Multibeam Backscatter Research Articles

Linking the morphology and ecology of subtidal soft-bottom marine benthic habitats: A novel multiscale approach

High-resolution surveying techniques of subtidal soft-bottom seafloor habitats show higher small-scale variation in topography and sediment type than previously thought, but the ecological relevance of this variation remains unclear. In addition, high-resolution surveys of benthic fauna show a large spatial variability in community composition, but this has yet poorly been linked to seafloor morphology and sediment composition. For instance, on soft-bottom coastal shelves, hydrodynamic forces from winds and tidal currents can cause nested multiscale morphological features ranging from metre-scale (mega)ripples, to sand waves and kilometre-scale linear sandbanks. This multiscale habitat heterogeneity is generally disregarded in the ecological assessments of benthic habitats. We therefore developed and tested a novel multiscale assessment toolbox that combines standard bathymetry, multibeam backscatter classification, video surveying of epibenthos and box core samples of sediment and macrobenthos. In a study on the Brown Bank, a sandbank in the southern North Sea, we found that these methods are greatly complementary and allow for more detail in the interpretation of benthic surveys. Acoustic and video data characterised the seafloor surface and subsurface, and macrobenthos communities were found to be structured by both sandbank and sand wave topography. We found indications that acoustic techniques can be used to determine the location of epibenthic reefs. The multiscale assessment toolbox furthermore allows formulating recommendations for conservation management related to the impact of sea floor disturbances through dredging and trawling.

Mapping the Seabed and Shallow Subsurface with Multi-Frequency Multibeam Echosounders

Multi-frequency multibeam backscatter (BS) has indicated, in particular for fine sediments, the potential for increasing the discrimination between different seabed environments. Fine sediments are expected to have a varying signal penetration within the frequency range of modern multibeam echosounders (MBESs). Therefore, it is unknown to what extent the multispectral MBES data represent the surface of the seabed or different parts of the subsurface. Here, the effect of signal penetration on the measured multi-frequency BS and bathymetry is investigated. To this end, two multi-frequency datasets (90 to 450 kHz) were acquired with an R2Sonic 2026 MBES, supported by ground-truthing, in the Vlietland Lake and Port of Rotterdam (The Netherlands). In addition, a model to simulate the MBES bathymetric measurements in a layered medium is developed. The measured bathymetry difference between the lowest (90 kHz) and highest frequency (450 kHz) in areas with muddy sediments reaches values up to 60 cm dependent on the location and incident angle. In spatial correspondence with the variation in the depth difference, the BS level at the lowest frequency varies by up to 15 dB for the muddy sediments while the BS at the highest frequency shows only small variations. A comparison of the acoustic results with the ground-truthing, geological setting and model indicates that the measured bathymetry and BS at the different frequencies correspond to different parts of the seabed. However, the low-frequency BS cannot be directly related to a subsurface layer because of a significant sound attenuation in the upper layer. The simulation of the MBES bottom detection indicates that the bathymetry measured at the highest and lowest frequency can be used to determine the thickness of thin layers (∼20 cm). However, with an increasing layer thickness, the bottom detection becomes more sensitive to the incident angle and small variations in the sediment properties. Consequently, an accurate determination of the layer thickness is hampered. Based on this study, it is highly recommended to analyze multi-frequency BS in combination with the inter-frequency bathymetry difference to ensure a correct interpretation and classification of multi-frequency BS data.

