Multibeam sonar water column data processing tools to support coastal ecosystem science Free

Multibeam sonar water column data are routinely collected by hydrographic survey vessels to observe and validate minimum depth measurements over anthropogenic submerged objects, which may pose a hazard to navigation. A large volume of additional data is collected during this process but mostly goes unused. This project investigates the development of processing tools and algorithms to automate the extraction of oceanographic and ecological features from the water column data files to enhance the usefulness of these datasets. Sample data from a Gulf of Mexico Research Initiative (GoMRI) project is explored where multibeam data is collected simultaneously with a towed profiling high resolution in situ ichthyoplankton imaging system (with CTD, dissolved oxygen, PAR, and chlorophyll-a fluorescence sensors). The objective is to identify and map spatial and temporal variations in biomass throughout the water column by correlating the acoustic data with imagery and sensor output from the towed profiling system. Processing the dataset to isolate and identify objects and signal patterns of interest, which might normally be considered noise, is investigated. The developed tools will aid in biological and physical feature extraction to further enhance the application of multibeam acoustic water column data.