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NOAA-Navy Sanctuary Soundscape Monitoring Project, Humpback Whale Sound Production, Hawaiian Islands, SanctSound_HI01_02_GoogleAI_humpbackwhale_1h

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coastwatch.pfeg.noaa.gov2025-01-15 收录
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NOAA and the U.S. Navy are working to better understand underwater sound within the U.S. National Marine Sanctuary System. From 2018 to 2021, these agencies will work with numerous scientific partners to study sound within seven national marine sanctuaries and one marine national monument, which includes waters off Hawai'i and the east and west coasts. Standardized measurements will assess sounds produced by marine animals, physical processes (e.g., wind and waves), and human activities. Collectively, this information will help NOAA and the Navy measure sound levels and baseline acoustic conditions in sanctuaries. This work is a continuation of ongoing Navy and NOAA research, including efforts by NOAA's Office of National Marine Sanctuaries This dataset represents the derived products from the raw acoustic data that are archived at NOAA National Centers for Environmental Information. abstract=This record represents humpback whale sound production detected from raw passive acoustic data.All continuous acoustic data were divided into 30 s wav file subsamples and processed using a machine learning humpback whale detector model developed and provided by Google (GoogleAI; Matt Harvey). The presence of humpback whale song is scored by the model and, compared to a choosen threshold, was assigned a binary 0/1 designation indicating absence (0) or presence (1). The percentage of files with humpback whale presence per hour was calculated.These data were recorded at SanctSound Site HI01_02 between December 01, 2019 and April 11, 2020. acknowledgement=This project received funding from the U.S. Navy. cdm_data_type=TimeSeries citation=Cite as: NOAA Office of National Marine Sanctuaries and U.S Navy. 2021. Humpback Whale Sound Production Recorded at SanctSound Site HI01_02, SanctSound Data Products. NOAA National Centers for Environmental Information. Accessed [date]. DOI: https://doi.org/http://doi.org/10.25921/zpw7-p870 comment=Data quality: Data were compromised after 04/11/2020 and excluded. contributor_name=Simone Baumann-Pickering, Scripps Institution of Oceanography; Leila Hatch, NOAA Stellwagen Bank National Marine Sanctuary; John Joseph, U.S. Naval Postgraduate School; Anke Kuegler, Hawai'i Institute of Marine Biology, University of Hawai'i at Manoa; Marc Lammers, NOAA Hawaiian Islands Humpback Whale National Marine Sanctuary; Tetyana Margolina, U.S. Naval Postgraduate School; Karlina Merkens, NOAA Pacific Islands Fisheries Science Center; Lindsey Peavey Reeves, NOAA Channel Islands National Marine Sanctuary; Timothy Rowell, NOAA Northeast Fisheries Science Center; Jenni Stanley, Woods Hole Oceanographic Institution; Alison Stimpert, Moss Landing Marine Laboratories; Sofie Van Parijs, NOAA Northeast Fisheries Science Center; Eden Zang,NOAA Hawaiian Islands Humpback Whale National Marine Sanctuary contributor_role=Principal Investigator Conventions=COARDS, CF-1.6, ACDD-1.3 featureType=TimeSeries geospatial_bounds=POINT (20.80734 -156.65543) history=All continuous acoustic data were divided into 30 s wav file subsamples. All 30 s recordings were processed using a machine learning humpback whale detector model developed and provided by Google (GoogleAI; Matt Harvey), which steps through each recording at 1.1 s intervals. At each step, the presence of humpback whale song is scored by the model, resulting in 27 scores for each file. The mean out of the 27 scores was calculated and upon meeting a choosen threshold of 0.25 was assigned a binary 0/1 designation indicating absence (0) or presence (1) of humpback whale song within the file. The percentage of files with humpback whale presence per hour was calculated. Data were processed with GoogleAI id=http://doi.org/10.25921/zpw7-p870 infoUrl=https://ncei.noaa.gov institution=NOAA instrument=SoundTrap ST500 keywords_vocabulary=GCMD Science Keywords naming_authority=NOAA-Navy project=NOAA-Navy Sanctuary Soundscape Monitoring Project sourceUrl=(local files) standard_name_vocabulary=CF Standard Name Table v55

国家海洋和大气管理局(NOAA)及美国海军正致力于深入理解美国国家海洋保护区系统内的水下声音。自2018年至2021年,这些机构将与众多科学合作伙伴合作,研究七个国家海洋保护区和一个海洋国家纪念碑内的声音,包括夏威夷群岛以及东海岸和西海岸附近海域。标准化的测量将评估由海洋动物、物理过程(例如风浪)以及人类活动产生的声音。汇总这些信息,将有助于NOAA和海军测量保护区内的声音水平和声学基线条件。这项工作是对海军和NOAA持续研究工作的延续,包括国家海洋保护区办公室的努力。该数据集代表了对存档于NOAA国家环境信息中心的原始声学数据的衍生产品。
提供机构:
ERDDAP Data Server at NOAA NMFS SWFSC Environmental Research Division
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