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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Benchmarking road network extraction methods for power distribution spatial planning</dc:title><dc:creator>Križaj,	Janez	(Avtor)
	</dc:creator><dc:creator>Štruc,	Vitomir	(Avtor)
	</dc:creator><dc:subject>road network extraction</dc:subject><dc:subject>satellite imagery</dc:subject><dc:subject>power distribution</dc:subject><dc:subject>spatial planning</dc:subject><dc:description>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-ofway. 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.</dc:description><dc:date>2026</dc:date><dc:date>2026-03-20 14:34:06</dc:date><dc:type>Neznano</dc:type><dc:identifier>180967</dc:identifier><dc:identifier>UDK: 004:629.056.8</dc:identifier><dc:identifier>COBISS_ID: 272486659</dc:identifier><dc:identifier>OceCobissID: 270650883</dc:identifier><dc:language>sl</dc:language><dc:rights>Podatek o licenci se nahaja na pristajalni strani.</dc:rights></metadata>
