PhD_Parcerisas: Broadband Acoustic Network dataset
Citation
Parcerisas Clea, Dick Botteldooren, Paul Devos, Debusschere Elisabeth, Flanders Marine Institute (VLIZ); 2021; Broadband Acoustic Network dataset. https://marineinfo.org/doc/dataset/7879
Contact:
Parcerisas, Clea Availability:
 This dataset is licensed under a Creative Commons Attribution 4.0 International License.Notes: Only data older than 1 year from the current date are available.
Description
Underwater Acoustic Network recording continuously from 10 Hz to 50 kHz, covering most of geophonic sounds, anthropogenic noise and biophonic events in the Belgian Part of the North Sea. moreMetadata can be found at https://rshiny.lifewatch.be/etn-data/ Scope Themes: Biology, Biology > Ecology - biodiversity, Biology > Fish Keywords: Marine/Coastal · Acoustic data · Acoustic telemetry · Acoustic Telemetry · Acoustic tracking · Acoustic tracking systems · Acoustics · Anthropogenic impacts · Anthropogenic sound · Belgian part of the North Sea · Ecology · Man-induced effects · Sound · Tracking networks · Underwater sound · Belgian Coast · Belgian Continental Shelf (BCS) · Animalia Geographical coverage Belgian Coast [Marine Regions] Belgian Continental Shelf (BCS) [Marine Regions] Temporal coverage
From 9 March 2021 on [In Progress] Taxonomic coverage
Animalia [WoRMS]
Parameter
Detections Methodology
Detections: Acoustic telemetry Contributors
Related datasets
Parent datasets: European Tracking Network (ETN) data, more Lifewatch observatory data: Broadband acoustic sensor network in the Belgian Part of the North Sea, more Child datasets: Acoustic salient event annotations, more LifeWatch Broadband acoustic network in the Belgian Part of the North Sea: Dataset annotated with AIS 2022, more Subset of acoustic data with AIS labels deployment from Grafton station in the Belgian Part of the North Sea, recorded in fall 2022, more Source dataset: Annotated unknown underwater sounds in the Belgian part of the North Sea, more Other relation: SoundLib: Marine Underwater SoundLib: underwater sound recordings of anthropogenic sources, more Project
PhD: Marine Soundscapes in Shallow Water: Automated Tools for Characterization and Analysis, more
Funding Own budget, for example: patrimony, inscription fees, gifts
Grant agreement ID DOCT/003826
Publication
Based on this dataset
Calonge, A. et al. (2024). Revised clusters of annotated unknown sounds in the Belgian part of the North sea. Front. Remote Sens. 5: 1384562. https://dx.doi.org/10.3389/frsen.2024.1384562, more
Parcerisas, C. (2024). Marine soundscapes in shallow water: Automated tools for characterization and analysis. VLIZ PhD Theses, 4. Ir Thesis. Ghent University, Faculty of Engineering and Architecture: Ghent. ISBN 978-94-6355-848-8. 370 pp., more
Parcerisas, C. et al. (2024). Machine learning for efficient segregation and labeling of potential biological sounds in long-term underwater recordings. Front. Remote Sens. 5: 1390687. https://dx.doi.org/10.3389/frsen.2024.1390687, more
Schmidlin, S. et al. (2024). Comparison of the effects of reef and anthropogenic soundscapes on oyster larvae settlement. NPG Scientific Reports 14(1): 12580. https://dx.doi.org/10.1038/s41598-024-63322-2, more
Parcerisas, C. et al. (2023). Categorizing shallow marine soundscapes using explained clusters. J. Mar. Sci. Eng. 11(3): 550. https://dx.doi.org/10.3390/jmse11030550, more
Rey Baquero, M.P. et al. (2021). Comparison of two soundscapes: An opportunity to assess the dominance of biophony versus anthropophony, in: Kappel, E.S. et al. Frontiers in Ocean Observing: Documenting ecosystems, understanding environmental changes, forecasting hazards. Oceanography, Suppl. 34(4): pp. 62-65. https://dx.doi.org/10.5670/oceanog.2021.supplement.02-24, more
Describing this dataset
Calonge, A. et al. (2026). Scalable low-cost seabed landers: The missing link for sustained, integrated, long-term observations in dynamic shallow seas. Remote Sensing in Ecology and Conservation Online first: 1-9. https://dx.doi.org/10.1002/rse2.70072, more
URL
Dataset status: In Progress
Data type: Data
Data origin: Research: field survey
Metadatarecord created: 2021-09-23
Information last updated: 2024-06-11
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