Vegetation interference with power lines is one of the most common causes of electrical outages of distribution systems and have a high potential of causing vast wildfires when combined with dry and hot weather under high wind conditions. The paper highlights the results of a case study of an approach using automated monitoring of vegetation and degree of its interference with power lines. It is based on the utilization of the so-called point clouds, which can be collected by terrestrial or airborne laser scanners or generated from stereoscopic images taken by drones. The approach allows the estimation of the location of the power lines in space and also allows the identification of the location of vegetation in the vicinity of the power lines. Sequential repetitive collections of the point cloud and its analysis allows us to automate the monitoring of vegetative growth and the quantification of the volume of vegetation to be removed to reduce or eliminate the hazard. In addition, the estimated shapes of the power lines are checked against the physically possible shapes to estimate their interference with large tree branches (for example, if a large branch with a lot of vegetation is resting on the power line). The advantages of the approach are presented in a case study of two typical power lines.

对电力线的植被干扰是配电系统断电的最常见原因之一，当在强风条件下与干燥和炎热的天气相结合时，极有可能引起巨大的野火。本文重点介绍了使用自动监测植被及其对电力线干扰程度的方法的案例研究结果。它基于所谓的点云的利用，这些点云可以由地面或机载激光扫描仪收集，也可以由无人机拍摄的立体图像生成。该方法允许估计电力线在空间中的位置，并且还允许识别在电力线附近的植被的位置。点云的连续重复收集及其分析使我们能够自动进行营养生长的监视和量化要去除的植被量，以减少或消除危害。另外，对照物理上可能的形状检查电源线的估计形状，以估计它们对大树枝的干扰（例如，如果有很多植被的大树枝搁在电源线上）。在两条典型电源线的案例研究中介绍了该方法的优点。根据物理上可能的形状检查估计的电源线形状，以估计它们对大树枝的干扰（例如，如果有很多植被的大树枝搁在电源线上）。在两条典型电源线的案例研究中介绍了该方法的优点。根据物理上可能的形状检查电源线的估计形状，以估计它们对大树枝的干扰（例如，如果有很多植被的大树枝搁在电源线上）。在两条典型电源线的案例研究中介绍了该方法的优点。