Examining the Links between Multi-Frequency Multibeam Backscatter Data and Sediment Grain Size

Publication history: Accepted - 13 April 2021Acoustic methods are routinely used to provide broad scale information on the geographical distribution of benthic marine habitats and sedimentary environments. Although single-frequency multibeam echosounder surveys have dominated seabed characterisation for decades, multifrequency approaches are now gaining favour in order to capture different frequency responses from the same seabed type. The aim of this study is to develop a robust modelling framework for testing the potential application and value of multifrequency (30, 95, and 300 kHz) multibeam backscatter responses to characterize sediments’ grain size in an area with strong geomorphological gradients and benthic ecological variability. We fit a generalized linear model on a multibeam backscatter and its derivatives to examine the explanatory power of single-frequency and multifrequency models with respect to the mean sediment grain size obtained from the grab samples. A strong and statistically significant (p < 0.05) correlation between the mean backscatter and the absolute values of the mean sediment grain size for the data was noted. The root mean squared error (RMSE) values identified the 30 kHz model as the best performing model responsible for explaining the most variation (84.3%) of the mean grain size at a statistically significant output (p < 0.05) with an adjusted r2 = 0.82. Overall, the single low-frequency sources showed a marginal gain on the multifrequency model, with the 30 kHz model driving the significance of this multifrequency model, and the inclusion of the higher frequencies diminished the level of agreement. We recommend further detailed and sufficient ground-truth data to better predict sediment properties and to discriminate benthic habitats to enhance the reliability of multifrequency backscatter data for the monitoring and management of marine protected areas.This research was funded by the Marine Institute under the Marine Research Programme by the Irish Government Cruise CE19007 Backscatter and Biodiversity of Shelf Sea Habitats (BaBioSSH) survey. Staffing was supported through the Marine Protected Area Monitoring and Management (MarPAMM) project, which is supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPM) with matching funding from the Government of Ireland, the Northern Ireland Executive, and the Scottish Government, as well as the PhD studentship through a Vice Chancellor Research Scholarship of Ulster University (U.K.)

Analysis of multibeam sonar data for benthic habitat characterization of the Port of Tauranga, New Zealand.

Tauranga Harbour is a mesotidal lagoon located within the Bay of Plenty, New Zealand, and is subject to an ongoing maintenance dredging program to remove mud deposits coming from various sources in the catchment. At the southern end of the commercial port, the Tauranga Bridge Marina was built adjacent to the bridge causeway, with 500 floating concrete berths, enclosed by concrete floating breakwaters. It is proposed to convert these floating breakwaters into solid ones to stop waves entering the marina. This is expected to influence tidal circulation around the Tauranga bridge causeway, and potentially affect sedimentation and marine habitats. The region is an important source of "kai moana" (seafood) for local iwi, and is a source of juvenile shellfish for the large beds located on the flood tidal delta and surrounding channels. This study investigates the impact of the successive harbour constructions on the local sedimentology. The overall goal of the mapping part of this project is to identify and locate the different seabed facies and features within the study site, which may be affected by the sediment transport potentially resulting from the past and future harbour developments. To investigate the impacts of the harbour modifications, a habitat-mapping survey using acoustic mapping techniques was undertaken in July and August 2011. The hydrographic survey was simultaneously performed using a multibeam echosounder (Kongsberg-Simrad EM3000) and a Starfish 452F sidescan sonar. The backscatter/imagery data from both systems was then used for habitat mapping, using a combination of Angular Response Analysis and image-based segmentation. An underwater camera survey and seabed sampling were also performed to ground-truth the morphologies identified from the acoustic backscatter analysis. The most recent habitat map was then compared to the previous studies to identify changes in response to the different modifications of the estuary

Benthic habitat mapping in coastal waters of south–east Australia

The Victorian Marine Mapping Project will improve knowledge on the location, spatial distribution, condition and extent of marine habitats and associated biodiversity in Victorian State waters. This information will guide informed decision making, enable priority setting, and assist in targeted natural resource management planning. This project entails benthic habitat mapping over 500 square kilometers of Victorian State waters using multibeam sonar, towed video and image classification techniques. Information collected includes seafloor topography, seafloor softness and hardness (reflectivity), and information on geology and benthic flora and fauna assemblages collectively comprising habitat. Computerized semi-automated classification techniques are also being developed to provide a cost effective approach to rapid mapping and assessment of coastal habitats.Habitat mapping is important for understanding and communicating the distribution of natural values within the marine environment. The coastal fringe of Victoria encompasses a rich and diverse ecosystem representative of coastal waters of South-east Australia. To date, extensive knowledge of these systems is limited due to the lack of available data. Knowledge of the distribution and extent of habitat is required to target management activities most effectively, and provide the basis to monitor and report on their status in the future.<br /

Assessment of multibeam backscatter texture analysis for seafloor sediment classification