Mapping seabed sediments for Sharm Obhur using multibeam echosounder backscatter data

The observed hydrographic surveying data from multibeam echosounder system (MBES) contains sounding and backscatter intensity data that can be utilized in many coastal and marine applications such as marine geological and environmental investigations. In this paper, the seabed sediments mapping for Sharm Obhur (Obhur Creek) was derived using backscatter intensity data. The backscatter data were radiometrically and geometrically corrected to produce a seabed backscatter mosaic for Sharm Obhur study area. Then, the angular response analysis was implemented to derive the seabed sediment’s grain size, classification (gravel, sand and mud) and associated confidence level values that identify the quality of the classification method implemented in this paper. It was shown that the mouth in the south of the Sharm Obhur mainly contains sand sediments, however, the north side of the Sharm Obhur contains mud sediments and gravel sediments can be seen in very small areas. Moreover, it was found that the successful rate of classification is 90% based on the estimated confidence values. To validate the derived seabed sedimentation map, a comparison was made between the grab sampling results reported in the literature and the seabed sediments types derived in this paper. The comparison showed that the derived seabed sediments results using angular response model agree with the grab sampling results. The advantage of mapping the seabed sedimentation using multibeam backscatter data over the grab sampling method is that it can provide the seabed sediment mapping for the entire area using the MBES due to its 100% coverage of the seabed.

Tidal inlets in the Anthropocene: Geomorphology and benthic habitats of the Chioggia inlet, Venice Lagoon (Italy)

AbstractAdopting a multidisciplinary approach, we mapped with unprecedented detail the seafloor morphology, sediment distribution and benthic habitats of a tidal inlet in the Venice Lagoon, Italy, which has been greatly impacted by human activity. Thanks to very high‐resolution multibeam data, we identified ebb and flood‐tidal deltas, a tidal point bar, active dune fields, pools and scour holes.The seafloor substrate of the inlet was investigated by integrating automatically classified multibeam backscatter data with sediment samples and underwater seafloor images. The sediment composition comprises four textural classes with 75% overall thematic accuracy. The particle size distribution of each morphological feature was assessed distinguishing, in particular, sediments over crests and troughs of small‐dune fields with wavelengths and heights of less than 4 m and 0.2 m, respectively.Adopting state‐of‐the‐art benthic habitat mapping procedures, we found seven distinctive benthic habitats that reflect spatial variability in hydrodynamics and sediment transport pathways. The dominant classes were Sand with sparse shell detritus (46%) and Bare sand (32%). The rip‐rap revetment used for the inlet jetties and for the hard structures, built in the inlet channel to protect Venice from flooding, created a new habitat that covers 5.5% of the study area. This study shows how combining geomorphological and ecological analyses is crucial for the monitoring and management of tidal inlets and coastal infrastructures. © 2019 John Wiley & Sons, Ltd.

Insights into the Short-Term Tidal Variability of Multibeam Backscatter from Field Experiments on Different Seafloor Types

Three experiments were conducted in the Belgian part of the North Sea to investigate short-term variation in seafloor backscatter strength (BS) obtained with multibeam echosounders (MBES). Measurements were acquired on predominantly gravelly (offshore) and sandy and muddy (nearshore) areas. Kongsberg EM3002 and EM2040 dual MBES were used to carry out repeated 300-kHz backscatter measurements over tidal cycles (~13 h). Measurements were analysed in complement to an array of ground-truth variables on sediment and current nature and dynamics. Seafloor and water-column sampling was used, as well as benthic landers equipped with different oceanographic sensors. Both angular response (AR) and mosaicked BS were derived. Results point at the high stability of the seafloor BS in the gravelly area (<0.5 dB variability at 45° incidence) and significant variability in the sandy and muddy areas with envelopes of variability >2 dB and 4 dB at 45° respectively. The high-frequency backscatter sensitivity and short-term variability are interpreted and discussed in the light of the available ground-truth data for the three experiments. The envelopes of variability differed considerably between areas and were driven either by external sources (not related to the seafloor sediment), or by intrinsic seafloor properties (typically for dynamic nearshore areas) or by a combination of both. More specifically, within the gravelly areas with a clear water mass, seafloor BS measurements where unambiguous and related directly to the water-sediment interface. Within the sandy nearshore area, the BS was shown to be strongly affected by roughness polarization processes, particularly due to along- and cross-shore current dynamics, which were responsible for the geometric reorganization of the morpho-sedimentary features. In the muddy nearshore area, the BS fluctuation was jointly driven by high-concentrated mud suspension dynamics, together with surficial substrate changes, as well as by water turbidity, increasing the transmission losses. Altogether, this shows that end-users and surveyors need to consider the complexity of the environment since its dynamics may have severe repercussions on the interpretation of BS maps and change-detection applications. Furthermore, the experimental observations revealed the sensitivity of high-frequency BS values to an array of specific configurations of the natural water-sediment interface which are of interest for monitoring applications elsewhere. This encourages the routine acquisition of different and concurrent environmental data together with MBES survey data. In view of promising advances in MBES absolute calibration allowing more straightforward data comparison, further investigations of the drivers of BS variability and sensitivity are required.

