DigitalGlobe, Inc., a provider of earth imagery and information about the planet, announced Thursday the launch of SpaceNet, an online repository of satellite imagery and labeled training data that will advance the development of machine learning and deep learning algorithms that leverage remote sensing data.
SpaceNet is a collaboration between DigitalGlobe, CosmiQ Works, and NVIDIA, and the imagery is now freely available as a public data set on Amazon Web Services, Inc. (AWS).
Until now, high-resolution satellite imagery has not been readily accessible for data scientists and developers to build meaningful computer vision algorithms, the company said. SpaceNet will for the first time open access to a large corpus of curated, high-resolution satellite imagery to incubate algorithm development.
SpaceNet will launch with an initial contribution of DigitalGlobe multi-spectral satellite imagery and 200,000 curated building footprints across the city of Rio de Janeiro, Brazil.
This initial contribution will provide the necessary data to create new algorithms to automate the extraction of features like buildings in dense urban environments. Over time DigitalGlobe, CosmiQ Works, NVIDIA, and AWS anticipate making more than 60 million labeled satellite images accessible to the public via SpaceNet, said the company.
“SpaceNet is key to unlocking a huge explosion of new AI-driven applications that ultimately will help us better respond to natural disasters, counter global security threats, improve population health outcomes, and much more,” said Tony Frazier, Senior Vice President at DigitalGlobe.
“The industry is coming together to power smarter algorithms so we can see and learn things from imagery about our planet that we simply cannot know today through manual techniques,” he added.