The underwater ancient town of Chunan is of great importance in archaeology and tourism. Hence, the efficient mapping and monitoring of the topographical changes in this town are essential. An attractive choice for the efficient mapping of underwater archaeology is the multibeam echo sounder system (MBES). The MBES has several advantages including noncontact survey, high precision, and low cost. In this study, the topographical changes of the ancient town under Qiandao Lake were quantitatively assessed on the basis of time-series MBES data collected in 2002 and 2015. First, the iterative closest point (ICP) algorithm was applied to eliminate the coordinate deviations between two point sets. Second, the robust estimation method was used to analyse the characterisations of the terrain variations of the town on the basis of the differences between the two matched point sets. Obvious topographical changes ranging from −0.89 m to 0.88 m were observed in a number of local areas in the town. On the global scale, the mean absolute value of the depth change in the town was merely 0.12 m, which indicated a weak global deformation pattern. The experiment proved the effectiveness of applying MBES data to analyse the deformation of the ancient town. The results are beneficial to the study of underwater ancient towns and the development of protection strategies.
Multi-beam echo sounders (MBESs) are characterized by the high resolution and high density of the sounding data. The processing of MBES bathymetry data is of special interest currently in marine surveying. The Combined Uncertainty and Bathymetry Estimator (CUBE) and surface filtering are the main MBES-processing algorithms for outliers. These algorithms involve five adjustable parameters; however, few studies have looked at parameter optimization. In this paper, a Parameter Group Optimization (PGO) method that determines the optimal parameters of CUBE and surface filtering based on the seafloor topographic characteristics of the survey area is presented. The method includes typical area selection, optimal grid resolution analysis, parameter group testing and batch processing, sounding and grid analysis. Raw MBES datasets from shallow-and deep-water survey areas (between 10 and 11000 m deep) are used to validate the proposed method. The results show that when the optimized parameters are used in the CUBE and filtering algorithm, the outliers are automatically eliminated; the processed bathymetry data is in good agreement with the bathymetry derived by a traditional manual processing method, while the processing efficiency can be improved by more than 8 times.INDEX TERMS Multi-beam bathymetry, CUBE algorithm, full ocean depth, parameter group optimization.
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