3D controlled-source electromagnetic imaging of gas hydrates: Insights from the Pelotas Basin offshore Brazil

Mapping of natural gas hydrate systems has been performed successfully in the past using the controlled-source electromagnetic (CSEM) method. This method relies on differentiating resistive highly saturated free gas or hydrate-bearing host sediment from a less resistive low-saturated gas or brine-bearing host sediments. Knowledge of the lateral extent and resistivity variations (and hence the saturation variations) within sediments that host hydrates is crucial to be able to accurately quantify the presence of saturated gas hydrates. A 3D CSEM survey (PUCRS14) was acquired in 2014 in the Pelotas Basin offshore Brazil, with hydrate resistivity mapping as the main objective. The survey was acquired within the context of the CONEGAS research project, which investigated the origin and distribution of gas hydrate deposits in the Pelotas Basin. We have inverted the acquired data using a proprietary 3D CSEM anisotropic inversion algorithm. Inversion was purely CSEM data driven, and we did not include any a priori information in the process. Prior to CSEM, interpretation of near-surface geophysical data including 2D seismic, sub-bottom profiler, and multibeam bathymetry data indicated possible presence of gas hydrates within features identified such as faults, chimneys, and seeps leading to pockmarks, along the bottom simulating reflector and within the gas hydrate stability zone. Upon integration of the same with CSEM-derived resistivity volume, the interpretation revealed excellent spatial correlation with many of these features. The interpretation further revealed new features with possible hydrate presence, which were previously overlooked due to a lack of a clear seismic and/or multibeam backscatter signature. In addition, features that were previously mapped as gas hydrate bearing had to be reinterpreted as residual or low-saturated gas/hydrate features, due to the lack of significant resistivity response associated with them. Furthermore, we used the inverted resistivity volume to derive the saturation volume of the subsurface using Archie’s equation.

A Multispectral Bayesian Classification Method for Increased Acoustic Discrimination of Seabed Sediments Using Multi-Frequency Multibeam Backscatter Data

Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed sediments. We propose an extension of the Bayesian method for seabed classification to multi-frequency backscatter. By combining the information retrieved at single frequencies we produce a multispectral acoustic classification map, which allows us to distinguish more seabed environments. In this study we use three triple-frequency (100, 200, and 400 kHz) backscatter datasets acquired with an R2Sonic 2026 in the Bedford Basin, Canada in 2016 and 2017 and in the Patricia Bay, Canada in 2016. The results are threefold: (1) combining 100 and 400 kHz, in general, reveals the most additional information about the seabed; (2) the use of multiple frequencies allows for a better acoustic discrimination of seabed sediments than single-frequency data; and (3) the optimal frequency selection for acoustic sediment classification depends on the local seabed. However, a quantification of the benefit using multiple frequencies cannot clearly be determined based on the existing ground-truth data. Still, a qualitative comparison and a geological interpretation indicate an improved discrimination between different seabed environments using multi-frequency backscatter.

