Report on the advances in sound measurement methods

This document, Deliverable 9.9 of the MINKE project, titled “Advances in Sound Measurement Methods,” provides an in-depth exploration of methodologies for enhancing underwater sound measurements. Task 9.6 focuses on improving data quality and measurement reliability in underwater acoustics, aligning with the objectives of Work Package 9. The deliverable outlines a comprehensive approach, including inventories of off-the-shelf devices, advanced statistical methods for ambient noise estimation, validation methodologies for ocean noise models, and intercomparison exercises for acoustic devices. Key findings highlight the critical need for metrological frameworks, robust calibration, and standardized methods to ensure high-quality acoustic data collection and analysis. The document concludes by proposing future directions for the integration of advanced algorithms, machine learning, and metrology-driven practices to enhance acoustic observation systems and their utility in marine ecosystem monitoring.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-13
DOI
https://doi.org/10.5281/zenodo.15016720
Primary Topic
Reformed Theology and Governance
Type
article
Field-Weighted Citation Impact
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article

Report on the advances in sound measurement methods

Zenodo (CERN European Organization for Nuclear Research)
Reformed Theology and Governance
article

Report on the advances in sound measurement methods

article en

Abstract

This document, Deliverable 9.9 of the MINKE project, titled “Advances in Sound Measurement Methods,” provides an in-depth exploration of methodologies for enhancing underwater sound measurements. Task 9.6 focuses on improving data quality and measurement reliability in underwater acoustics, aligning with the objectives of Work Package 9. The deliverable outlines a comprehensive approach, including inventories of off-the-shelf devices, advanced statistical methods for ambient noise estimation, validation methodologies for ocean noise models, and intercomparison exercises for acoustic devices. Key findings highlight the critical need for metrological frameworks, robust calibration, and standardized methods to ensure high-quality acoustic data collection and analysis. The document concludes by proposing future directions for the integration of advanced algorithms, machine learning, and metrology-driven practices to enhance acoustic observation systems and their utility in marine ecosystem monitoring.

Zenodo (CERN European Organization for Nuclear Research)
Oceanic Platform of the Canary Islands (ES), Service Hydrographique et Océanographique de la Marine (FR), United States Bone and Joint Initiative (US), National Research Council (IT), Universitat Politècnica de Catalunya (ES)
Life below water
Openalex Percentile: Top 54%
Reformed Theology and Governance
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