Estimation of mean grain size of seafloor sediments using neural network

The feasibility of an artificial neural network based approach is investigated to estimate the values of mean grain size of seafloor sediments using four dominant echo features, extracted from acoustic backscatter data. The acoustic backscatter data were collected using a dual-frequency (33 and 210 kHz) single-beam, normal-incidence echo sounder at twenty locations in the central part of the western continental shelf of India. Statistically significant correlations are observed between the estimated average values of mean grain size of sediments and the ground-truth data at both the frequencies. The results indicate that once a multi-layer perceptron model is trained with back-propagation algorithm, the values of mean grain size can reasonably be estimated in an experimental area. The study also revealed that the consistency among the estimated values of mean grain size at different acoustic frequencies is considerably improved with the neural network based method as compared to that with a model-based approach.     

Effects of using inclined parametric echosounding on sub-bottom acoustic imaging and advances in buried object detection

This study reports an adaptation of a parametric echosounder system using 15 kHz as secondary frequency to investigate the angular response of sub-bottom backscatter strength of layered mud, providing a new method for enhanced acoustic detection of buried targets. Adaptions to achieve both vertical (0°) and non-vertical inclination (1–15°, 30°, 45° and 60°) comprise mechanical tilting of the acoustic transducer and electronic beam steering. Data were acquired at 18 m water depth at a study site characterized by a flat, muddy seafloor where a 0.1 m diameter power cable lies 1–2 m below the seafloor. Surveying the cable with vertical incidence revealed that the buried cable can hardly be discriminated against the backscatter strength of the layered mud. However, the backscatter strength of layered mud decreases strongly at >3±0.5° incidence and the layered mud echo pattern vanishes beyond 5°. As a consequence, the backscatter pattern of the buried cable is very pronounced in acoustic images gathered at 15°, 30°, 45° and 60° incidence. The size of the cable echo pattern increases linearly with incidence. These effects are attributed to reflection loss from layered mud at larger incidence and to the scattering of the 0.1 m diameter buried cable. Data analyses support the visual impression of superior detection of the cable with an up to 2.6-fold increase of the signal-to-noise ratio at 40° incidence compared to the vertical incidence case.     

海底沉积物声学特征定量分析及其智能分类研究

海底底质特性描述及分类是当今浅海声学的研究热点,海底沉积物的物理结构特性与其声学响应特征密切相关。在分析海底沉积物声传播特性的基础上,应用现代计算机信号分析技术手段,对海底沉积物声学响应波形提取了4个特征参数:声速、波幅指数、波形关联维分形指数和声波频谱的频率矩。以这4个特征参数作为输入向量,海底沉积物的结构类型作为输出向量,建立径向基概率神经网络模型。研究表明建立的神经网络模型具有较强的海底沉积物分类预报能力。     

Multi-angle backscatter classification and sub-bottom profiling for improved seafloor characterization

This study applies three classification methods exploiting the angular dependence of acoustic seafloor backscatter along with high resolution sub-bottom profiling for seafloor sediment characterization in the Eckernförde Bay, Baltic Sea Germany. This area is well suited for acoustic backscatter studies due to its shallowness, its smooth bathymetry and the presence of a wide range of sediment types. Backscatter data were acquired using a Seabeam1180 (180 kHz) multibeam echosounder and sub-bottom profiler data were recorded using a SES-2000 parametric sonar transmitting 6 and 12 kHz. The high density of seafloor soundings allowed extracting backscatter layers for five beam angles over a large part of the surveyed area. A Bayesian probability method was employed for sediment classification based on the backscatter variability at a single incidence angle, whereas Maximum Likelihood Classification (MLC) and Principal Components Analysis (PCA) were applied to the multi-angle layers. The Bayesian approach was used for identifying the optimum number of acoustic classes because cluster validation is carried out prior to class assignment and class outputs are ordinal categorical values. The method is based on the principle that backscatter values from a single incidence angle express a normal distribution for a particular sediment type. The resulting Bayesian classes were well correlated to median grain sizes and the percentage of coarse material. The MLC method uses angular response information from five layers of training areas extracted from the Bayesian classification map. The subsequent PCA analysis is based on the transformation of these five layers into two principal components that comprise most of the data variability. These principal components were clustered in five classes after running an external cluster validation test. In general both methods MLC and PCA, separated the various sediment types effectively, showing good agreement (kappa >0.7) with the Bayesian approach which also correlates well with ground truth data (r²?>?0.7). In addition, sub-bottom data were used in conjunction with the Bayesian classification results to characterize acoustic classes with respect to their geological and stratigraphic interpretation. The joined interpretation of seafloor and sub-seafloor data sets proved to be an efficient approach for a better understanding of seafloor backscatter patchiness and to discriminate acoustically similar classes in different geological/bathymetric settings.     

