An airborne LiDAR bathymetric waveform decomposition method in very shallow water: A case study around Yuanzhi Island in the South China Sea

Abstract

Airborne LiDAR bathymetry (ALB) is an active remote sensing technology for deriving underwater topography by detecting surface and bottom signals with a scanning green channel (532 nm) laser. However, due to the limitations of laser pulse duration and receiver bandwidth, the surface and bottom signal contributions are typically mixed in the green channel waveform in very shallow water (<2 m water depth). To address this issue, this paper proposes an ALB waveform decomposition method based on a signal resolution enhancement model and fractional differentiation mathematical tool in very shallow water. The initial Gaussian decomposition parameters of the surface and bottom are determined first. Then, the accurate surface and bottom positions are discriminated optimally using the Levenberg-Marquardt algorithm. Finally, the proposed method is verified by a green channel waveform dataset, which is obtained by the Mapper5000 ALB system of the Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences. The root mean square error (RMSE) of the surface position differences is 0.62 ns (that is, the ranging distance is 7.0 cm), which is less than the sampling frequency of 1 ns. Moreover, the mean correlation coefficient between the waveform processed results and the actual data is 0.9950. The presented method not only shows good accuracy and robustness in estimating the surface and bottom components from such mixed peaks but also contributes to improving the minimum penetration depth of the ALB system.