Potential analyses of LiDAR-based automatic powerline detection algorithms
Keywords:Powerline detection, LiDAR, Point cloud, Aerial systems, Disaster monitoring
Powerlines are utilized for distributing electricity for household use, industry, healthcare purposes and etc. The detection of powerlines is an important topic in object detection studies. In addition, overgrown trees in dense forest regions may pose a risk for powerlines positioned in these regions and even may cause forest fires if unattended. So, it is also important in the scope of disaster monitoring research and studies. Light detection and ranging (LiDAR) systems are utilized for the detection of powerlines in urban regions and forests with the ability to obtain high-resolution point cloud data. Also, with the operation principle based on active remote sensing aerial LiDAR systems with multi-return capability can be used to obtain information about forest understory and is more effective compared to optical systems in this context. In this study, aerial LiDAR point cloud data of an urban region was utilized for the automatic detection of powerlines. For the automatic detection of powerlines, Robust Railroad Infrastructure Detection Framework which was developed by Eötvös Loránd University (ELTE) Geoinformatics Laboratory was utilized and five algorithms including Above, AngleAbove, AngleGroundAbove, VoronoiAbove, and VoronoiGroundAbove are applied separately on LiDAR point cloud data. When results are analyzed visually AngleAbove gave the best results in powerline detection.
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