A Method to Decompose Airborne LiDAR Bathymetric Waveform in Very Shallow Waters Combining Deconvolution With Curve Fitting

Airborne LiDAR bathymetry (ALB) is a useful technology for seamless topobathymetric mapping, offering high acquisition rate and point density. However, in very shallow waters (< 2 m depths), it is sometimes difficult to discriminate the bottom waveform from the water surface waveform because they are overlapped in total green signals. To make them separable, we narrow the widths of bottom and surface waveforms through deconvoluting the system impulse response function from the total received signal. Specifically, the mean surface waveform and Richardson–Lucy deconvolution (RLD) are used to determine the initial Gaussian parameters of bottom and surface waveforms. These parameters are further iteratively optimized using the Levenberg–Marquardt (LM) algorithm. A water LiDAR (Wa-LiD) simulated dataset and an Optech Aquarius dataset are used to assess the performance. In the Aquarius dataset, the proposed method can effectively identify bottom points in very shallow waters (with a recall rate >90%). In the simulated dataset, the root mean square error of the laser travel time between the estimated and truth values is 0.22 ns (corresponding to 2.5-cm slant range). The results indicate that the proposed method provides a new solution for filling the bathymetric gap in very shallow water, which is very essential for topobathymetry mapping.