The Hyper-Angular Cube Concept for Improving the Spatial and Acoustic Resolution of MBES Backscatter Angular Response Analysis

This study presents a novel approach, based on high-dimensionality hydro-acoustic data, for improving the performance of angular response analysis (ARA) on multibeam backscatter data in terms of acoustic class separation and spatial resolution. This approach is based on the hyper-angular cube (HAC) data structure which offers the possibility to extract one angular response from each cell of the cube. The HAC consists of a finite number of backscatter layers, each representing backscatter values corresponding to single-incidence angle ensonifications. The construction of the HAC layers can be achieved either by interpolating dense soundings from highly overlapping multibeam echo-sounder (MBES) surveys (interpolated HAC, iHAC) or by producing several backscatter mosaics, each being normalized at a different incidence angle (synthetic HAC, sHAC). The latter approach can be applied to multibeam data with standard overlap, thus minimizing the cost for data acquisition. The sHAC is as efficient as the iHAC produced by actual soundings, providing distinct angular responses for each seafloor type. The HAC data structure increases acoustic class separability between different acoustic features. Moreover, the results of angular response analysis are applied on a fine spatial scale (cell dimensions) offering more detailed acoustic maps of the seafloor. Considering that angular information is expressed through high-dimensional backscatter layers, we further applied three machine learning algorithms (random forest, support vector machine, and artificial neural network) and one pattern recognition method (sum of absolute differences) for supervised classification of the HAC, using a limited amount of ground truth data (one sample per seafloor type). Results from supervised classification were compared with results from an unsupervised method for inter-comparison of the supervised algorithms. It was found that all algorithms (regarding both the iHAC and the sHAC) produced very similar results with good agreement (>0.5 kappa) with the unsupervised classification. Only the artificial neural network required the total amount of ground truth data for producing comparable results with the remaining algorithms.

Seabed Classification Using Multibeam Backscatter in G-Island, North Jakarta

Seabed Classification Using Multibeam Backscatter in G-Island, North Jakarta

Quantifying the discriminatory power of remote sensing technologies for benthic habitat mapping

ABSTRACTWhen mapping benthic habitats using remotely sensed data, the ability to discriminate between pairs of habitats is a key measure of the usefulness of a set of one or more input covariates. In the case where some input data is already available, but a superior map is sought, map-makers would like to know which additional remote sensing data would make the greatest improvement to the quality of their maps. Depending on the purpose of the map, this could be measured by the extent to which a selected pair of habitats is discriminated.This study exploits an existing data-rich study site in order to provide guidance for the use of remote sensing technology in regions where such data do not exist already. LiDAR (light detection and ranging) reflectivity, multibeam backscatter, World View 2 (WV2) bands 1–4, multibeam bathymetry, and depth-derived variables are analysed to determine the extent to which they enable benthic habitats of interest to be discriminated from one another in a statistical sense. Ground truth is employed in the form of towed video.Quantitative results are tabulated for each of the six pairs of four key habitat classes: macroalgae, seagrass, sand, and reef. The technique of Canonical Variate Analysis (CVA) is used to calculate ratios of between-class to within-class variation and cross-validated error rate estimates are calculated for the best combination of N variables, where N varies from 1 to 8. It is found that: Reef and Macroalgae classes cannot be statistically distinguished with the technologies and training methods studied here; WV2 augmented with depth provides good discrimination between the separable classes; multibeam echosounder depth and backscatter data both provide good information for mapping cover types, but in general are not as useful as optical data if it is available. LiDAR reflectivity is a very useful covariate, which has comparable discriminatory power to any one of the first three WV2 bands, with the added potential to penetrate to greater depths than the passive satellite sensors.

