Benchmarking Road Network Extraction Methods for Power Distribution Spatial Planning

Accurate road network extraction from high-resolution overhead imagery is a prerequisite for corridor-aware routing and cost modelling in power-system infrastructure planning, where medium- and low-voltage lines often follow transport rights-of-way. Yet roads are thin, occluded, and cluttered, and downstream optimisation needs routable graphs, not just masks. We benchmark six representative pipelines (SAM-Road, D-LinkNet, CRESI, CU-dGCN, Sat2Graph, and U-Net-ResNet18) on SpaceNet imagery. The comparison reveals trade-offs between segmentation-centric and graph-aware designs and highlights where topology fails most often. Finally, practical guidance is provided for selecting road extractors that deliver reliable, optimisation-ready networks for power distribution corridor planning and the routing of medium- and low-voltage lines.