The top solutions have since been deployed to assist with the 2020 California wildfires, coastal hurricanes, and the 2019-2020 Australia Bushfires. The competition resulted in more than 2,000 submissions and multiple winning solutions with an 80% damage assessment success rate (the first-place algorithm was 266% more accurate than the government baseline). Winning models were deployed in various disaster relief efforts and data remain available for download. The xView2 Challenge used high-resolution RGB satellite imagery and competitors developed algorithms to identify buildings and score structural damage before and after a variety of natural disasters around the world.

While satellite and aerial imagery offer a less risky alternative that covers more ground, analysts must still conduct manual, time-intensive assessments of images. However, emergency responders must often navigate disruptions to local communication and transportation infrastructure, making accurate assessments dangerous, difficult, and slow. The time it takes to properly assess damage in the wake of a major event can be the difference between life and death. XView2 Challenge: Building Damage Assessment The top five competitors in the open source track and the top three competitors in the closed track will each receive a prize!Ĭompetition terms and conditions are detailed here. All individuals and organizations are eligible to compete in the open source track and win GFW prizes U.S.-based competitors are eligible to compete in both open source and closed source tracks and win DIU prizes. DIU and GFW will award $150,000 in total prizes. The xView3 Challenge will offer two tracks for competition: one for open source algorithms and the other for closed source algorithms. GFW is a leading international nonprofit organization dedicated to advancing ocean governance through increased transparency of human activity at sea. The xView3 challenge is organized and run by DIU in collaboration with Global Fishing Watch (GFW). Register today to compete in the xView3 challenge and compete for $150,000 in total prizes! COMPETITION DETAILS

xView3 challenges competitors to develop algorithms that identify and classify SAR satellite images of vessels suspected of engaging in IUU fishing. The rise of synthetic aperture radar (SAR) satellite imagery offers an all-weather tool to detect vessels that may otherwise elude fishery enforcement authorities. Rapid detection of IUU fishing activity would enable earlier interdiction and prosecution of offenders, mitigating these damages and reestablishing regional stability.

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