Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams

Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams
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评估 Apple iPhone LiDAR 对粗层溪流中地形和粗糙度元素的测量

DOI:
10.1080/24705357.2023.2204087
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发表时间:
2023
期刊:
Journal of Ecohydraulics
影响因子:
--
通讯作者:
Tonina, Daniele
Tonina, Daniele
中科院分区:
--
文献类型:
--
作者:
Monsalve, Angel;Yager, Elowyn M.;Tonina, Daniele

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高分辨率的地形数据是必要的,以了解底栖生境,量化过程中的水-沉积物界面,并支持计算流体动力学模型的表面和潜流水力学。在河流系统中,这些数据通常使用传统的测量方法(全站仪、DGPS等)收集,空中或地面激光扫描和摄影测量。最近,手持式测量设备已经迅速获得普及,部分原因是其处理能力、价格、尺寸和多功能性。其中一种设备是iPhone激光雷达,它可以在精度和易用性之间取得良好的平衡,是传统测量工具的潜在替代品。在这里,我们评估了LiDAR传感器的准确性和基于使用iPhone相机收集的照片的运动结构(SfM)方法。我们将LiDAR和SfM高程与高精度激光扫描仪的高程进行了比较,这些激光扫描仪用于实验性粗糙的水处理砾石床通道,具有巨石状结构。我们观察到LiDAR和SfM方法都捕获了整体河床形态,并检测到大尺度(Hs≥ 15 cm)和宏观尺度(5 cm ≤Hs< 15 cm)的地形变化(Hs,粗糙度)。SfM技术还捕获了小尺度(Hs<5cm)粗糙度,而LiDAR始终将其简化为± 3.7 mm的误差。
High resolution topographic data are necessary to understand benthic habitat, quantify processes at the water-sediment interface, and support computational fluid dynamics models for both surface and hyporheic hydraulics. In riverine systems, these data are typically collected using traditional surveying methods (total station, DGPS, etc.), airborne or terrestrial laser scanning, and photogrammetry. Recently, handheld surveying equipment has been rapidly acquiring popularity in part due to its processing capacity, price, size, and versatility. One such device is the iPhone LiDAR, which could have a good balance between precision and ease of use and is a potential replacement for conventional measuring tools. Here, we evaluated the accuracy of the LiDAR sensor and a Structure from Motion (SfM) method based on photos collected using the iPhone Cameras. We compared the LiDAR and SfM elevations to those from a high-precision laser scanner for an experimental rough water-worked gravel-bed channel with boulder-like structures. We observed that both the LiDAR and SfM methods captured the overall streambed morphology and detected large (Hs≥ 15 cm) and macro (5 cm ≤Hs< 15 cm) scales of topographic variations (Hs, roughness). The SfM technique also captured small scale (Hs<5cm) roughness whereas the LiDAR consistently simplified it with errors of ∼3.7 mm.
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