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Quantifying streambank movement and topography using unmanned aircraft system photogrammetry with comparison to terrestrial laser scanning

机译:与地面激光扫描相比,使用无人飞机系统摄影测量法来量化河岸运动和地形

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Streambank movement is an integral part of geomorphic changes along river corridors and affects a range of physical, ecological, and socio-economic systems including aquatic habitat, water quality, and infrastructure. Various methods have been used to quantify streambank erosion, including bank pins, ground surveys, lidar, and analytical models, however, due to high-cost or labour intensive fieldwork these are typically feasible or appropriate only for site-specific studies. Advancements in unmanned aircraft systems (UAS) and photogrammetry provide opportunities for more rapid and economical quantification of streambank erosion and deposition at variable scales. This work assesses the performance of UAS-based photogrammetry for capturing topography of streambank surfaces and quantifying bank movement. UAS data are compared to terrestrial laser scanner (TLS) and GPS surveying from streambank sites located in Vermont that featured a variety of bank conditions and vegetation. Cross-sectional analysis of data from UAS and TLS revealed that the UAS reliably captured the bank surface within 0.2m of TLS and GPS surveys across all sites during leaf-off conditions. Mean error between UAS and TLS was only 0.11m in early spring conditions. Dense summer vegetation resulted in decreased accuracy and was a limiting factor in the ability of the UAS to capture the ground surface. At areas with observed bank movement, the change in cross-sectional area estimated using UAS data compared reliably to TLS survey for net cross-sectional changes greater than 3.5m(2), given a 10% error tolerance. At locations with smaller changes, error increased due to the effect of vegetation, georeferencing, and overhanging bank profiles. UAS-based photogrammetry shows significant promise for capturing bank topography and movement at fine resolutions in a flexible and efficient manner.
机译:河岸运动是沿河走廊地貌变化不可或缺的一部分,会影响包括水生生境,水质和基础设施在内的一系列物理,生态和社会经济系统。已经使用了多种方法来量化河岸侵蚀,包括河岸大头针,地面勘测,激光雷达和分析模型,但是,由于成本高昂或劳动强度大的实地考察,这些方法通常是可行的或仅适用于特定地点的研究。无人飞机系统(UAS)和摄影测量技术的进步为更快速,更经济地量化不同规模的河岸侵蚀和沉积提供了机会。这项工作评估了基于UAS的摄影测量技术在捕获河岸表面地形和量化河岸运动方面的性能。将UAS数据与位于佛蒙特州的河岸站点的地面激光扫描仪(TLS)和GPS测量进行比较,这些站点具有多种河岸条件和植被。对来自UAS和TLS的数据进行的横断面分析显示,UAS在下车情况下在所有站点的TLS和GPS调查的0.2m范围内可靠地捕获了河岸表面。在春季初期,UAS和TLS之间的平均误差仅为0.11m。夏季茂密的植被导致精度降低,并且是限制UAS捕获地面的能力的因素。在观察到堤岸运动的区域,在给定10%的误差容限的情况下,对于净横截面变化大于3.5m(2)的情况,使用UAS数据估算的横截面积变化与TLS测量可靠地比较。在变化较小的位置,由于植被,地理配准和悬垂河岸剖面的影响,误差增加。基于UAS的摄影测量法显示出以灵活有效的方式捕获银行地形和精细分辨率运动的巨大前景。

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