![]() ![]() ![]() ![]() This technical challenge has been unlocked by access to a spatio-temporal dataset at a scale and cadence that was previously unavailable to the broader research community. Whereas all six previous SpaceNet challenges were based on static road and building detection, the partnership between SpaceNet and Planet will allow the seventh competition to focus on discovery of change events directly. Previous competitions led to a dramatic expansion of the availability of open source data of building footprints and road networks for the geospatial machine learning community. SpaceNet offers free, precision-labeled, electro-optical and synthetic aperture radar satellite imagery data sets and runs challenges with prizes to foster emerging analytical frameworks. Rapid and accurate remote-sensing of infrastructure change can aid in a variety of efforts, from infrastructure development to disaster preparedness to epidemic prevention.Įstablished in 2016 by In-Q-Tel’s CosmiQ Works, and DigitalGlobe (now part of Maxar Technologies), SpaceNet is dedicated to accelerating the research and application of open source AI technology for geospatial applications. The challenge focuses on developing better methods to track building construction over time using Planet imagery mosaics. We’re excited to partner with SpaceNet LLC, a nonprofit focused on machine learning techniques for geospatial applications, to support the SpaceNet7 Multi-Temporal Urban Development Challenge which was just recently announced. Planet Partners with SpaceNet for Multi-Temporal Urban Development Challenge. ![]()
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