Geostatistical modelling of multibeam backscatter for full-coverage seabed sediment maps

Extensive seabed sediment mapping is highly relevant to describe marine ecosystems and to quantify the distribution and extent of benthic habitats. Compared to traditional mapping methods, primarily based on bed sampling, multibeam echo sounding (MBES) is a time-efficient tool to acquire high-resolution bathymetric and backscatter data over large areas. We use a Bayesian method for unsupervised acoustic sediment classification (ASC) of MBES backscatter data of the Cleaver Bank, Netherlands Continental Shelf. On these sparsely distributed backscatter datasets, we tested and evaluated different Kriging algorithms, showing that Ordinary Kriging results in a reliable map. We introduce a new approach to classify interpolated MBES backscatter based on the Bayesian method for producing full-coverage sediment maps. Comparison to a traditional sediment map and in situ measurements shows that this approach resolves lateral heterogeneities (kilometers). When evaluating the high-resolution sediment map obtained from the Bayesian method, based on the actual backscatter, mapping laterally heterogeneous sediments significantly improved (meters). In order to create the optimal sediment map, we aimed to integrate ASC into existing maps, which, however, requires quantified spatial uncertainties of both considered maps. Finally, the low discrimination power of MBES backscatter for coarse sediments is highlighted as a shortcoming of current ASC mapping.

Improving marine habitat mapping using high-resolution acoustic data; a predictive habitat map for the Firth of Lorn, Scotland

Habitat mapping is an important tool for marine spatial planning and is required for most ecosystem-based management approaches. The Firth of Lorn Special Area of Conservation (SAC), west Scotland, was originally designated for its rocky reef habitat but it is also an area of high importance for the Flapper skate (Dipturus intermedius) and Harbour porpoise (Phocoena phocoena). Here we present an improved predictive habitat map for the SAC utilising multibeam backscatter and bathymetry data collected as part of the Ireland, Northern Ireland and Scotland Hydrographic Survey Project.Backscatter, bathymetry and bathymetric derivatives were analysed using Principal Component Analysis (PCA) and acoustic signatures were created from drop-down video habitat location data. A predictive habitat map was created from Maximum Likelihood Classification using the PCA. Dominant habitat types identified included; moderate energy circalittoral rock (CR.MCR), sublittoral mixed sediment (SS.SMx) and sublittoral sand and muddy sand (SS.SSa). Drop down video showed variable accuracy with 0–100% correctly classified habitats due to the small sample size. The initial validation points were added and the model was rerun. In areas with no previous sea truthing points, some predictions changed to SS.SMx at depths > 100 m and SS.SSa in depths < 50 m, suggesting that the model can be improved with a greater depth-range of sea truthing data. Modern acoustic surveys undertaken for other purposes, such as navigational charting, can thus be used to generate broad-scale predictive habitat maps in a cost and time effective manner. Such maps have the potential for a wide range of use by marine stakeholders, in particular, for establishing environmental baselines for long term monitoring of benthic habitats. Given the high costs of surveying, such an approach supports the rationale of “Collect once and use many times”.

Using Multibeam Backscatter Data to Investigate Sediment‐Acoustic Relationships

AbstractSediment properties are known to influence acoustic backscatter intensity. This sediment‐acoustic relationship has been investigated previously through using physical geoacoustic models and empirical methods and found to be complex and nonlinear. Here we employ a robust machine‐learning statistical model (random forest decision tree) to investigate the most likely nonlinear sediment‐backscatter relationships. The analysis uses colocated sediment and acoustic backscatter data (collected from a 300‐kHz multibeam sonar system) for 564 locations in four different areas on the Australian margin. Seven sediment grain size properties (%gravel, %sand, %mud, mean grain size, sorting, skewness, and kurtosis) were used to predict the acoustic backscatter responses at individual incidence angles. The modeling results demonstrate the effectiveness of this multivariate predictive approach for the investigation of sediment‐acoustic relationship. Thus, we find that for incidence angles between 1° and 41°, the sediment variables explain around 70% of variance in the backscatter intensity. Sediment mud content was found to be the most important sediment variable in the model and has a significant negative relationship with backscatter intensity. Mean grain size was the second ranked sediment variable and found to have a positive relationship with backscatter intensity. The results also show that sediment mud content plays a key role in sorting‐backscatter and sand‐backscatter relationships. Using only two sediment properties, mud content and mean grain size, together it was possible to largely explain the sediment‐acoustic relationship. The strongest backscatter return occurred with medium sediment mud content and large mean grain sizes (or muddy coarse sand).

