Scalable, interoperable processing of water column sonar data for biological applications using the echopype Python package
Abstract
High-frequency sonar systems deployed on a growing variety of ocean observing platforms are creating an increasing deluge of water column sonar data. These echosounder and ADCP systems are widely used in fisheries and marine ecological studies. Efficient and integrated analysis of these data, either across different sonar instruments or with other types of ocean data, holds a distinct potential for monitoring and understanding the response of marine organisms to the rapidly changing environment and to study marine ecosystems at broad spatial and temporal scales. We will briefly discuss the current state of water column sonar data, then present and demonstrate echopype (https://github.com/OSOceanAcoustics/echopype), an open-source Python software package designed to address these needs. Echopype standardizes water column sonar data from diverse instrument vendor formats into a variant of the SONAR-netCDF4 community convention optimized for usability and analysis, providing instrument-agnostic, netCDF-based exploration and use of sonar data. By leveraging existing open-source Python libraries optimized for distributed computing (xarray, dask, zarr, fsspec), it enables computational interoperability and scalability in both local and cloud computing environments. We will also demonstrate echopype’s data processing capabilities, entice your contributions to the package, and briefly touch on our ongoing echopype-enabled work developing cloud-native data processing workflows and machine learning applications.
Emilio Mayorga
Senior Oceanographer at APL-UW
