Sammanfattning

Passive acoustic monitoring (PAM) is emerging as a cost-effective non-intrusive method to monitor the health and biodiversity of marine habitats, including the impacts of anthropogenic noise on marine organisms. When long PAM recordings are to be analysed, automatic recognition and identification processes are invaluable tools to extract the relevant information. We propose a pattern recognition methodology based on hidden Markov models (HMMs) for the detection and recognition of acoustic signals from marine vessels passages and test it in two different regions, the Tagus estuary in Portugal and the Oresund strait in the Baltic Sea. Results show that the combination of HMMs with PAM provides a powerful tool to monitor the presence of marine vessels and discriminate different vessels such as small boats, ferries, and large ships. Improvements to enhance the capability to discriminate different types of small recreational boats are discussed.

Nyckelord

automatic sound recognition; boat; marine vessels; noise pollution; passive acoustic monitoring; recreational

Publicerad i

ICES Journal of Marine Science
2020, Volym: 77, nummer: 6, sidor: 2157-2170
Utgivare: OXFORD UNIV PRESS

SLU författare

• Sundelöf, Andreas

  • Institutionen för akvatiska resurser (SLU Aqua), Sveriges lantbruksuniversitet
    

• Prista, Nuno

  • Institutionen för akvatiska resurser (SLU Aqua), Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Fisk- och akvakulturforskning


Publikationens identifierare

DOI: https://doi.org/10.1093/icesjms/fsz194

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/110615