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鲸声定位软件工具包:用于动物发声的声数组定位。

Where's Whaledo: A software toolkit for array localization of animal vocalizations.

机构信息

Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, United States of America.

出版信息

PLoS Comput Biol. 2024 May 20;20(5):e1011456. doi: 10.1371/journal.pcbi.1011456. eCollection 2024 May.

DOI:10.1371/journal.pcbi.1011456
PMID:38768239
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11142720/
Abstract

Where's Whaledo is a software toolkit that uses a combination of automated processes and user interfaces to greatly accelerate the process of reconstructing animal tracks from arrays of passive acoustic recording devices. Passive acoustic localization is a non-invasive yet powerful way to contribute to species conservation. By tracking animals through their acoustic signals, important information on diving patterns, movement behavior, habitat use, and feeding dynamics can be obtained. This method is useful for helping to understand habitat use, observe behavioral responses to noise, and develop potential mitigation strategies. Animal tracking using passive acoustic localization requires an acoustic array to detect signals of interest, associate detections on various receivers, and estimate the most likely source location by using the time difference of arrival (TDOA) of sounds on multiple receivers. Where's Whaledo combines data from two small-aperture volumetric arrays and a variable number of individual receivers. In a case study conducted in the Tanner Basin off Southern California, we demonstrate the effectiveness of Where's Whaledo in localizing groups of Ziphius cavirostris. We reconstruct the tracks of six individual animals vocalizing concurrently and identify Ziphius cavirostris tracks despite being obscured by a large pod of vocalizing dolphins.

摘要

Whaledo 是一个软件工具包,它结合了自动化流程和用户界面,极大地加速了从被动声学记录设备阵列中重建动物足迹的过程。被动声学定位是一种非侵入性但功能强大的方法,有助于物种保护。通过跟踪动物的声信号,可以获得有关潜水模式、运动行为、栖息地利用和摄食动态的重要信息。这种方法有助于了解栖息地利用、观察对噪声的行为反应,并制定潜在的缓解策略。使用被动声学定位进行动物跟踪需要一个声学阵列来检测感兴趣的信号,在各个接收器上关联检测,并使用多个接收器上声音的到达时间差 (TDOA) 来估计最可能的声源位置。Whaledo 将来自两个小孔径体积阵列和多个单独接收器的数据结合在一起。在加利福尼亚南部 Tanner 盆地进行的一项案例研究中,我们展示了 Whaledo 在定位 Ziphius cavirostris 群体方面的有效性。我们重建了六只同时发声的个体动物的轨迹,并在被大量发声海豚遮挡的情况下识别出了 Ziphius cavirostris 的轨迹。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/db86aa8de128/pcbi.1011456.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/1020c6aca8a3/pcbi.1011456.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/6c015de14ded/pcbi.1011456.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/789b84c67089/pcbi.1011456.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/ddd67d9fd604/pcbi.1011456.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/ebed22c8ddee/pcbi.1011456.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/62bf8c3cf160/pcbi.1011456.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/865b0ac85e8f/pcbi.1011456.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/6511f08ebc44/pcbi.1011456.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/db86aa8de128/pcbi.1011456.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/1020c6aca8a3/pcbi.1011456.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/6c015de14ded/pcbi.1011456.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/789b84c67089/pcbi.1011456.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/ddd67d9fd604/pcbi.1011456.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/ebed22c8ddee/pcbi.1011456.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/62bf8c3cf160/pcbi.1011456.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/865b0ac85e8f/pcbi.1011456.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/6511f08ebc44/pcbi.1011456.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef75/11142720/db86aa8de128/pcbi.1011456.g009.jpg

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Discriminating and classifying odontocete echolocation clicks in the Hawaiian Islands using machine learning methods.利用机器学习方法在夏威夷群岛区分和分类齿鲸的回声定位声纳信号。
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