评估基于主动和被动无人机的浅滩区测绘系统

R. Arav, C. Ressl, Robert Weiss, Thomas Artz, Gottfried Mandlburger
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摘要

摘要沿岸带在露出水面和沉入水下之间交替变化,对高分辨率特征描述提出了挑战。通常,其测绘分为低水位和高水位两种,每种水位都需要不同类型的测量仪器。这就导致了测绘产品在精度和分辨率上的不一致。最近,有人建议使用无人驾驶飞行器(UAV)进行摄影测量,这是一种可用且低成本的解决方案。然而,这种方法依赖于被动传感器,需要适当的环境条件,而且其绘制淹没区地图的能力有限。另外,基于无人机的地形测深激光扫描仪可以不受光照条件的限制,同时采集淹没区和暴露区的数据,并保持采集的灵活性。本文将评估此类系统在沿岸带的适用性。为此,我们在无人机上安装了地形和地形-测深激光雷达传感器,以绘制莱茵河沿岸地区的地图。绘制的点云与无人机摄影测量的点云进行了比较。对点间距、绝对精度和垂直偏移等方面进行了分析。为了提供可操作的建议,每次激光雷达扫描都是在不同的飞行高度下获取的,而摄影测量点云则是根据不同的外部信息配置进行地理参照的。为了评估河床模型,我们将地形测深激光雷达传感器获取的地表模型与多波束回声测深仪测量结果进行了比较。我们的分析表明,激光雷达点云的精确度几乎不受飞行高度的影响。另一方面,得出的河床高程显示出与水深成线性关系的偏差。
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Evaluation of Active and Passive UAV-Based Surveying Systems for Eulittoral Zone Mapping
Abstract. The eulittoral zone, which alternates between being exposed and submerged, presents a challenge for high-resolution characterization. Normally, its mapping is divided between low and high water levels, where each calls for a different type of surveying instrument. This leads to inconsistent mapping products, both in accuracy and resolution. Recently, uncrewed airborne vehicle (UAV) based photogrammetry was suggested as an available and low-cost solution. However, relying on a passive sensor, this approach requires adequate environmental conditions, while its ability to map inundated regions is limited. Alternatively, UAV-based topo-bathymetric laser scanners enable the acquisition of both submerged and exposed regions independent of lighting conditions while maintaining the acquisition flexibility. In this paper, we evaluate the applicability of such systems in the eulittoral zone. To do so, both topographic and topo-bathymetric LiDAR sensors were loaded on UAVs to map a coastal region along the river Rhein. The resulting point clouds were compared to UAV-based photogrammetric ones. Aspects such as point spacing, absolute accuracy, and vertical offsets were analysed. To provide operative recommendations, each LiDAR scan was acquired at different flying altitudes, while the photogrammetric point clouds were georeferenced based on different exterior information configurations. To assess the riverbed modelling, we compared the surface model acquired by the topo-bathymetric LiDAR sensor to multibeam echosounder measurements. Our analysis shows that the accuracies of the LiDAR point clouds are hardly affected by flying altitude. The derived riverbed elevation, on the other hand, shows a bias which is linearly related to water depth.
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