File Transformation for Effective Visualization of Large-Scale LAS Data

As LiDAR (Light Detection and Ranging) technology supports higher resolution and uses wider ranges of scans, the size of LAS files becomes larger, and more memory and processing are required to visualize the point cloud data. To address this problem, we propose a new method that provides sep- arate visualization files according to view distances using LOD (Level of Detail) for a large LAS file. In addition, by expressing point cloud data in a lightweight manner, less memory is needed to load data. In the experimental test, applying the proposed technique to high-resolution real LAS files, we show that the proposed method provides sufficient visualization quality while using small memory.