Improved Interpretation of Marine Sedimentary Environments Using Multi-Frequency Multibeam Backscatter Data

Backscatter mosaics based on a multi-frequency multibeam echosounder survey in the continental shelf setting of the North Sea were compared. The uncalibrated backscatter data were recorded with frequencies of 200, 400 and 600 kHz. The results showed that the seafloor appears mostly featureless in acoustic backscatter mosaics derived from 600 kHz data. The same area surveyed with 200 kHz reveals numerous backscatter anomalies with diameters of 10–70 m deviating between −2 dB and +4 dB from the background sediment. Backscatter anomalies were further subdivided based on their frequency-specific texture and were attributed to bioturbation within the sediment and the presence of polychaetes on the seafloor. While low frequencies show the highest overall contrast between different seafloor types, a consideration of all frequencies permits an improved interpretation of subtle seafloor features.

Sensitivity of Texture Parameters to Acoustic Incidence Angle in Multibeam Backscatter

Texture analysis is one of the principal methods by which acoustic backscatter information is analyzed and classified. Recently, its application to the identification of subtle changes in acoustic images, such as the identification of marine life, has begun to increase. To utilize texture analysis for these purposes, the effect of survey geometry on texture parameters must be understood. A dense net of multibeam echo sounder data was recorded with a sixfold overlap to study the impact of the acoustic incidence angle on selected texture parameters derived from a Haralick gray-level co-occurrence matrix. The results show that a correlation of up to 0.29 exists between the beam angle and texture values in sedimentary facies. This correlation depends on the seafloor composition. The correlation is masked when seafloors of different compositions are considered, and it is reduced with decreasing image resolution. The observed effects are relevant when subtle seafloor changes are considered, and they may also be responsible for the comparably poor performance of texture analysis in several habitat mapping studies.

Acoustic investigations of natural seeps at GC600

We examine the acoustic signature of natural seeps in the Green Canyon block 600 of the Gulf of Mexico. The survey site was 2200'1600 m2 at a depth of 1200 m. Near-bottom multibeam backscatter, side-scan sonar mosaic, and chirp sub-bottom profiles were collected using an AUV cruising at 40 m above the seafloor. The water-column profiles collected by the Kongsberg EM2040 at 200 kHz central frequency were utilized to detect and localize seeps. Geological information from the chirp sonar and side scan images will also augment these data to further our understanding of the geologic structure of natural seeps. Identified seeps from the backscatter intensity were visited with a Comanche ROV for a visual inspection. An oily plume was selected for further investigations and vertical upwelling will be monitored with an Acoustic Scintillation Flow Meter (ASFM), for the first time. Concurrent measurements include nearby Acoustic Doppler profilers, a vertical array of conductivity/temperature instruments and two video cameras (VTLC) for identifying bubble/droplet sizes and distribution and will provide invaluable reference data on temporal variability.

Calibrating nadir striped artifacts in a multibeam backscatter image using the equal mean-variance fitting model

Acoustic seafloor classification with multibeam backscatter measurements is an attractive approach for mapping seafloor properties over a large area. However, artifacts in the multibeam backscatter measurements prevent accurate characterization of the seafloor. In particular, the backscatter level is extremely strong and highly variable in the near-nadir region due to the specular echo phenomenon. Consequently, striped artifacts emerge in the backscatter image, which can degrade the classification accuracy. This study focuses on the striped artifacts in multibeam backscatter images. To this end, a calibration algorithm based on equal mean-variance fitting is developed. By fitting the local shape of the angular response curve, the striped artifacts are compressed and moved according to the relations between the mean and variance in the near-nadir and off-nadir region. The algorithm utilized the measured data of near-nadir region and retained the basic shape of the response curve. The experimental results verify the high performance of the proposed method.

