Impact of Atmospheric Turbulence and Pointing Error on Earth Observation
A new research paper introduces an enhanced image simulator to generate realistic Earth Observation (EO) imagery degraded by atmospheric turbulence and satellite pointing errors. The study evaluates the performance of YOLOv8 and RetinaNet models on vessel detection tasks using this simulated data. Results indicate that YOLOv8's recall significantly drops under degraded conditions, while RetinaNet shows greater robustness, maintaining higher recall. AI
IMPACT Highlights the need for more robust AI models trained on realistic environmental conditions for reliable Earth Observation applications.