Abstract
In this paper, an improved method based on a mixture of Gaussian and quadrilateral functions is presented to process airborne bathymetric LiDAR waveforms. In the presented method, the LiDAR waveform is fitted to a combination of three functions: one Gaussian function for the water surface contribution, another Gaussian function for the water bottom contribution, and a new quadrilateral function to fit the water column contribution. The proposed method was tested on a simulated dataset and a real dataset, with the focus being mainly on the performance of retrieving bottom response and water depths. We also investigated the influence of the parameter settings on the accuracy of the bathymetry estimates. The results demonstrate that the improved quadrilateral fitting algorithm shows a superior performance in terms of low RMSE and a high detection rate in the water depth and magnitude retrieval. What’s more, compared with the use of a triangular function or the existing quadrilateral function to fit the water column contribution, the presented method retrieved the least noise and the least number of unidentified waveforms, showed the best performance in fitting the return waveforms, and had consistent fitting goodness for all different water depths.
Highlights
Bathymetry is the measurement of underwater terrain, which is very important for a wide range of applications in hydrology, geomorphology, and meteorology
The advantage of the new quadrilateral fitting algorithm we present was evaluated on sets of airborne simulated light detection and ranging (LiDAR) waveforms and actual observed LiDAR waveform
To understand the capabilities of the improved quadrilateral fitting algorithm, which shows a better performance than the existing quadrilateral fitting algorithm and the triangular fitting algorithm in retrieving both the water magnitude and depth, we further studied the influence of the parameter settings on the three algorithms and tested the robustness of each algorithm by using a Monte Carlo method
Summary
Bathymetry is the measurement of underwater terrain, which is very important for a wide range of applications in hydrology, geomorphology, and meteorology. By using the mathematical approximation methods, the LiDAR bathymetric waveform can be fitted as a combination of mathematical functions These mathematical functions can represent the surface return, bottom return, and the water column response. It is important to develop suitable algorithms to fit the water column contribution in LiDAR waveforms, which can improve the accuracy of bathymetry retrieval, and obtain the optical properties and ecological parameters of water [30,31]. We propose a new quadrilateral fitting algorithm to process bathymetric LiDAR waveforms and obtain bathymetry where: (1) Gaussian functions are used to fit both the surface and bottom components, and a new quadrilateral function is used to fit the water column contribution;. We assess the fitting results of return waveforms and compute the root mean squared error (RMSE) between the fitting and true values of the amplitude of return waveforms by using different algorithms
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