Enhanced remote sensing of the marine environment through glint avoidance modeling

Remote Sensing applications of the marine environment, such as benthic mapping or in-water parameter retrieval, can be highly sensitive to in-scene glint. Glint can negatively impact retrieval algorithms rendering the image data unusable in extreme cases. This work seeks to identify the best sensor tasking for minimizing glint when collecting data from an aircraft or space-based imaging platform while maximizing image quality. This paper describes the development of a glint-avoidance tool through the use of statistical surface models, in-water radiative transfer models, and simple atmospheric models to optimize collection planning to reduce the probability of glint contamination in remotely sensed data.