Dynamic voxel modeling resolution based on quality assessments from LIDAR path tracing

Airborne LIDAR instruments are capable of delivering high density point clouds, but sampling is inherently uneven in both 2D and 3D space due to collection patterns as well as effects like occlusion. Taking full advantage of the detail available when creating 3D models therefore requires that resolution be adaptable to the amount of localized data. Voxel-based modeling of LIDAR has proven advantageous in many situations, but the traditional use of a fixed grid size prevents full realization of the potential resolution. Allowing voxel sizes to vary across the model using spatial subdivision techniques overcomes this limitation. An important part of this process is defining an appropriate limit of resolution for different sections of a model, and we incorporate information gained through tracing of LIDAR pulses to guide this decision process. Real-world data are used to demonstrate our results, and we show how dynamic resolution voxelization of LIDAR allows for both reduced storage requirements as well as improved modeling flexibility.