The task of SpaceNet 6 was to automatically extract building footprints with computer vision and artificial intelligence (AI) algorithms using a combination of SAR and electro-optical imagery datasets. This openly-licensed dataset features a unique combination of half-meter Synthetic Aperture Radar (SAR) imagery from Capella Space and half-meter electro-optical (EO) imagery from Maxar’s WorldView 2 satellite. The area of interest for the challenge was centered over the largest port in Europe: Rotterdam, the Netherlands. This area features thousands of buildings, vehicles, and boats of various sizes, to make an effective test bed for SAR and the fusion of these two types of data.
The Challenge ran March 16 – May 1, receiving more than 1,600 submissions and 411 registrants, making it the most competitive SpaceNet Challenge to date. The winner was zbigniewwojna, followed by MaksimovKA, and SatShipAI. The top five competitors in the challenge each received a portion of the total $50,000 cash prize, with first place taking home $20,000. The winners were able to successfully adapt state-of-the-art AI and computer vision algorithms to automatically extract building footprints from very-high resolution SAR data.