Estimating fin whale distribution from ambient noise spectra using Bayesian inversion

Passive acoustic monitoring is increasingly used to study the distribution and migration of marine mammals. Marine mammal vocalizations are transient sounds, but the combined sound energy of a population continuously repeating a vocalization, adds up to a quasi-continuous chorus. Marine mammal choru...

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Bibliographic Details
Main Author: Menze, Sebastian
Format: Master Thesis
Language:English
Published: The University of Bergen 2015
Subjects:
Online Access:https://hdl.handle.net/1956/10323
id ftunivbergen:oai:bora.uib.no:1956/10323
record_format openpolar
spelling ftunivbergen:oai:bora.uib.no:1956/10323 2023-05-15T15:36:42+02:00 Estimating fin whale distribution from ambient noise spectra using Bayesian inversion Menze, Sebastian 2015-06-01 12747325 bytes application/pdf https://hdl.handle.net/1956/10323 eng eng The University of Bergen https://hdl.handle.net/1956/10323 Copyright the Author. All rights reserved inverse theory fin whales Balaenoptera physalus passive acoustic monitoring ambient noise marine mammal chorus ocean acoustics finnhvaler akustiske metoder dyrekommunikasjon Norskehavet http://data.ub.uio.no/realfagstermer/c008554 http://data.ub.uio.no/realfagstermer/c030222 http://data.ub.uio.no/realfagstermer/c004899 756213 Master thesis 2015 ftunivbergen 2023-03-14T17:39:47Z Passive acoustic monitoring is increasingly used to study the distribution and migration of marine mammals. Marine mammal vocalizations are transient sounds, but the combined sound energy of a population continuously repeating a vocalization, adds up to a quasi-continuous chorus. Marine mammal choruses can be identified as peaks in ocean ambient noise spectra. In the North Atlantic, the fin whale chorus is commonly observed as peak at 20 Hz. This thesis proposes a method to estimate the distribution of vocalizing fin whales based on a set of fin whale chorus recordings. This is an extremely under-determined inverse problem. The method is based on Bayesian inverse theory and uses simulated annealing to estimate the most likely distribution of sound sources (vocalizing whales) on a geodesic grid. This includes calculating a transmission loss matrix connecting all grid nodes and recorders, using an arbitrary sound propagation model. Two models were successfully implemented: geometrical spreading and the ray trace model BELLHOP. The inversion method was tested under different scenarios. The results indicated that an imprecise transmission loss matrix is tolerated by the inversion method. The accuracy of the method depended mainly on the number and distribution of recorders. For the Norwegian sea, simulations showed that fin whale chorus inversion is possible using as few as 12 recorders between Iceland and Svalbard. An inversion based on data from published fin whale chorus observations indicated realistic winter distribution patterns. Existing methods to study marine mammal distribution are often confined to the summer months and a limited area. Future application of the proposed method admits automatic year-round monitoring of marine mammal distribution on a basin-wide scale. JMAMN-MCLI MCLI399 Master Thesis Balaenoptera physalus Fin whale Iceland Norskehav* North Atlantic Norwegian Sea Svalbard University of Bergen: Bergen Open Research Archive (BORA-UiB) Norwegian Sea Svalbard
institution Open Polar
collection University of Bergen: Bergen Open Research Archive (BORA-UiB)
op_collection_id ftunivbergen
language English
topic inverse theory
fin whales
Balaenoptera physalus
passive acoustic monitoring
ambient noise
marine mammal chorus
ocean acoustics
finnhvaler
akustiske metoder
dyrekommunikasjon
Norskehavet
http://data.ub.uio.no/realfagstermer/c008554
http://data.ub.uio.no/realfagstermer/c030222
http://data.ub.uio.no/realfagstermer/c004899
756213
spellingShingle inverse theory
fin whales
Balaenoptera physalus
passive acoustic monitoring
ambient noise
marine mammal chorus
ocean acoustics
finnhvaler
akustiske metoder
dyrekommunikasjon
Norskehavet
http://data.ub.uio.no/realfagstermer/c008554
http://data.ub.uio.no/realfagstermer/c030222
http://data.ub.uio.no/realfagstermer/c004899
756213
Menze, Sebastian
Estimating fin whale distribution from ambient noise spectra using Bayesian inversion
topic_facet inverse theory
fin whales
Balaenoptera physalus
passive acoustic monitoring
ambient noise
marine mammal chorus
ocean acoustics
finnhvaler
akustiske metoder
dyrekommunikasjon
Norskehavet
http://data.ub.uio.no/realfagstermer/c008554
http://data.ub.uio.no/realfagstermer/c030222
http://data.ub.uio.no/realfagstermer/c004899
756213
description Passive acoustic monitoring is increasingly used to study the distribution and migration of marine mammals. Marine mammal vocalizations are transient sounds, but the combined sound energy of a population continuously repeating a vocalization, adds up to a quasi-continuous chorus. Marine mammal choruses can be identified as peaks in ocean ambient noise spectra. In the North Atlantic, the fin whale chorus is commonly observed as peak at 20 Hz. This thesis proposes a method to estimate the distribution of vocalizing fin whales based on a set of fin whale chorus recordings. This is an extremely under-determined inverse problem. The method is based on Bayesian inverse theory and uses simulated annealing to estimate the most likely distribution of sound sources (vocalizing whales) on a geodesic grid. This includes calculating a transmission loss matrix connecting all grid nodes and recorders, using an arbitrary sound propagation model. Two models were successfully implemented: geometrical spreading and the ray trace model BELLHOP. The inversion method was tested under different scenarios. The results indicated that an imprecise transmission loss matrix is tolerated by the inversion method. The accuracy of the method depended mainly on the number and distribution of recorders. For the Norwegian sea, simulations showed that fin whale chorus inversion is possible using as few as 12 recorders between Iceland and Svalbard. An inversion based on data from published fin whale chorus observations indicated realistic winter distribution patterns. Existing methods to study marine mammal distribution are often confined to the summer months and a limited area. Future application of the proposed method admits automatic year-round monitoring of marine mammal distribution on a basin-wide scale. JMAMN-MCLI MCLI399
format Master Thesis
author Menze, Sebastian
author_facet Menze, Sebastian
author_sort Menze, Sebastian
title Estimating fin whale distribution from ambient noise spectra using Bayesian inversion
title_short Estimating fin whale distribution from ambient noise spectra using Bayesian inversion
title_full Estimating fin whale distribution from ambient noise spectra using Bayesian inversion
title_fullStr Estimating fin whale distribution from ambient noise spectra using Bayesian inversion
title_full_unstemmed Estimating fin whale distribution from ambient noise spectra using Bayesian inversion
title_sort estimating fin whale distribution from ambient noise spectra using bayesian inversion
publisher The University of Bergen
publishDate 2015
url https://hdl.handle.net/1956/10323
geographic Norwegian Sea
Svalbard
geographic_facet Norwegian Sea
Svalbard
genre Balaenoptera physalus
Fin whale
Iceland
Norskehav*
North Atlantic
Norwegian Sea
Svalbard
genre_facet Balaenoptera physalus
Fin whale
Iceland
Norskehav*
North Atlantic
Norwegian Sea
Svalbard
op_relation https://hdl.handle.net/1956/10323
op_rights Copyright the Author. All rights reserved
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