Noise reduction automation of LiDAR point clouds for modeling and representation of high voltage lines in a 3D virtual globe

Abstract

Due to the importance of electricity supply, electric companies must inspect their infrastructure in order to guarantee the reliability of the service. In this scenario, many companies use LiDAR technology for modeling the power line corridors and detect possible anomalies and risks. This process is quite expensive in terms of costs and human dependency so, maximizing the automation of the process is critical. In this paper, a method for reducing turbulence-noise in airborne LiDAR point clouds for a posterior visualization of a power line corridor in a virtual 3D-globe is presented. Based on an analysis performed against a set of point clouds that indicates that most noise is composed of a mass which follows the helicopter trajectory, the method attempts to integrate a noise reduction process using the distance between points and the helicopter as cleaning criterion. A comparison between a proposed variation of a classification method using a point cloud manually filtered and the same method variation but integrating the presented noise reduction method is carried out to validate the automation effectiveness. Finally, the resulting model is displayed using a virtual 3D-globe, easing analytical tasks.