A trove of satellite data could teach software to track our trash from orbit.
Why can’t computers watch the Earth from above and automatically map our roads, buildings and trash heaps? Satellite operator DigitalGlobe is teaming up with Amazon, the venture arm of the CIA, and chipmaker NVIDIA to try and make it happen.
In a joint project, DigitalGlobe today released satellite imagery depicting the whole of Rio de Janeiro to a resolution of 50 centimeters. The outlines of 200,000 buildings inside the city's roughly 1900 square kilometers have been manually marked on the photos. The SpaceNet dataset, as it is called, is intended to spark efforts to train machine learning algorithms to interpret high resolution satellite photos by themselves.
DigitalGlobe says the SpaceNet dataset should eventually include high resolution images of half a million square miles of Earth, and that it will be adding annotations beyond just buildings.
DigitalGlobe's data is much more detailed than publicly available satellite data such as NASA's, which typically has a resolution of tens of meters. Amazon will make the SpaceNet data available via its cloud computing service. NVIDIA will provide tools to help machine learning researchers train and test algorithms on the data, and CosmiQ Works, a division of the CIA’s venture arm In-Q-Tel focused on space, is also supporting the project.
“We need to develop new algorithms for this data,” says Tony Frazier, a senior vice president at DigitalGlobe. The company operates four imaging satellites and provides data to U.S. intelligence agencies, humanitarian agencies, and other organizations that today mainly rely on humans to extract data from images.Park benches.
Frazier says it should be possible to train software to do things like map the roads and buildings of shanty towns, track changes to urban infrastructure such as park benches and stop signs, and measure the materials used in roofs and other structures....MORE