Toward remote seafloor classification using the angular response ofacoustic backscattering: a case study from multiple overlapping GLORIAdata

While the average seafloor backscatter strength within a narrow range of grazing angles can be used as a first-order classification tool, this technique often fails to distinguish seafloors of known differing geological character. In order to resolve such ambiguities, it is necessary to examine the variation in backscatter strength as a function of grazing angle. For this purpose, a series of multiply overlapping GLORIA sidescan sonar images (6.5 kHz) have been obtained in water depths ranging from 1000 to 2500 m. To constrain the placement of acoustic backscatter measurements and to measure the true impinging angle of the incident wave, the corresponding seafloor was simultaneously surveyed using the Seabeam multibeam system. As a result of the multiple overlap, the angular response of seafloor backscatter strength may be derived for regions much smaller than the swath width. By using the derived angular response of seafloor backscatter strength in regions for which sediment samples exist, an empirical seafloor classification scheme is proposed based on the shape, variance, and magnitude of the angular response. Because of the observed variability in the shape of the angular response with differing seafloor types, routine normalization of single-pass swath data to an equivalent single grazing angle image cannot be achieved. As a result, for the case of single-pass surveys, confident seafloor classification may only be possible for regions approaching the scale of the swath width     

Single-beam acoustic ground discrimination of shallow water habitats: 50 kHz or 200 kHz frequency survey?

The single-beam acoustic ground discrimination system QTC View, Series V, was used in the Bay of Cadiz, Southwest Spain, for the identification and mapping of the bottom acoustic diversity. The acoustic data were obtained through two successive surveys, each conducted with one of the following echo sounder frequencies: 50 kHz and 200 kHz. The performance of each survey frequency for the identification of the sedimentary gradients was analyzed. The surveys were conducted during high tide given that the majority of the surveyed area is shallower than 5 m, although depth may occasionally reach 20 m in specific areas located in a navigation channel. The acoustic data obtained at the two different frequencies were, individually, submitted to manual clustering and a final solution consisting of three acoustic classes was reached for both datasets. However, only the geographical distribution of the acoustic classes obtained with 50 kHz echo sounder frequency was coincident with the spatial distribution of the superficial sediment groups (silty medium sand, very silty fine sand and mud), identified through multivariate analysis of the grain-size data of ground-truth sediment samples. The results obtained with the 200 kHz echo sounder frequency did not match the sedimentary gradients obtained for the area surveyed, not even the separation of muddy and sandy areas.     

Calibration techniques and sampling resolution requirements for groundtruthing multibeam acoustic backscatter (EM3000) and QTC VIEW™ classification technology

Both acoustic and sediment surveys were carried out in the Broughton Archipelago, British Columbia, in order to map a former aquaculture site and calibrate acoustic surveys with georeferenced sediment properties. The acoustic surveys included EM3000 Multibeam (including backscatter) and QTC VIEW™ (Series IV) technologies, while the geotechnical survey entailed Van Veen grab sampling of surface sediments and associated analyses. The two acoustic technologies were consistent in their ability to identify distinct regions of seafloor characterized by rock outcrops, consolidated substrates, or gel-mud depositional fields. Both multibeam backscatter data and QTC VIEW™ number-coded classifications were extracted across a range of circular areas located at each georeferenced sampling station (radii: 2, 3, 4, 5, 8, 12, 16, 20 m). Statistical correlations were observed between backscatter and certain geotechnical properties, such as sediment porosity, sediment grain size fractions (<2 μm, silt content), and particulate sulfur concentration. The areal resolution of backscatter extraction was explored in terms of determining a sensitive calibration technique between backscatter and sediment properties. In general the highest r² values between backscatter and sediment variables were observed across extraction radii between 8 and 20 m. Such groundtruthing techniques could be used to interpolate seafloor characteristics between sampling stations and provide a steering tool for sampling designs associated with benthic monitoring programs.     

多波束反向散射强度数据处理研究

在探讨多波束测深系统反向散射强度与海底底质类型的关系基础上,研究影响反向散射强度的各种因素,主要分析了海底地形起伏、中央波束区反射信号对反向散射强度的影响,并给出了消除这些影响的方法;将处理后的“纯”反向散射强度数据镶嵌生成海底声像图,为海底底质类型划分以及地貌解译提供了基础数据和辅助判读依据.     

Processing Multibeam Backscatter Data

A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research.     

Processing Multibeam Backscatter Data

A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research.     

Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data

The variation of the backscatter strength with the angle of incidence is an intrinsic property of the seafloor, which can be used in methods for acoustic seafloor characterization. Although multibeam sonars acquire backscatter over a wide range of incidence angles, the angular information is normally neglected during standard backscatter processing and mosaicking. An approach called Angular Range Analysis has been developed to preserve the backscatter angular information, and use it for remote estimation of seafloor properties. Angular Range Analysis starts with the beam-by-beam time-series of acoustic backscatter provided by the multibeam sonar and then corrects the backscatter for seafloor slope, beam pattern, time varying and angle varying gains, and area of insonification. Subsequently a series of parameters are calculated from the stacking of consecutive time series over a spatial scale that approximates half of the swath width. Based on these calculated parameters and the inversion of an acoustic backscatter model, we estimate the acoustic impedance and the roughness of the insonified area on the seafloor. In the process of this inversion, the behavior of the model parameters is constrained by established inter-property relationships. The approach has been tested using a 300 kHz Simrad EM3000 multibeam sonar in Little Bay, NH. Impedance estimates are compared to in situ measurements of sound speed. The comparison shows a very good correlation, indicating the potential of this approach for robust seafloor characterization.     

High-resolution mapping of large gas emitting mud volcanoes on the Egyptian continental margin (Nile Deep Sea Fan) by AUV surveys

Two highly active mud volcanoes located in 990–1,265 m water depths were mapped on the northern Egyptian continental slope during the BIONIL expedition of R/V Meteor in October 2006. High-resolution swath bathymetry and backscatter imagery were acquired with an autonomous underwater vehicle (AUV)-mounted multibeam echosounder, operating at a frequency of 200 kHz. Data allowed for the construction of ~1 m pixel bathymetry and backscatter maps. The newly produced maps provide details of the seabed morphology and texture, and insights into the formation of the two mud volcanoes. They also contain key indicators on the distribution of seepage and its tectonic control. The acquisition of high-resolution seafloor bathymetry and acoustic imagery maps with an AUV-mounted multibeam echosounder fills the gap in spatial scale between conventional multibeam data collected from a surface vessel and in situ video observations made from a manned submersible or a remotely operating vehicle.     

Seafloor acoustic remote sensing with multibeam echo-sounders and bathymetric sidescan sonar systems

This paper examines the potential for remote classification of seafloor terrains using a combination of quantitative acoustic backscatter measurements and high resolution bathymetry derived from two classes of sonar systems currently used by the marine research community: multibeam echo-sounders and bathymetric sidescans sonar systems. The high-resolution bathymetry is important, not only to determine the topography of the area surveyed, but to provide accurate bottom slope corrections needed to convert the arrival angles of the seafloor echoes received by the sonars into true angles of incidence. An angular dependence of seafloor acoustic backscatter can then be derived for each region surveyed, making it possible to construct maps of acoustic backscattering strength in geographic coordinates over the areas of interest. Such maps, when combined with the high-resolution bathymetric maps normally compiled from the data output by the above sonar systems, could be very effective tools to quantify bottom types on a regional basis, and to develop automatic seafloor classification routines.     

Seabed characterization through a range of high-resolution acoustic systems – a case study offshore Oman

This study uses three acoustic instruments (different in their operating frequencies, 13, 3.5, and 6–10 kHz, and deployment type, hull-mounted, surface-towed and deep-towed) to investigate and characterize the acoustic response of seafloor NE of Oman in a frequency-independent manner. High-resolution control was achieved by having selected areas of our acoustic transects ground-truthed by sampling and/or sea-floor photography. On the regional scale, the greatest degree of change in backscatter amplitude was correlated with major changes of seabed morphology and lithology. However, small-scale roughness had the biggest effect on amplitude on the local scale, i.e. within each area of specific seafloor type. The study also shows that seafloor reflection amplitude changes are far more easily detected by deep-towed instrument than by surface-towed or hull-mounted systems. Whilst there are significant changes in bioturbation types and density along the transects, the suite of instruments deployed was not able to pick up the effect of the bioturbation on acoustic signals.     

济州岛南部海域海底声呐图像分析与声学底质分类

东海北部外陆架靠近济州岛南部海域,是黄海槽向冲绳海槽延伸的部分,属于黑潮分支黄海暖流的通道入口,分布着脊槽相间的海底底形,对其海底声呐图像的处理分析及声学底质分类的分析研究,有助于了解该通道海底底形表层纹理特征及沉积物分布规律。基于在济州岛南部海域获取的多波束声呐数据,应用图像处理技术和方法,对数据进行了处理,获得了海底声呐影像图,并对其表层纹理特征进行了描述和分析;同时,基于多波束反向散射强度数据,结合19组海底地质取样数据,建立研究区海底反向散射强度与沉积物粒度特征之间的统计关系模型,并以改进的学习向量量化神经网络方法,实现对海底粉砂质砂、黏土质砂以及砂-粉砂-黏土3种底质类型的快速自动分类识别。     