Multisource multibeam backscatter data: developing a strategy for the production of benthic habitat maps using semi-automated seafloor classification methods

The establishment of multibeam echosounders (MBES) as a mainstream tool in ocean mapping has facilitated integrative approaches towards nautical charting, benthic habitat mapping, and seafloor geotechnical surveys. The bathymetric and backscatter information generated by MBES enables marine scientists to present highly accurate bathymetric data with a spatial resolution closely matching that of terrestrial mapping, and can generate customized thematic seafloor maps to meet multiple ocean management needs. However, when a variety of MBES systems are used, the creation of objective habitat maps can be hindered by the lack of backscatter calibration, due for example, to system-specific settings, yielding relative rather than absolute values. Here, we describe an approach using object-based image analysis to combine 4 non-overlapping and uncalibrated (backscatter) MBES coverages to form a seamless habitat map on St. Anns Bank (Atlantic Canada), a marine protected area hosting a diversity of benthic habitats. The benthoscape map was produced by analysing each coverage independently with supervised classification (k-nearest neighbor) of image-objects based on a common suite of 7 benthoscapes (determined with 4214 ground-truthing photographs at 61 stations, and characterized with backscatter, bathymetry, and bathymetric position index). Manual re-classification based on uncertainty in membership values to individual classes—especially at the boundaries between coverages—was used to build the final benthoscape map. Given the costs and scarcity of MBES surveys in offshore marine ecosystems—particularly in large ecosystems in need of adequate conservation strategies, such as in Canadian waters—developing approaches to synthesize multiple datasets to meet management needs is warranted.

Integrating dual frequency side-scan sonar data and multibeam backscatter, angular response and bathymetry, for benthic habitat mapping in the Laganas Gulf MPA, Zakinthos Isl., Greece

The preferred procedure nowadays for benthic habitat mapping is combining marine acoustic and ground truthing methods, with the former ones tending to be the swath sonars, such as the Multi Beam Echo Sounders (MBES) and the Side-Scan Sonars (SSS). Both above acoustic systems, in conjunction with an extensive underwater video footage, were employed to map in detail benthic habitats in the marine area of Laganas Gulf in the National Marine Park of Zakynthos Isl., Greece, including key protected habitats such as P.oceanica beds and coralligenous formations. Object oriented seafloor classification was achieved taking advantage of the multi-layer information available, including the two individual frequencies of SSS and the MBES backscatter, angular response, and bathymetry data. The extracted statistical derivatives regarded: (1) textural analysis of the multi-frequency backscatter imagery, (2) angular range analysis of the MBES backscatter, as well as (3) application of various bathymetric indices. Those derivatives were classified individually or fuzzed together, to explore the rate of improvement when choosing one system or another and to investigate their best combinations and practices towards valid seafloor classification. Benthic habitat classification has been comprehended using the NATURA and EUNIS classification schemes to be compatible with the EU regulations.

Mobility of maerl-siliciclastic mixtures: Impact of waves, currents and storm events

Maerl beds are free-living, non-geniculate coralline algae habitats which form biogenic reefs with high micro-scale complexity supporting a diversity and abundance of rare epifauna and epiflora. These habitats are highly mobile in shallow marine environments where substantial maerl beds co-exist with siliciclastic sediment, exemplified by our study site of Galway Bay. Coupled hydrodynamic-wave-sediment transport models have been used to explore the transport patterns of maerl-siliciclastic sediment during calm summer conditions and severe winter storms. The sediment distribution is strongly influenced by storm waves even in water depths greater than 100 m. Maerl is present at the periphery of wave-induced residual current gyres during storm conditions. A combined wave-current Sediment Mobility Index during storm conditions shows correlation with multibeam backscatter and surficial sediment distribution. A combined wave-current Mobilization Frequency Index during storm conditions acts as a physical surrogate for the presence of maerl-siliciclastic mixtures in Galway Bay. Both indices can provide useful integrated oceanographic and sediment information to complement coupled numerical hydrodynamic, sediment transport and erosion-deposition models.