Recently, there have been many debates to analyse backscatter data from multibeam echosounder system (MBES) for seafloor classifications. Among them, two common methods have been used lately for seafloor classification; (1) signal-based classification method which using Angular Range Analysis (ARA) and Image-based texture classification method which based on derived Grey Level Co-occurrence Matrices (GLCMs). Although ARA method could predict sediment types, its low spatial resolution limits its use with high spatial resolution dataset. Texture layers from GLCM on the other hand does not predict sediment types, but its high spatial resolution can be useful for image analysis. The objectives of this study are; (1) to investigate the correlation between MBES derived backscatter mosaic textures with seafloor sediment type derived from ARA method, and (2) to identify which GLCM texture layers have high similarities with sediment classification map derived from signal-based classification method. The study area was located at Tawau, covers an area of 4.7km2, situated off the channel in the Celebes Sea between Nunukan Island and Sebatik Island, East Malaysia. First, GLCM layers were derived from backscatter mosaic while sediment types (i.e. sediment map with classes) was also constructed using ARA method. Secondly, Principal Component Analysis (PCA) was used determine which GLCM layers contribute most to the variance (i.e. important layers). Finally, K-Means clustering algorithm was applied to the important GLCM layers and the results were compared with classes from ARA. From the results, PCA has identified that GLCM layers of Correlation, Entropy, Contrast and Mean contributed to the 98.77% of total variance. Among these layers, GLCM Mean showed a good agreement with sediment classes from ARA sediment map. This study has demonstrated different texture layers have different characterisation factors for sediment classification and proper analysis is needed before using these layers with any classification technique

Alluvial Substrate Mapping by Automated Texture Segmentation of Recreational-Grade Side Scan Sonar Imagery

Side scan sonar in low-cost ‘fishfinder’ systems has become popular in aquatic ecology and sedimentology for imaging submerged riverbed sediment at coverages and resolutions sufficient to relate bed texture to grain-size. Traditional methods to map bed texture (i.e. physical samples) are relatively high-cost and low spatial coverage compared to sonar, which can continuously image several kilometers of channel in a few hours. Towards a goal of automating the classification of bed habitat features, we investigate relationships between substrates and statistical descriptors of bed textures in side scan sonar echograms of alluvial deposits. We develop a method for automated segmentation of bed textures into between two to five grain-size classes. Second-order texture statistics are used in conjunction with a Gaussian Mixture Model to classify the heterogeneous bed into small homogeneous patches of sand, gravel, and boulders with an average accuracy of 80%, 49%, and 61%, respectively. Reach-averaged proportions of these sediment types were within 3% compared to similar maps derived from multibeam sonar

Characterising the ocean frontier : a review of marine geomorphometry

Geomorphometry, the science that quantitatively describes terrains, has traditionally focused on the investigation of terrestrial landscapes. However, the dramatic increase in the availability of digital bathymetric data and the increasing ease by which geomorphometry can be investigated using Geographic Information Systems (GIS) has prompted interest in employing geomorphometric techniques to investigate the marine environment. Over the last decade, a suite of geomorphometric techniques have been applied (e.g. terrain attributes, feature extraction, automated classification) to investigate the characterisation of seabed terrain from the coastal zone to the deep sea. Geomorphometric techniques are, however, not as varied, nor as extensively applied, in marine as they are in terrestrial environments. This is at least partly due to difficulties associated with capturing, classifying, and validating terrain characteristics underwater. There is nevertheless much common ground between terrestrial and marine geomorphology applications and it is important that, in developing the science and application of marine geomorphometry, we build on the lessons learned from terrestrial studies. We note, however, that not all terrestrial solutions can be adopted by marine geomorphometric studies since the dynamic, four- dimensional nature of the marine environment causes its own issues, boosting the need for a dedicated scientific effort in marine geomorphometry. This contribution offers the first comprehensive review of marine geomorphometry to date. It addresses all the five main steps of geomorphometry, from data collection to the application of terrain attributes and features. We focus on how these steps are relevant to marine geomorphometry and also highlight differences from terrestrial geomorphometry. We conclude with recommendations and reflections on the future of marine geomorphometry.peer-reviewe

Quantifying Riverbed Sediment Using Recreational-Grade Side Scan Sonar

The size and organization of bed material, bed texture, is a fundamental attribute of channels and is one component of the physical habitat of aquatic ecosystems. Multiple discipline-specific definitions of texture exist and there is not a universally accepted metric(s) to quantify the spectrum of possible bed textures found in aquatic environments. Moreover, metrics to describe texture are strictly statistical. Recreational-grade side scan sonar systems now offer the possibility of imaging submerged riverbed sediment at resolutions potentially sufficient to identify subtle changes in bed texture with minimal cost,expertise in sonar, or logistical effort. However, inferring riverbed sediment from side scan sonar data is limited because recreational-grade systems were not designed for this purpose and methods to interpret the data have relied on manual and semi-automated routines. Visual interpretation of side scan sonar data is not practically applied to large volumes of data because it is labor intensive and lacks reproducibility. This thesis addresses current limitations associated with visual interpretation with two objectives: 1) objectively quantify side scan sonar imagery texture, and 2) develop an automated texture segmentation algorithm for broad-scale substrate characterization. To address objective 1), I used a time series of imagery collected along a 1.6 km reach of the Colorado River in Marble Canyon, AZ. A statistically based texture analysis was performed on georeferenced side scan sonar imagery to identify objective metrics that could be used to discriminate different sediment types. A Grey Level Co-occurrence Matrix based texture analysis was found to successfully discriminate the textures associated with different sediment types. Texture varies significantly at the scale of ≈ 9 m2 on side scan sonar imagery on a regular 25 cm grid. A minimum of three and maximum of five distinct textures could be observed directly from side scan sonar imagery. To address objective 2), linear least squares and a Gaussian mixture modeling approach were developed and tested. Both sediment classification methods were found to successfully classify heterogeneous riverbeds into homogeneous patches of sand, gravel, and boulders. Gaussian mixture models outperformed the least squares models because they classified gravel with the highest accuracies.Additionally, substrate maps derived from a Gaussian modeling approach were found to be able to better estimate reach averaged proportions of different sediments types when they were compared to similar maps derived from multibeam sonar