Work

Regularized log-linear models for predicting underwater radiated noise spectra of small vessels

Year: 2026

Type: article

Abstract: Underwater radiated noise (URN) from vessels is an anthropogenic stressor that negatively affects marine ecosystems. Accordingly, the ability to estimate URN levels is a critical component for environmental assessment. Predictive models are widely used to estimate URN emissions from different vessel types and operating conditions; however, comparable models for small recreational vessels are largely lacking, even though these vessels are arguably a dominant source of noise pollution in coastal areas. Here, we use a large dataset of acoustic measurements of recreational vessels to extend the empirical framework to small motorized vessels (motorized yachts and sailboats) by constructing regularized log-linear regression models that provide length and speed dependent source spectra over 23–24,000 Hz.

Source: Frontiers in Marine Science

DOI: 10.3389/fmars.2026.1759355

Authors: Mark Shipton, Roee Diamant

Institutions: University of Haifa, University of Zagreb, Faculty of Electrical Engineering and Computing in Zagreb

Language: English

Topic: Marine animal studies overview

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Life below water

Open Access status: gold

Estimated APC paid: $3,801