acoustic seafloor classification model output GOA 2019

Files contain outputs from a ML model described in "Seabed classification in the Gulf of Alaska from acoustic surveys using deep learning " by K. Agarwal, C. Rooper, and K. Williams. Each row is derived from an acoustic sample collected during the 2019 GOA summer acoustic survey, which is conducted by the NOAA/AFSC. The fields include geographic position, depth, and probability of class membership across five seafloor habitat categories including Sand/Mud, Mixed Coarse, Cobble, Boulder, and Bedrock. Rugosity represents small scale change in elevation (1 m). The dataset is divided into 6 files for ease of downloading/managing.