Fusing multiplatform topo-bathymetric point clouds based on a pseudo-grid model: A case study around Ganquan Island, South China sea

High-quality, full-coverage topographic bathymetric data is crucial for marine economic development and ecological environment protection. Due to the complex environment of land-sea transition zone, it is challenging to acquire comprehensive bathymetric topography using a single sensor. Multiplatform topographic bathymetric technology, such as airborne LiDAR bathymetry (ALB) and multibeam echo sounding (MBES), whose point clouds can be integrated to construct a complete model of land-sea transition zone. However, point cloud data from different sources may have certain differences in the digital description of the same target. Meanwhile, affected by factors such as registration error and sensor system error, there are data gaps in the registered point cloud, which hinders the subsequent reconstruction. To overcome these problems, a fusion method combining a pseudo-grid model is proposed to construct a high-quality, seamless topographic-bathymetric map. This paper’s contribution identifies non-overlapping ALB regions and generates anti-noise MBES simulated points (SPs) by constructing a pseudo-grid. Moreover, this paper focuses on establishing a point-to-SP model to eliminate the gaps and reduce the impact of registration errors on the fusion accuracy. To verify the effectiveness of the proposed method, four typical samples along with six reference samples exhibiting diverse features collected from Ganquan Island in the South China Sea are utilized in the experiment. The results show that the proposed algorithm can achieve ideal results in terms of the average root mean square error (RMSE) of the six reference samples, which is reduced from 0.41 m to 0.19 m. It is indicated that the true topography can be restored and the proposed method has advantages in accuracy and robustness.