Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation

1. Passive acoustic surveys are becoming increasingly popular as a means of surveying for cetaceans and other marine species. These surveys yield large amounts of data, the analysis of which is time consuming and can account for a substantial proportion of the survey budget. Semi-automatic processes...

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Published in:Methods in Ecology and Evolution
Main Authors: Webber, Thomas, Gillespie, Douglas Michael, Lewis, Timothy, Gordon, Jonathan, Ruchirabha, Tararak, Thompson, Kirsten Freja
Format: Article in Journal/Newspaper
Language:English
Published: 2022
Subjects:
Online Access:https://risweb.st-andrews.ac.uk/portal/en/researchoutput/streamlining-analysis-methods-for-large-acoustic-surveys-using-automatic-detectors-with-operator-validation(21ac5235-0539-423d-a0e4-bb9249f79fde).html
https://doi.org/10.1111/2041-210X.13907
https://research-repository.st-andrews.ac.uk/bitstream/10023/25541/1/Webber_2022_MEE_Streamlining_CC.pdf
id ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/21ac5235-0539-423d-a0e4-bb9249f79fde
record_format openpolar
spelling ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/21ac5235-0539-423d-a0e4-bb9249f79fde 2023-05-15T18:26:52+02:00 Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation Webber, Thomas Gillespie, Douglas Michael Lewis, Timothy Gordon, Jonathan Ruchirabha, Tararak Thompson, Kirsten Freja 2022-06-15 application/pdf https://risweb.st-andrews.ac.uk/portal/en/researchoutput/streamlining-analysis-methods-for-large-acoustic-surveys-using-automatic-detectors-with-operator-validation(21ac5235-0539-423d-a0e4-bb9249f79fde).html https://doi.org/10.1111/2041-210X.13907 https://research-repository.st-andrews.ac.uk/bitstream/10023/25541/1/Webber_2022_MEE_Streamlining_CC.pdf eng eng info:eu-repo/semantics/openAccess Webber , T , Gillespie , D M , Lewis , T , Gordon , J , Ruchirabha , T & Thompson , K F 2022 , ' Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation ' , Methods in Ecology and Evolution , vol. Early View . https://doi.org/10.1111/2041-210X.13907 Acoustic survey Acoustics Bioacoustics Click train detector Open-source PAMGuard Semi-automatic article 2022 ftunstandrewcris https://doi.org/10.1111/2041-210X.13907 2022-10-31T06:44:01Z 1. Passive acoustic surveys are becoming increasingly popular as a means of surveying for cetaceans and other marine species. These surveys yield large amounts of data, the analysis of which is time consuming and can account for a substantial proportion of the survey budget. Semi-automatic processes enable the bulk of processing to be conducted automatically while allowing analyst time to be reserved for validating and correcting detections and classifications. 2. Existing modules within the Passive Acoustic Monitoring software PAMGuard were used to process a large (25.4 Terabyte) dataset collected during towed acoustic ship transits. The recently developed ‘Multi-Hypothesis Tracking Click Train Detector’ and the ‘Whistle and Moan Detector’ modules were used to identify occasions within the dataset at which vocalising toothed whales (odontocetes) were likely to be acoustically present. These putative detections were then reviewed by an analyst, with false positives being corrected. Target motion analysis provided a perpendicular distance to odontocete click events enabling the estimation of detection functions for both sperm whales and delphinids. Detected whistles were assigned to the lowest taxonomical level possible using the PAMGuard ‘Whistle Classifier’ module. 3. After an initial tuning process, this semi-automatic method required 91 hr of an analyst's time to manually review both automatic click train and whistle detections from 1,696 hr of survey data. Use of the ‘Multi-Hypothesis Tracking Click Train Detector’ reduced the amount of data for the analyst to search by 74.5%, while the ‘Whistle and Moan Detector’ reduced data to search by 85.9%. In total, 443 odontocete groups were detected, of which 55 were from sperm whale groups, six were from beaked whales, two were from porpoise and the remaining 380 were identified to the level of delphinid group. An effective survey strip half width of 3,277 and 699 m was estimated for sperm whales and delphinids respectively. 4. The semi-automatic workflow proved ... Article in Journal/Newspaper Sperm whale toothed whales University of St Andrews: Research Portal Moan ENVELOPE(9.843,9.843,62.881,62.881) Methods in Ecology and Evolution 13 8 1765 1777
