Large Quantities of Acoustic Multibeam Bathymetric Point Clouds: Organizing Method for Efficient Storage and Retrieval

To efficiently organize large quantities of acoustic multibeam bathymetric point clouds, this paper proposes an improved oriented quadtree-based method for establishing a data indexing structure stored on a hard disk. First, the spatial characteristics of the multibeam swath data are integrated into the traditional quadtree structure, resulting in an oriented quadtree for data organization. Then, the primary orientation of the root node’s bounding box, which reflects the main orientation of the swath, is consistently applied to all child nodes, eliminating the need to calculate the orientation for each individual child node by the conventional oriented quadtree. Finally, index files containing the point cloud offset, oriented bounding box, and child node information for root, child, and leaf nodes are designed and stored in external storage. Experimental results indicate that, in terms of tree construction time, although the traditional quadtree reduces time consumption by approximately 50% compared to the improved oriented quadtree, the improved oriented quadtree still achieves a 70% reduction in time consumption compared to the conventional oriented quadtree. Regarding point cloud retrieval, within the same retrieval range, the improved oriented quadtree achieves similar average retrieval times as the conventional oriented quadtree but reduces the maximum time consumption by approximately 20.83% compared to the traditional quadtree. Furthermore, by storing the constructed index in binary format on external storage, the space occupancy was reduced by 50%. The approach effectively organizes acoustic multibeam bathymetric point clouds, providing valuable insights for enhancing point cloud retrieval efficiency and reducing data memory usage.

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Publication Details

Journal
Remote Sensing
Published
2025-06-13
DOI
https://doi.org/10.3390/rs17122039
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00

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article

Large Quantities of Acoustic Multibeam Bathymetric Point Clouds: Organizing Method for Efficient Storage and Retrieval

Xiaodong Cui, Yi Huang, Tianyu Yun, Xianhai Bu et al.
Remote Sensing
Robotics and Sensor-Based Localization
article

Large Quantities of Acoustic Multibeam Bathymetric Point Clouds: Organizing Method for Efficient Storage and Retrieval

Xiaodong Cui, Yi Huang, Tianyu Yun, Xianhai Bu, Shan Dou, Jianxing Zhang, Yabing Zhu
article en

Abstract

To efficiently organize large quantities of acoustic multibeam bathymetric point clouds, this paper proposes an improved oriented quadtree-based method for establishing a data indexing structure stored on a hard disk. First, the spatial characteristics of the multibeam swath data are integrated into the traditional quadtree structure, resulting in an oriented quadtree for data organization. Then, the primary orientation of the root node’s bounding box, which reflects the main orientation of the swath, is consistently applied to all child nodes, eliminating the need to calculate the orientation for each individual child node by the conventional oriented quadtree. Finally, index files containing the point cloud offset, oriented bounding box, and child node information for root, child, and leaf nodes are designed and stored in external storage. Experimental results indicate that, in terms of tree construction time, although the traditional quadtree reduces time consumption by approximately 50% compared to the improved oriented quadtree, the improved oriented quadtree still achieves a 70% reduction in time consumption compared to the conventional oriented quadtree. Regarding point cloud retrieval, within the same retrieval range, the improved oriented quadtree achieves similar average retrieval times as the conventional oriented quadtree but reduces the maximum time consumption by approximately 20.83% compared to the traditional quadtree. Furthermore, by storing the constructed index in binary format on external storage, the space occupancy was reduced by 50%. The approach effectively organizes acoustic multibeam bathymetric point clouds, providing valuable insights for enhancing point cloud retrieval efficiency and reducing data memory usage.

Remote SensingVol. 17(12)
Chinese Academy of Sciences (CN), Ministry of Natural Resources (CN), Institute of Oceanology (CN), Ocean University of China (CN), Shandong University of Science and Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hainan Province
Openalex Percentile: Top 82%
Robotics and Sensor-Based Localization
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