NWSP: A Novel Indicator for Ocean–Land Interface Extraction Using Bathymetric LiDAR

Because of water-surface uncertainty, green lasers used in airborne bathymetric LiDAR cannot accurately detect the water surface, as they reflect near-water surface penetration (NWSP) into the water column. The existence of the NWSP of a green laser in water is not beneficial for high-accuracy depth measurements; however, it can be useful for ocean–land interface (OLI) extraction. In this study, novel ocean–land discrimination and interface extraction methods based on the NWSPs of green lasers are proposed. First, the NWSPs of different green laser channels are calculated and averaged to obtain a robust NWSP for each laser footprint. Second, a novel NWSP-based ocean–land discriminator is proposed based on the different characteristics of the NWSPs in land and ocean areas. Third, density-based spatial clustering of applications with noise algorithm is used to identify and correct the misclassified points of the NWSP-based ocean–land discriminator, and the OLIs are formed by connecting the land boundary points. Finally, the novel NWSP method is verified using a raw ABL data set collected via Optech coastal zone mapping and imaging LiDAR. The OLIs derived by waveform clustering are used as reference to evaluate the performance of the proposed NWSP method. OLI extraction based on the proposed NWSP method and the traditional point elevation method can reach accuracies of 1.9 and 4.8 m, respectively, in the research area. The proposed NWSP method provides a novel and convenient means for OLI extraction using the NWSPs of green lasers.