Application of the Properties of an Organized Point Cloud in an Octree in Solving Geodetic Tasks

Abstract

The study discusses the problems associated with using organized arrays of points in geodetic tasks The aim of the work was to develop approaches to using the octree as a format for storing terrain data obtained during aerial photography and aerial laser scanning. All stages of creating a digital model of a territorial object require processing a large amount of data. The study presents an approach to using the octree structure to work with this data. Organized point clouds in the octree were used to solve geodetic tasks by speeding up the process of searching for the nearest points. The octree was a data structure that divided the space into octagonal subdomains, each of which contained a certain number of points. To solve geodetic tasks using an octree, the tree itself was first built, after which the nearest points to a given point were searched. This process was accelerated due to the fact that organized point clouds make it possible to exclude a set of points that are far from the starting point and cannot be its nearest neighbors. Thus, the use of organized point clouds in an octree is an effective approach to storing and compressing spatial data without loss of accuracy in solving geodetic tasks.