

Over the past decade, NASA's Lunar Reconnaissance Orbiter (LRO) has captured thousands of high-resolution images of the Moon's surface—far more than humans can manually review. To tackle this challenge, scientists have developed an automated system that quickly identifies scientifically significant images from the LRO data, making it the first anomaly detector for planetary imagery. Experiments show that the system reliably highlights unusual features, such as striking geological formations and sites of human landings or spacecraft crashes. This approach fills a critical gap in planetary science, offering a groundbreaking way to uncover hidden insights in vast archives of remote-sensing data. Join senior planetary astronomer Franck Marchis as he chats with authors Adam Lesnikowski and Daniel Angerhausen about this revolutionary method and its implications for future discoveries. (Recorded 20 February 2025.)
103 episodes
Over the past decade, NASA's Lunar Reconnaissance Orbiter (LRO) has captured thousands of high-resolution images of the Moon's surface—far more than humans can manually review. To tackle this challenge, scientists have developed an automated system that quickly identifies scientifically significant images from the LRO data, making it the first anomaly detector for planetary imagery. Experiments show that the system reliably highlights unusual features, such as striking geological formations and sites of human landings or spacecraft crashes. This approach fills a critical gap in planetary science, offering a groundbreaking way to uncover hidden insights in vast archives of remote-sensing data. Join senior planetary astronomer Franck Marchis as he chats with authors Adam Lesnikowski and Daniel Angerhausen about this revolutionary method and its implications for future discoveries. (Recorded 20 February 2025.)
103 episodes
Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.