This deep learning model is designed to extract roads from high-resolution (30–50 cm) aerial or satellite imagery. Road layers play a critical role in creating base maps and supporting analysis for urban development, infrastructure planning, change detection, and a wide range of other applications.

Manually digitizing roads from imagery is often labour-intensive and time-consuming. Deep learning offers an efficient solution by accurately interpreting complex spatial patterns. This model automates the road extraction process, significantly reducing the time and effort needed to generate detailed and accurate road layers.