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...
Published in: | Methods in Ecology and Evolution |
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Online Access: | https://hdl.handle.net/10023/25541 https://doi.org/10.1111/2041-210X.13907 |
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ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/25541 2024-04-28T08:39:49+00:00 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 University of St Andrews. Sea Mammal Research Unit University of St Andrews. Marine Alliance for Science & Technology Scotland University of St Andrews. Scottish Oceans Institute University of St Andrews. School of Biology University of St Andrews. Bioacoustics group University of St Andrews. Sound Tags Group 2022-06-16T14:30:03Z 13 1986802 application/pdf https://hdl.handle.net/10023/25541 https://doi.org/10.1111/2041-210X.13907 eng eng Methods in Ecology and Evolution 279750539 21ac5235-0539-423d-a0e4-bb9249f79fde 85131869571 000811362600001 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 2041-210X ORCID: /0000-0001-9628-157X/work/114641534 https://hdl.handle.net/10023/25541 doi:10.1111/2041-210X.13907 Acoustic survey Acoustics Bioacoustics Click train detector Open-source PAMGuard Semi-automatic QH301 Biology DAS SDG 14 - Life Below Water QH301 Journal article 2022 ftstandrewserep https://doi.org/10.1111/2041-210X.13907 2024-04-09T23:33:08Z 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: Digital Research Repository Methods in Ecology and Evolution 13 8 1765 1777 |
institution |
Open Polar |
collection |
University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
Acoustic survey Acoustics Bioacoustics Click train detector Open-source PAMGuard Semi-automatic QH301 Biology DAS SDG 14 - Life Below Water QH301 |
spellingShingle |
Acoustic survey Acoustics Bioacoustics Click train detector Open-source PAMGuard Semi-automatic QH301 Biology DAS SDG 14 - Life Below Water QH301 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 QH301 Biology DAS SDG 14 - Life Below Water QH301 |
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 ... |
author2 |
University of St Andrews. Sea Mammal Research Unit University of St Andrews. Marine Alliance for Science & Technology Scotland University of St Andrews. Scottish Oceans Institute University of St Andrews. School of Biology University of St Andrews. Bioacoustics group University of St Andrews. Sound Tags Group |
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://hdl.handle.net/10023/25541 https://doi.org/10.1111/2041-210X.13907 |
genre |
Sperm whale toothed whales |
genre_facet |
Sperm whale toothed whales |
op_relation |
Methods in Ecology and Evolution 279750539 21ac5235-0539-423d-a0e4-bb9249f79fde 85131869571 000811362600001 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 2041-210X ORCID: /0000-0001-9628-157X/work/114641534 https://hdl.handle.net/10023/25541 doi:10.1111/2041-210X.13907 |
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 |
_version_ |
1797570695415201792 |