54 min

#25 Evaluating SpaceNet 5 Challenge Results: Road Network Detection & Optimized Routing Training_Data

    • Arts

Despite its application to myriad humanitarian and civil use cases, automated road network extraction from overhead satellite imagery remains quite challenging. However, the SpaceNet 5 challenge made significant progress in this field with top participants being able to extract both road networks and speed/travel time estimates for each roadway. On today’s pod, CosmiQ’s Ryan Lewis and Dr. Adam Van Etten explore the challenge’s unique dataset and geographic diversity over time, the winning models, and the tradeoff between inference speed and model performance. SpaceNet is a non-profit LLC co-founded and managed by In-Q-Tel's CosmiQ Works in collaboration Maxar Technologies, a co-founder, and the other SpaceNet Partners including AWS, Intel AI, Topcoder, Capella Space, IEEE GRSS, The National Geospatial-Intelligence Agency (NGA), and Planet.

Despite its application to myriad humanitarian and civil use cases, automated road network extraction from overhead satellite imagery remains quite challenging. However, the SpaceNet 5 challenge made significant progress in this field with top participants being able to extract both road networks and speed/travel time estimates for each roadway. On today’s pod, CosmiQ’s Ryan Lewis and Dr. Adam Van Etten explore the challenge’s unique dataset and geographic diversity over time, the winning models, and the tradeoff between inference speed and model performance. SpaceNet is a non-profit LLC co-founded and managed by In-Q-Tel's CosmiQ Works in collaboration Maxar Technologies, a co-founder, and the other SpaceNet Partners including AWS, Intel AI, Topcoder, Capella Space, IEEE GRSS, The National Geospatial-Intelligence Agency (NGA), and Planet.

54 min