institution Open Polar
collection University of St Andrews: Research Portal
op_collection_id ftunstandrewcris
language English
topic Acoustic survey
Acoustics
Bioacoustics
Click train detector
Open-source
PAMGuard
Semi-automatic
spellingShingle Acoustic survey
Acoustics
Bioacoustics
Click train detector
Open-source
PAMGuard
Semi-automatic
Webber, Thomas
Gillespie, Douglas Michael
Lewis, Timothy
Gordon, Jonathan
Ruchirabha, Tararak
Thompson, Kirsten Freja
Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
topic_facet Acoustic survey
Acoustics
Bioacoustics
Click train detector
Open-source
PAMGuard
Semi-automatic
description 1. Passive acoustic surveys are becoming increasingly popular as a means of surveying for cetaceans and other marine species. These surveys yield large amounts of data, the analysis of which is time consuming and can account for a substantial proportion of the survey budget. Semi-automatic processes enable the bulk of processing to be conducted automatically while allowing analyst time to be reserved for validating and correcting detections and classifications. 2. Existing modules within the Passive Acoustic Monitoring software PAMGuard were used to process a large (25.4 Terabyte) dataset collected during towed acoustic ship transits. The recently developed ‘Multi-Hypothesis Tracking Click Train Detector’ and the ‘Whistle and Moan Detector’ modules were used to identify occasions within the dataset at which vocalising toothed whales (odontocetes) were likely to be acoustically present. These putative detections were then reviewed by an analyst, with false positives being corrected. Target motion analysis provided a perpendicular distance to odontocete click events enabling the estimation of detection functions for both sperm whales and delphinids. Detected whistles were assigned to the lowest taxonomical level possible using the PAMGuard ‘Whistle Classifier’ module. 3. After an initial tuning process, this semi-automatic method required 91 hr of an analyst's time to manually review both automatic click train and whistle detections from 1,696 hr of survey data. Use of the ‘Multi-Hypothesis Tracking Click Train Detector’ reduced the amount of data for the analyst to search by 74.5%, while the ‘Whistle and Moan Detector’ reduced data to search by 85.9%. In total, 443 odontocete groups were detected, of which 55 were from sperm whale groups, six were from beaked whales, two were from porpoise and the remaining 380 were identified to the level of delphinid group. An effective survey strip half width of 3,277 and 699 m was estimated for sperm whales and delphinids respectively. 4. The semi-automatic workflow proved ...
format Article in Journal/Newspaper
author Webber, Thomas
Gillespie, Douglas Michael
Lewis, Timothy
Gordon, Jonathan
Ruchirabha, Tararak
Thompson, Kirsten Freja
author_facet Webber, Thomas
Gillespie, Douglas Michael
Lewis, Timothy
Gordon, Jonathan
Ruchirabha, Tararak
Thompson, Kirsten Freja
author_sort Webber, Thomas
title Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
title_short Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
title_full Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
title_fullStr Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
title_full_unstemmed Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
title_sort streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation
publishDate 2022
url https://risweb.st-andrews.ac.uk/portal/en/researchoutput/streamlining-analysis-methods-for-large-acoustic-surveys-using-automatic-detectors-with-operator-validation(21ac5235-0539-423d-a0e4-bb9249f79fde).html
https://doi.org/10.1111/2041-210X.13907
https://research-repository.st-andrews.ac.uk/bitstream/10023/25541/1/Webber_2022_MEE_Streamlining_CC.pdf
long_lat ENVELOPE(9.843,9.843,62.881,62.881)
geographic Moan
geographic_facet Moan
genre Sperm whale
toothed whales
genre_facet Sperm whale
toothed whales
op_source Webber , T , Gillespie , D M , Lewis , T , Gordon , J , Ruchirabha , T & Thompson , K F 2022 , ' Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation ' , Methods in Ecology and Evolution , vol. Early View . https://doi.org/10.1111/2041-210X.13907
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1111/2041-210X.13907
container_title Methods in Ecology and Evolution
container_volume 13
container_issue 8
container_start_page 1765
op_container_end_page 1777
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