Satellite imagery analysis is fast becoming a highly lucrative business model for both commercial players and defense contractors. Just last month, Airbus launched a new geospatial tool which would make planet-wide change detection possible in near-real-time. And now, Lockheed Martin has announced a satellite imagery recognition system which uses open-source deep learning libraries to identify and classify large datasets quickly.
Called Global Automated Target Recognition (GATR), the artificial intelligence model uses Maxar’s Geospatial Big Data platform to access the latter’s 100 petabyte treasure trove of satellite imagery library and millions of curated data labels. The Cloud-based system promises to save image analysts the trouble of spending countless hours manually categorizing and labeling items within an image.
During a public demo at GEOINT 2019 conference, GATR was able to search the entire state of Pennsylvania – 120,000 square kilometers – for fracking sites in only 2 hours. So, even if someone who is not an expert on oil production sites is looking for information on the same, they can leave the traditionally-manual process to GATR.
Lockheed Martin says the system can identify characteristics of an object area or target with an accuracy of over 90%. The self-learning model can recognize ships, airplanes, buildings, seaports, and many other commercial categories, freeing up analysts for higher-level tasks.
Mark Pritt, a senior fellow at Lockheed Martin and principal investigator for GATR, adds, “This system teaches itself the defining characteristics of an object, saving valuable time training an algorithm and ultimately letting an image analyst focus more on their mission.”
Lockheed Martin insists that it has an advantage over other players offering imagery analysis because its system uses commercial imagery from vendors like Maxar and Planet to ensure global coverage. “With our tool, the user can draw a box anywhere in the world and hit the button,” Pritt tells SpaceNews in an interview. “The system will go search for objects of interest such as fracking wells, airplanes or refugee camps.”