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Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

机译:浅河测深的高分辨率机载全波形激光雷达性能评估

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We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT) is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.
机译:我们用浅河中的高分辨率单波段机载LiDAR测深系统评估全波形LiDAR分解算法的性能。提出了一种连续小波变换(CWT)并将其应用于两个河流环境,并将结果与​​现有的回波检索方法进行了比较。还可以将LiDAR水深与独立的现场测量结果进行比较。在清澈和浑浊的水中,如果只有绿色LiDAR观测值可用,则CWT算法的性能优于其他方法。但是,水面的定义和水的浊度均会严重影响LiDAR水深观测的性能。结果表明,没有针对所有测深情况的最佳全波形处理算法。总的来说,最佳的处理策略可以确定水深,其中清水的标准偏差为14厘米,平均值为6厘米,较浑浊的水的平均值为16厘米,标准偏差为27厘米。

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