Bound block elimination algorithm for accurate visibility computation in point cloud analysis

Visual representations of viewshed analysis play a crucial role in urban planning, environmental conservation, and defense strategies by visually assessing impacts and guiding planning decisions. The simulation and modeling of environmental changes necessitate processing extensive datasets, including satellite photos, panoramic images, and point clouds generated from LiDAR scans. In response to these demands, the authors propose an approach tailored to address visibility challenges in environments with highly detailed and extensive point sets. The presented method identifies visible and occluded areas from a predetermined set of viewpoints, departing from previous approaches reliant on orthogonal maps. The proposed solution is evaluated by comparing the results obtained from a TIN (Triangulated Irregular Network) surface, a traditional ray-tracing approach, and a viewshed obtained from the Digital Surface Model (DSM). Additionally, the authors present a simulation by overlaying the obtained results with real landscape photographs, modeling the accurate visibility determination in the point cloud analysis process.