Interoperable and scalable echosounder data processing with Echopype
Wu-Jung Lee, Landung Setiawan, Caesar Tuguinay, Emilio Mayorga, and Valentina Staneva

TL;DR
Echopype is an open-source Python library that standardizes, scales, and enhances interoperability of echosounder data, facilitating efficient analysis of marine ecosystems across diverse platforms and datasets.
Contribution
It introduces a standardized data format and scalable processing framework for echosounder data, promoting integration and analysis across oceanographic research.
Findings
Standardizes echosounder data in netCDF format
Enables scalable processing in local and cloud environments
Supports expansion for additional instruments and analysis tools
Abstract
Echosounders are high-frequency sonar systems used to sense fish and zooplankton underwater. Their deployment on a variety of ocean observing platforms is generating vast amounts of data at an unprecedented speed from the oceans. Efficient and integrative analysis of these data, whether across different echosounder instruments or in combination with other oceanographic datasets, is crucial for understanding marine ecosystem response to the rapidly changing climate. Here we present Echopype, an open-source Python software library designed to address this need. By standardizing data as labeled, multi-dimensional arrays encoded in the widely embraced netCDF data model following a community convention, Echopype enhances the interoperability of echosounder data, making it easier to explore and use. By leveraging scientific Python libraries optimized for distributed computing, Echopype…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEnvironmental Monitoring and Data Management · Scientific Computing and Data Management · Oceanographic and Atmospheric Processes
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
