Modeling the Water Bottom Geometry Effect on Peak Time Shifting in LiDAR Bathymetric Waveforms
Modeling the Water Bottom Geometry Effect on Peak Time Shifting in LiDAR Bathymetric Waveforms
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DOI：
10.1109/lgrs.2013.2292814
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发表时间：
2014-07-01
影响因子：
4.8
通讯作者：
Abady, Lydia
中科院分区：
文献类型：
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作者：
Bouhdaoui, Anis;Bailly, Jean-Stephane;Abady, Lydia
水深测量通常使用绿色LiDAR波形的水面和水底峰的位置来确定。已知水底峰特性对引起脉冲展宽的水底斜率敏感。然而，在不透明介质下方的足迹内的更复杂的底部几何形状的影响较少被理解。在这封信中，水底的几何形状的波形中的底峰的移位的影响进行了建模。为了简单起见，底部几何形状被建模为具有各种斜率的连续段的1D序列。波形中的峰值的位置被推断出使用传统的峰值检测过程对仿真波形。使用现有的Wa-LID波形模拟器模拟波形，该波形模拟器在本研究中进行了扩展，以考虑1D复杂的底部几何形状。根据卫星传感器的设计，使用各种水深、底坡和LiDAR足迹尺寸的实验设计用于波形模拟。幂律解释了作为足迹大小和水底斜率的函数的峰值时间偏移。峰移导致水深测量估计中的偏差，这是基于高达92%的真实水深的峰值检测。这种偏差也可以解释在各种经验研究中观察到的水深机载激光雷达调查的水深经常被低估。
Bathymetry is usually determined using the positions of the water surface and the water bottom peaks of the green LiDAR waveform. The water bottom peak characteristics are known to be sensitive to the bottom slope, which induces pulse stretching. However, the effects of a more complex bottom geometry within the footprint below semitransparent media are less understood. In this letter, the effects of the water bottom geometry on the shifting of the bottom peaks in the waveforms were modeled. For the sake of simplicity, the bottom geometry is modeled as a 1D sequence of successive contiguous segments with various slopes. The positions of the peaks in waveforms were deduced using a conventional peak detection process on simulated waveforms. The waveforms were simulated using the existing Wa-LID waveform simulator, which was extended in this study to account for a 1D complex bottom geometry. An experimental design using various water depths, bottom slopes, and LiDAR footprint sizes according to the design of satellite sensors was used for the waveform simulation. Power laws that explained the peak time shifting as a function of the footprint size and the water bottom slope were approximated. Peak shifting induces a bias in the bathymetry estimates that is based on a peak detection of up to 92% of the true water depth. This bias may also explain the frequent underestimation of the water depth from bathymetric airborne LiDAR surveys observed in various empirical studies.