A Database of Underwater Radiated Noise from Small Vessels in the Coastal Area.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-18 DOI:10.1038/s41597-025-04584-x
Mark Shipton, Juraj Obradović, Fausto Ferreira, Nikola Mišković, Tomislav Bulat, Neven Cukrov, Roee Diamant
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Abstract

The current procedures for measuring underwater radiated noise (URN) are designed for cooperating vessels in controlled areas. As such, not a lot of data is available for the URN of unidentified vessels of opportunity (VOO), especially for small vessels that do not carry an automatic identification systems (AIS). To this end, we assembled a database of 1148 VOO's URN from acoustic and visual recordings of ferries, fishing boats, yachts, and small speed boats made within Šibenik canal, Croatia. The database comprises source pressure levels at the closest point of approach, picture and video of the vessel, and the vessel's speed, size, and type. A shared webpage allows filtering and comparing vessel types and characteristics. In this paper, we share the structure of our database, the analysis methodology. We conclude that the URN of small vessels is significant and compatible to large vessels.

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沿海地区小型船只水下辐射噪声数据库。
现行的水下辐射噪声测量方法是为控制区域内的合作船舶设计的。因此,对于未识别船只(VOO)的URN可用数据并不多,特别是对于没有携带自动识别系统(AIS)的小型船只。为此,我们从克罗地亚Šibenik运河内制造的渡轮、渔船、游艇和小型快艇的声学和视觉记录中收集了1148个VOO的URN数据库。该数据库包括最近接近点的源压力水平、船舶的图片和视频,以及船舶的速度、大小和类型。共享网页允许过滤和比较船舶类型和特性。在本文中,我们分享了我们的数据库结构,分析方法。我们得出结论,小血管的URN是显著的,并与大血管兼容。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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