Seafloor and buried mounds on the western slope of the Niger Delta

Seafloor mounds are potential geohazards to offshore rig emplacement and drilling operations and may contain evidence of underlying petroleum systems. Therefore, identifying and mapping them is crucial in de-risking exploration and production activities in offshore domains.A 738 km² high resolution three-dimensional seismic dataset was used to investigate the occurrence, seismic characteristics and distribution of features interpreted as seafloor and buried sediment mounds, at water-depths of 800–1600 m, on the western Niger Delta slope. Fifteen seafloor mounds and eighteen shallowly buried mounds were identified. The seafloor mounds are characterised by lower seismic amplitude anomalies than the surrounding seabed sediments, and overlie vertical zones of acoustic blanking. The buried mounds in contrast are characterised by high amplitude anomalies; they also directly overlie sub-vertical zones of acoustic blanking. Seismic evidences from the features, their distribution patterns and tectono-stratigraphic associations suggest that their formation was controlled by the juxtaposition of buried channels and structural highs and their formation caused by focused fluid flow and expulsion of entrained sediments at the seabed.Considering the acoustic and geometrical characteristics of the mounds and comparing them with mound-shaped features from around the world, we conclude that the mounds most likely comprise heterolithic seafloor extrusions of muds and sands from the Agbada Formation with gas and possibly oil in some of the pore space giving rise to the acoustic characteristics.     

Investigation of the relationship between seafloor echo strength and sediment type—a case study in Jiaozgou Bay,China

In recent years, increasing attention is being given to investigating the relationships between seafloor echo strength and sediment type. This aspect was assessed in a course of a marine survey conducted in Jiaozhou Bay near the city of Qingdao, China, where various sediment types are known to exist. Multi-beam echo data and sediment samples were acquired, processed and analyzed. The findings demonstrate that multi-beam echo strengths are strongly related to seabed types such as rock, sand and clay. Thus, echo strength increases progressively with the increase in sand content in gravely, sandy, and clayey sediments. However, echo strength is more sensitive to changes in sand content in fine-grained sediment and less sensitive in coarse-grained sediment. Also, high shell content of sediments greatly enhances the acoustic reflection. These findings help to predict seafloor sediment types by analyzing echo strength.     

声学方法进行海底沉积物遥测分类:综述

本文讨论利用声学遥测方法进行海底沉积物分类的目的、用途及该项技术的发展背景和现状。重点介绍目前主要的用于浅、表层沉积物分类的声学遥测方法，包括选通等幅脉冲、宽频带脉冲、连续线性扫频脉冲等正入射方法和侧扫声呐、多波束测深等斜入射方法。回顾它们的发展历史，评述它们的技术现状，并讨论它们的进一步发展     

A framework to quantify uncertainties of seafloor backscatter from swath mapping echosounders

Multibeam echosounders (MBES) have become a widely used acoustic remote sensing tool to map and study the seafloor, providing co-located bathymetry and seafloor backscatter. Although the uncertainty associated with MBES-derived bathymetric data has been studied extensively, the question of backscatter uncertainty has been addressed only minimally and hinders the quantitative use of MBES seafloor backscatter. This paper explores approaches to identifying uncertainty sources associated with MBES-derived backscatter measurements. The major sources of uncertainty are catalogued and the magnitudes of their relative contributions to the backscatter uncertainty budget are evaluated. These major uncertainty sources include seafloor insonified area (1–3 dB), absorption coefficient (up to >?6 dB), random fluctuations in echo level (5.5 dB for a Rayleigh distribution), and sonar calibration (device dependent). The magnitudes of these uncertainty sources vary based on how these effects are compensated for during data acquisition and processing. Various cases (no compensation, partial compensation and full compensation) for seafloor insonified area, transmission losses and random fluctuations were modeled to estimate their uncertainties in different scenarios. Uncertainty related to the seafloor insonified area can be reduced significantly by accounting for seafloor slope during backscatter processing while transmission losses can be constrained by collecting full water column absorption coefficient profiles (temperature and salinity profiles). To reduce random fluctuations to below 1 dB, at least 20 samples are recommended to be used while computing mean values. The estimation of uncertainty in backscatter measurements is constrained by the fact that not all instrumental components are characterized and documented sufficiently for commercially available MBES. Further involvement from manufacturers in providing this essential information is critically required.     

A methodology for acoustic seafloor classification

A seafloor classification methodology, based on a parameterization of the reverberation probability density function in conjunction with neural network classifiers, is evaluated through computer simulations. Different seafloor provides are represented by a number of scatterer distributions exhibiting various degrees of departure from the nominal Poisson distribution. Using a computer simulation program, these distributions were insonified at different spatial scales by varying the transmitted pulse length. The statistical signature obtained consists of reverberation kurtosis estimates as a function of pulse length. Two neural network classifiers are presented with the task of discriminating among the various scatterer distributions based on obtained acoustic signatures. The results indicate that this approach offers considerable promise for practical, realizable solutions to the problem of remote seafloor classification