Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA)
Making Ambient Noise Trends Accessible (MANTA) software is a tool for the community to enable comparisons between soundscapes and identification of ambient ocean sound trends required by ocean stakeholders. MANTA enhances the value of individual datasets by assisting users in creating thorough calib...
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2021-08-01
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Series: | Frontiers in Marine Science |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2021.703650/full |
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author | Jennifer L. Miksis-Olds Peter J. Dugan S. Bruce Martin Holger Klinck Holger Klinck David K. Mellinger David A. Mann Dimitri W. Ponirakis Olaf Boebel |
author_facet | Jennifer L. Miksis-Olds Peter J. Dugan S. Bruce Martin Holger Klinck Holger Klinck David K. Mellinger David A. Mann Dimitri W. Ponirakis Olaf Boebel |
author_sort | Jennifer L. Miksis-Olds |
collection | DOAJ |
description | Making Ambient Noise Trends Accessible (MANTA) software is a tool for the community to enable comparisons between soundscapes and identification of ambient ocean sound trends required by ocean stakeholders. MANTA enhances the value of individual datasets by assisting users in creating thorough calibration metadata and internationally recommended products comparable over time and space to ultimately assess ocean sound at any desired scale up to a global level. The software package combines of two applications: MANTA Metadata App, which allows users to specify information about their recordings, and MANTA Data Mining App, which applies that information to acoustic recordings to produce consistently processed, calibrated time series products of sound pressure levels in hybrid millidecade bands. The main outputs of MANTA are daily.csv and NetCDF files containing 60-s spectral energy calculations in hybrid millidecade bands and daily statistics images. MANTA data product size and formats enable easy and compact transfer and archiving among researchers and programs, allowing data to be further averaged and explored to address user-specified questions. |
first_indexed | 2024-12-14T22:53:15Z |
format | Article |
id | doaj.art-0d7bd4a8e71b410a8f79fa4111f26d6e |
institution | Directory Open Access Journal |
issn | 2296-7745 |
language | English |
last_indexed | 2024-12-14T22:53:15Z |
publishDate | 2021-08-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Marine Science |
spelling | doaj.art-0d7bd4a8e71b410a8f79fa4111f26d6e2022-12-21T22:44:38ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452021-08-01810.3389/fmars.2021.703650703650Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA)Jennifer L. Miksis-Olds0Peter J. Dugan1S. Bruce Martin2Holger Klinck3Holger Klinck4David K. Mellinger5David A. Mann6Dimitri W. Ponirakis7Olaf Boebel8Center for Acoustics Research and Education, University of New Hampshire, Durham, NH, United StatesK. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY, United StatesJASCO Applied Sciences, Dartmouth, NS, CanadaK. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY, United StatesMarine Mammal Institute, Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Newport, OR, United StatesCooperative Institute for Marine Resources Studies, NOAA Pacific Marine Environmental Laboratory, Oregon State University, Newport, OR, United StatesLoggerhead Instruments, Sarasota, FL, United StatesK. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY, United StatesAlfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, GermanyMaking Ambient Noise Trends Accessible (MANTA) software is a tool for the community to enable comparisons between soundscapes and identification of ambient ocean sound trends required by ocean stakeholders. MANTA enhances the value of individual datasets by assisting users in creating thorough calibration metadata and internationally recommended products comparable over time and space to ultimately assess ocean sound at any desired scale up to a global level. The software package combines of two applications: MANTA Metadata App, which allows users to specify information about their recordings, and MANTA Data Mining App, which applies that information to acoustic recordings to produce consistently processed, calibrated time series products of sound pressure levels in hybrid millidecade bands. The main outputs of MANTA are daily.csv and NetCDF files containing 60-s spectral energy calculations in hybrid millidecade bands and daily statistics images. MANTA data product size and formats enable easy and compact transfer and archiving among researchers and programs, allowing data to be further averaged and explored to address user-specified questions.https://www.frontiersin.org/articles/10.3389/fmars.2021.703650/fullocean soundambient soundsoundscapenoisestandards |
spellingShingle | Jennifer L. Miksis-Olds Peter J. Dugan S. Bruce Martin Holger Klinck Holger Klinck David K. Mellinger David A. Mann Dimitri W. Ponirakis Olaf Boebel Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA) Frontiers in Marine Science ocean sound ambient sound soundscape noise standards |
title | Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA) |
title_full | Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA) |
title_fullStr | Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA) |
title_full_unstemmed | Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA) |
title_short | Ocean Sound Analysis Software for Making Ambient Noise Trends Accessible (MANTA) |
title_sort | ocean sound analysis software for making ambient noise trends accessible manta |
topic | ocean sound ambient sound soundscape noise standards |
url | https://www.frontiersin.org/articles/10.3389/fmars.2021.703650/full |
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