ( ~ 1.3 × the ground sampling distance), when flying at an altitude of ~?450 m above ground level. This compares favourably with previous GCP-derived uncertainties in glacial environments and allows us to apply the SfM–MVS photogrammetry at an inland study site where ice flows at 2?m?day sup?1/sup and stable ground control is not available. Here, we were able to produce, without the use of GCPs, the first UAV-derived velocity fields of an ice sheet interior. Given the growing use of UAVs and SfM–MVS in glaciology and the geosciences, GNSS-AT will be of interest to those wishing to use UAV photogrammetry to obtain high-precision measurements of topographic change in contexts where GCP collection is logistically constrained.
机译:无人飞行器(UAV)和多视立体运动(SfM–MVS)摄影测量的运动结构越来越成为地球科学应用的工具,但是如果没有密集且分布良好的地面网络,最终产品的精度可能会大大降低控制点(GCP)。这在难以接近或危险的野外环境(包括高度裂缝的冰川)中是有问题的,在该环境中,即使不是不可能,实施合适的GCP网络在后勤上也将很困难。为了克服这一挑战,我们提出了另一种地理定位方法,称为GNSS支持的空中三角测量(GNSS-AT)。在此,机载载波相位GNSS接收器用于通过运动学差分载波相位定位来确定照片采集的位置。相机位置可用作摄影测量过程的地理空间输入。我们描述了这种方法在低成本,定制的无人机中的实现方式,并将该方法应用于格陵兰西部Store Glacier的冰川环境中。我们在产犊前线对该技术进行了验证,当在〜?450的高度飞行时,水平不确定度为水平±0.12 m(〜1.1×地面采样距离)和垂直±0.14 m(≥1.3×地面采样距离) m高于地面。与以前在冰川环境中由GCP得出的不确定性相比,它具有优势,并允许我们将SfM-MVS摄影测量法应用于内陆研究地点,那里冰在2?m?day ?1 流动,并且地面控制稳定无法使用。在这里,我们能够在不使用GCP的情况下产生冰盖内部的第一个无人机衍生的速度场。鉴于冰川和地球科学中越来越多地使用UAV和SfM–MVS,希望在GCP收集受到逻辑约束的情况下,希望使用UAV摄影测量技术来获得高精度地形测量的人们将对GNSS-AT感兴趣。

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