Point Cloud Storage and Access on a Global Scale

Point Cloud data is a collection of sampled points representing the three dimensional X, Y, Z surface coordinates of an object typically generated by a scanning device or computer simulation. Light Detection and Ranging LiDAR systems are one example of geospatial point cloud generation using a range finding LASER to perform high resolution target mapping from aircraft or other vehicles. Modern LiDAR sensors generate Terabytes of point cloud data resulting in datasets too large for the current state of the art commercial software to Process, Exploit, Disseminate PED, and visualize. A service based approach needed to be developed to allow applications to utilize a streaming metaphor in order to access these massive datasets on a global scale. This approach eliminates the requirement for workstations to store Terabytes of data and permits sharing of intermediate products and visualizations. The goal of this effort was an initial design and implementation of a prototype clientserver design that provides an efficient, contiguous, and global approach to handling massive point clouds. Potential use of this technology includes Advanced Visualization, Object Segmentation, Classification, and Inflight Usage.