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Storage method of multi-channel lidar data based on tree structure.

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This study introduces a novel tree structure method for efficient multi-channel lidar data storage. This approach enhances storage capacity and retrieval speed for lidar systems.

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Area of Science:

  • Geospatial technology
  • Data science
  • Computer engineering

Background:

  • Multi-channel lidar systems generate large, high-dimensional data volumes requiring efficient real-time storage.
  • Traditional lidar data storage methods struggle to meet the demands of fast acquisition speeds and large datasets.

Purpose of the Study:

  • To develop a novel and efficient data storage method for multi-channel lidar data.
  • To improve storage capacity and retrieval speed for lidar datasets.
  • To enhance the practicality and data storage utilization of multi-channel lidar systems.

Main Methods:

  • A novel approach utilizing tree structures, adjacency linked lists, and binary data storage principles.
  • Construction of a tree structure based on the four-dimensional data of multi-channel lidar.
  • Development of a data retrieval method for multi-channel lidar data files.

Main Results:

  • The proposed tree structure approach significantly saves storage capacity.
  • Retrieval speed for multi-channel lidar data is demonstrably improved.
  • Enhanced data storage utilization and system practicality were achieved.

Conclusions:

  • The novel tree structure method effectively addresses the challenges of multi-channel lidar data storage.
  • The system meets the requirements for efficient storage and rapid retrieval of lidar data.
  • This approach improves the overall efficiency and usability of multi-channel lidar systems.