The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W10
https://doi.org/10.5194/isprs-archives-XLII-3-W10-807-2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-807-2020
08 Feb 2020
 | 08 Feb 2020

COMPARISON AND ANALYSIS OF THINNING METHODS FOR MULTI-BEAM SOUNDING DATA

R. J. Wang and C. P. Li

Keywords: Multi-beam Sounding System, Underwater Topography, Thinning, Water Depth

Abstract. Marine surveying and mapping is the basis of all marine development activities, and underwater topographic survey is one of the essential tasks of it. The multi-beam sounding system can give dozens or even hundreds of water depth values in the vertical plane perpendicular to the course at a time, and there is a lot of redundancy in these data. Efficient compression can make better use of water depth data, improve work efficiency, save system hardware resources, and facilitate rapid mapping and the construction of submarine topography model. Thinning requires an optimal balance between data accuracy and sampling density. In this paper, several commonly used thinning methods are selected and applied to the sounding data for experiments, and the application effects of different thinning methods are analyzed and compared. The results show that the mesh-based and system-based thinning methods are simple and efficient, and the results are more evenly distributed. It works well in areas with flat topography and low complexity. But in the area with large relief, the result of thinning may not take into account the topographical features, and the effect of topography representation is poor. The thinning method based on distance and elevation difference takes the elevation factor into account and has a better performance in preserving topography features. However, this method needs to search the points in a given range constantly, and it is inefficient to apply it to large amounts of data. The thinning method based on the Douglas-Peucker algorithm only considers the spatial relationship within each ping data, and the thinning result is not reasonable enough. This paper can provide reference for sounding data thinning.