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Airborne light detection and ranging (LiDAR) bathymetry (ALB) is an effective technique for seamless topobathymetric mapping in shallow water. A green laser beam spreads due to the forward scattering effect in the water column, which significantly influences the shape of seafloor reflected waveforms and further introduces bathymetric error. To quantitatively analyze the water column forward scattering effect, this study develops an ALB waveform simulator (ALBWS) based on the semianalytical Monte Carlo numerical simulation (MCNS) and Fournier–Forand (FF) phase function. The ALBWS is first verified by waveforms collected by the Chinese Academy of Sciences Mapper5000 and Optech Aquarius ALB systems around Yuanzhi Island in the South China Sea. Then, based on the ALBWS, the specific bathymetric error and received energy influenced by the forward scattering effect are quantitatively investigated under different system and environmental parameters. Please note that the bathymetric error is obtained by processing noiseless waveforms using the centroiding algorithm. The results indicate that, when the water quality varies from Type I (clear) to Type II (coastal) at a depth of 30 m, the bathymetric error due to the forward scattering effect alone increases from 40 cm to 70 cm, which no longer satisfies the requirements of IHO S44 Level 1a. To achieve more accurate bathymetric results, the ALB collection should be conducted in water areas where the particle size distribution slope is less than 3.91. Moreover, the ALB system can acquire higher bathymetric accuracy and received energy when the instantaneous field of view is approximately 3–11 times greater than the laser divergence angle. This study proposes a robust and flexible model to evaluate the scattering influence on ALB systems, which is not only beneficial for acquiring and processing ALB data but also helpful for optimizing the design of ALB system configurations.

The correlation between seafloor morphological features and biological complexity has been identified in numerous recent studies. This research focused on the potential for accurate characterization of coral reefs based on high‐resolution bathymetry from multiple sources. A standard deviation (STD) based method for quantitatively characterizing terrain complexity was developed that includes robust estimation to correct for irregular bathymetry and a calibration for the depth‐dependent variablity of measurement noise. Airborne lidar and shipborne sonar bathymetry measurements from Yuanzhi Island, South China Sea, were merged to generate seamless high‐resolution coverage of coral bathymetry from the shoreline to deep water. The new algorithm was applied to the Yuanzhi Island surveys to generate maps of quantitive terrain complexity, which were then compared to in situ video observations of coral abundance. The terrain complexity parameter is significantly correlated with seafloor coral abundance, demonstrating the potential for accurately and efficiently mapping coral abundance through seafloor surveys, including combinations of surveys using different sensors. Lidar and MBES data were combined to provide thorough coverage of coral reefRobust estimation and depth calibration were introduced to obtain an accurate estimate of terrain complexity in coral reef environmentsDerived terrain complexity index was found to be significantly correlated with in situ observation of coral abundance