Monitoring Data-Driven Optimization Technology for Overhead Transmission Line Routing

This article focuses on the optimization of line routing and elaborates a series of key strategies based on monitoring data, providing technical support and practical guidance for the route selection of overhead transmission lines. By utilizing satellite remote sensing monitoring data and relying on high-resolution images, a high-precision three-dimensional terrain model is constructed through stereo pair matching and digital photogrammetry. Multiple sources of remote sensing data are integrated, compared with existing data for correction. Through image preprocessing and multiple optimizations, accurate updating of terrain data is achieved. With the help of UAV inspections, the LiDAR and optical cameras carried by the UAVs collect the three-dimensional coordinates and characteristic information of ground objects. Point cloud segmentation and deep learning algorithms are applied to separate and identify ground objects, and the data is integrated to update the information of ground objects in real time, providing the latest ground object data for route selection.