Performance measurements on the FinisTerrae-II supercomputer were possible thanks to the CESGA (Galician supercomputing center).

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<p><strong>Abstract.</strong> Light Detection and Ranging (LiDAR) is nowadays one of the most used tools to obtain geospatial data. In this paper, a method to detect and characterise power lines of both high and low voltage and their surroundings from 3D LiDAR point clouds exclusively is proposed. First, to identify points of the power lines a global search of candidate points is carried out based on the height of each point compared to its neighbours. Then, the Hough Transform (HT) is applied on the set of candidate points to extract the catenaries that belong to each power line, allowing the identification of each conductor individually. Finally, conductors located on the same power line are grouped, their geometric characteristics analysed, and the quantitative features of the surroundings are computed. A very high accuracy of power line classification is reached with these methods, while the computational time is optimised by efficient memory usage and parallel implementation of the code.</p>