It can be a real challenge to construct the ambient noise modeling among the harbors of very frequent shipping. Therefore, in these harbors, a great amount of resource has to be utilized for precisely control the ambient noise occurring parameters. In this study, the underwater measuring skill is adapted to collect the ambient noise raw data among the first harbor area of Kaohsiung Harbor and the sound intensity of various ships as well. Besides, the signal processing skill is also conducted for ship tracing experiment. The harbor ambient noise mainly comes from ships. Thus, the understanding of ship activity and their different sound intensity can be a great help to construct the ambient noise modeling. The results of this study indicate¡GShips outside the harbor create more low-frequency noise than those inside the harbor.Waves inside the harbor create more middle-frequency noise than those outside the harbor.In the harbor, those ships with onboard electricity create more noise and there is less noise around the wharfs without any ships. In the part of ship noise study, the intensity is usually correlated with ship types, displacement, ship speed, primary engine and auxiliary engine, etc. However, only two ship types, small and large ships, are categorized in this study. Small ships can be operated easily with the most power outcome, which can create the sound intensity of 155 to 165 dB in average. On the contrary, large ships are usually limited within their operating range and can not move with the most power outcome under the security consideration. Therefore, the sound intensity of large ships is measured between 169 to 177 dB. In the ship tracing experiment, operations are the basis for constructing the harbor ambient noise model.

Sound propagation can be greatly affected by seabed, especially in shallow water, therefore by understanding the geoacoustic parameters of sea bottom can help to improve the performance of sonar systems. In this study, ship noise collected by the vertical line array (VLA) in South China Sea experiment of the Asian Seas International Acoustics Experiment (ASIAEX SCS) in 2001 was used as a sound source to invert the geoacoustic parameters. The nearest horizontal distance between VLA and the passing ship was estimated by beamforming the receiving sounds on the array, and this distance was used in the sound propagation modal. In the modal, two layers structure were assumed for the bottom, so the sound speed (C1) and density (£l1) of sediment layer, sound speed (C2 ) and density (£l2) of subbottom layer, and total absorption coefficient (£\) need to be inverted. Matched field processing is used to solve this inverse problem, and computing the minimum cost function between the measured and modeled sound field, the best matched bottom parameters are C1¡×1600 m/s¡BC2¡×1650 m/s¡B£l1=1.6 g/cm3¡B£l2=2.1 g/cm3¡B£\=0.6 dB/£f. These results were compared with chirp sonar survey in this area, and the agreement is satisfactory.

Levels of underwater noise in the open ocean have been increasing since at least the 1960s due to growth in global shipping traffic and the speed and propulsion power of vessels. This rise in noise levels reduces the range over which vocal marine species can communicate, and can induce physiological stress and behavioural responses, which may ultimately have population-level consequences. Although long-term noise trends have been studied at some open-ocean sites, in shallower coastal regions the high spatiotemporal variability of noise levels presents a substantial methodological challenge, and trends in these areas are poorly understood. This thesis addresses this challenge by introducing new techniques which combine multiple data sources for ship noise assessment in coastal waters. These data include Automatic Identification System (AIS) ship-tracking data, shore-based time-lapse footage, meteorological data, and tidal data. Two studies are presented: in the first, AIS data and acoustic recordings from Falmouth Bay in the western English Channel are combined using an adaptive threshold, which separates ship passages from background noise in the acoustic data. These passages are then cross-referenced with AIS vessel tracks, and the noise exposure associated with shipping activity is then determined. The second study, at a site in the Moray Firth, Scotland, expanded the method to include shore-based time-lapse footage, which enables visual corroboration of vessel identifications and the production of videos integrating the various data sources. Two further studies examine and enhance basic analysis techniques for ambient noise monitoring. The first study examines averaging metrics and their applicability to the assessment of noise from shipping. Long-term data from the VENUS observatory are empirically assessed for different averaging times and in the presence of outliers. It is concluded that the mean sound pressure level averaged in linear space is most appropriate, in terms of both standardization and relevance to impacts on marine fauna. In the second study, a new technique for the statistical analysis of long-term passive acoustic datasets, termed spectral probability density (SPD), is introduced. It is shown that the SPD can reveal characteristics such as multimodality, outlier influence, and persistent self-noise, which are not apparent using conventional techniques. This helps to interpret long-term datasets, and can indicate whether an instrument’s dynamic range is appropriate to field conditions. Taken together, the contributions presented in this thesis help to establish a stronger methodological basis for the assessment of shipping noise. These methods can help to inform emerging policy initiatives, efforts to standardise underwater noise measurements, and investigation into the effects of shipping noise on marine life.

Kaohsiung Harbor is one of the major commercial ports in Taiwan, located at the hub of northeastern and southeastern Asia shipping lanes. Therefore there are a considerable number of commercial shipping channels distributed around Kaohsiung Harbor. The security of Kaohsiung Harbor becomes more difficult to defense than others due to the complexity of channels. In this study, Automatic Identification System (AIS) system is used to collect the ships information from June 1, 2010 to June 30, 2011. The collected AIS data were decoded, converted, corrected, integrated and analyzed systematically, which will become the base of future database. The information of the AIS includes Maritime Mobile Service Identity (MMSI), latitude and longitude, heading, course, speed, and others. The activities of ships can be monitored by AIS, so the density and distribution of ships on each major channel can be obtained by grid computing. By the results of one-year AIS data, three major shipping channels of Kaohsiung Harbor can be identified, which are north-western, north-southern, and east-western. Based on this kind of long term shipping statistics, possible novel harbor security defense may be founded. Although the AIS was designed to monitor the ship activities, but it can be viciously shut down, or signal is out of range sometimes, then it will become the possible security breach. Nevertheless, ships at sea will generate certain kind of noises, such as from engine and propeller. With efficient propagation of sound waves in water, acoustic technology may compensate the limitations of AIS, to be a feasible method of detecting unknown ships. In this study, acoustic modeling code ¡§Acoustic Module for Sea-surface Noise¡¨ (AMSN) is applied by using the ship position information from AIS, to calculate the related underwater noise sound field of Kaohsiung Harbor. Discussions were made on the dependence of noise level variation with ship density. As a conclusion, with sufficient understanding of sound field statistics of harbor, any anomaly of noise level can be an indication of hostile intrusion, thus harbor security can be further assured.

Qun-yan Ren received his Diploma in Electronic and Information Engineering, master degree in Underwater Acoustics Engineering both from Harbin Engineering University (HEU) in 2006 and 2009, respectively. Then he became a PhD student at the Environmental Hydroacoustics Laboratory, Ecole polytechnique de Bruxelles, Faculty of Applied Sciences, Universitie libre de Bruxelles (U.L.B.), Belgium, in co-tutelle with the National Key Laboratory of Underwater Acoustic Technology, HEU, China, under the co-supervision of Prof. Jean-Pierre Hermand and Prof. Piao Shengchun from U.L.B. and HEU, respectively. Since 2013, he became a full PhD student at the ULB. In Oct 2011, he obtained a four-year `Aspirantq{} grant from the Belgian National Fund for Scientific Research (F.R.S.-F.N.R.S.). / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished