Continuous, High-Resolution Mapping of Coastal Seafloor Sediment Distribution (original) (raw)
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Chemistry and Ecology, 2020
We present a new seafloor sedimentological map of Bagnoli-Coroglio SIN (Sites of National Interest) in the Gulf of Pozzuoli (Napoli), Italy, based on the analysis of the acoustic backscatter, calibrated with grain size distribution of sampled surficial marine deposits. Geophysical and ground-truthing (geological) data were acquired during a series of marine surveys designed for a seafloor characterisation aimed at remediation of the marine environment offshore the dismissed industrial area of Bagnoli. This study describes the acquisition and processing of the multibeam echosounder (Reson SeaBat 7125 high-resolution) backscatter data recorded during geophysical survey and illustrates the approach followed in the construction of a high-resolution seafloor map of the Bagnoli-Coroglio offshore.
ICES Journal of Marine Science, 2013
Maps of surficial sediment distribution and benthic habitats or biotopes provide invaluable information for ocean management and are at the core of many seabed mapping initiatives, including Norway's national offshore mapping programme MAREANO (www.mareano.no). Access to high-quality multibeam echosounder data (bathymetry and backscatter) has been central to many of MAREANO's mapping activities, but in order to maximize the cost-effectiveness of future mapping and ensure timely delivery of scientific information, seabed mappers worldwide may increasingly need to look to existing bathymetry data as a basis for thematic maps. This study examines the potential of compiled single-beam bathymetry data for sediment and biotope mapping. We simulate a mapping scenario where full coverage multibeam data are not available, but where existing bathymetry datasets are supplemented by limited multibeam data to provide the basis for thematic map interpretation and modelling. Encouraging results of sediment interpretation from the compiled bathymetry dataset suggest that production of sediment grain size distribution maps is feasible at a 1:250 000 scale or coarser, depending on the quality of available data. Biotope modelling made use of full-coverage predictor variables based on (i) multibeam data, and (ii) compiled singlebeam data supplemented by limited multibeam data. Using the same response variable (biotope point observations obtained from video data), the performance of the respective models could be assessed. Biotope distribution maps based on the two datasets are visually similar, and performance statistics also indicate there is little difference between the models, providing a comparable level of information for regional management purposes. However, whilst our results suggest that using compiled bathymetry data with limited multibeam is viable as a basis for regional sediment and biotope mapping, it is not a substitute. Backscatter data and the better feature resolution provided by multibeam data remain of great value for these and other purposes.
Geostatistical modelling of multibeam backscatter for full-coverage seabed sediment maps
Hydrobiologia, 2018
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 highresolution 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.
Examining the Links between Multi-Frequency Multibeam Backscatter Data and Sediment Grain Size
Remote Sensing
Acoustic 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) cor...
Estuarine, Coastal and Shelf Science, 2016
Recent technological developments of multibeam echosounder systems (MBES) allow mapping of benthic habitats with unprecedented detail. MBES can now be employed in extremely shallow waters, challenging data acquisition (as these instruments were often designed for deeper waters) and data interpretation (honed on datasets with resolution sometimes orders of magnitude lower). With extremely high-resolution bathymetry and colocated backscatter data, it is now possible to map the spatial distribution of fine scale benthic habitats, even identifying the acoustic signatures of single sponges. In this context, it is necessary to understand which of the commonly used segmentation methods is best suited to account for such level of detail. At the same time, new sampling protocols for precisely georeferenced ground truth data need to be developed to validate the benthic environmental classification. This study focuses on a dataset collected in a shallow (2-10 m deep) tidal channel of the Lagoon of Venice, Italy. Using 0.05-m and 0.2-m raster grids, we compared a range of classifications, both pixel-based and object-based approaches, including manual, Maximum Likelihood Classifier, Jenks Optimization clustering, textural analysis and Object Based Image Analysis. Through a comprehensive and accurately geo-referenced ground truth dataset, we were able to identify five different classes of the substrate composition, including sponges, mixed submerged aquatic vegetation, mixed detritic bottom (fine and coarse) and unconsolidated bare sediment. We computed estimates of accuracy (namely Overall, User
Sedimentary Geology, 2015
Seabed sediment texture can be mapped by geostatistical prediction from limited direct observations such as grab-samples. A geostatistical model can provide local estimates of the probability of each texture class so the most probable sediment class can be identified at any unsampled location, and the uncertainty of this prediction can be quantified. In this paper we show, in a case study off the northeast coast of England, how swath bathymetry and backscatter can be incorporated into a geostatistical linear mixed model (LMM) as fixed effects (covariates). Parameters of the LMM were estimated by maximum likelihood which allowed us to show that both covariates provided useful information. In a cross-validation, each observation was predicted from the rest using the LMMs with (i) no covariates, or (ii) bathymetry and backscatter as covariates. The proportion of cases in which the most probable class according to the prediction corresponded to the observed class was increased (from 58% to 65% of cases) by including the covariates which also increased the information content of the predictions, measured by the entropy of the class probabilities. A qualitative assessment of the geostatistical results shows that the model correctly predicts, for example, the occurrence of coarser sediment over discrete glacial sediment landforms, and muddier sediment in relatively quiescent,
waters, 2020
In the Mediterranean Sea, crustose coralline algae form endemic algal reefs known as Coralligenous (C) build-ups. The high degree of complexity that C can reach through time creates notable environmental heterogeneity making C a major hotspot of biodiversity for the Mediterranean basin. C build-up can variably modify the submarine environment by a ecting the evolution of submerged landforms, although its role is still far from being systematically defined. Our work proposes a new, ad-hoc semi-automated, GIS-based methodology to map the distribution of C build-ups in shallow coastal waters using high-resolution bathymetric data, collected on a sector of the southern Apulian continental shelf (Southern Adriatic Sea, Italy). Our results quantitatively define the 3D distribution of C in terms of area and volume, estimating more than 103,000 build-ups, covering an area of roughly 305,200 m2, for a total volume of 315,700 m3. Our work firstly combines acoustic survey techniques and geomorphometric analysis to develop innovative approaches for eco-geomorphological studies. The obtained results can contribute to a better definition of the ocean carbon budget, and to the monitoring of local anthropogenic impacts (e.g., bottom trawling damage) and global changes, like ocean warming and acidification. These can a ect the structural complexity and total volume of carbonate deposits characterizing the Mediterranean benthic environment.
Multibeam echo-sounders (MBES) are primarily used to map seafloor bathymetry. In addition, MBESs can also measure the acoustic backscatter intensity of the seafloor. Backscatter intensity can be influenced by a variety of seafloor properties, including the acoustic impedance (relative to the water column), surface roughness and volume heterogeneity. Hence, backscatter intensity measurements have been used to infer seafloor properties, such as mean grain size, percentage of mud, presence of seagrass, etc. Although there is a well established relationship between sediment and acoustic properties of the seafloor, predicting seafloor properties directly from backscatter intensity recorded by sonar systems, such as MBES, is not a trivial problem. One of the problems is the lack of an adequate theoretical model of high-frequency backscatter. In addition, the prediction of seafloor properties usually requires a calibrated sonar system, which is not always possible. An alternative approach ...
Mapping mud content and median grain-size of North Sea sediments – A geostatistical approach
Marine Geology, 2018
Sediment grain size is well known for its influence on biogeophysical processes and hence, grain size parameter maps, important elements in an integrated ecological modelling strategy. In this study, a large database was compiled from legacy data on grain size parameters and distributions in North Sea surface sediments. The database was analysed by means of non-linear regression to enable a consistent quantification of various grain size parameters. In a second step, multivariate geostatistics (kriging) were employed to predict the spatial distribution of percentage mud content and median grain size in the North Sea with a resolution of 1 × 1 nautical miles. The results show that incorporation of secondary information in the interpolation led to a physically more realistic representation of large-scale patterns compared to deterministic approaches. An evaluation of map confidence, however, suggests only minor differences in the quality obtained by different kriging techniques. It appears that the data density and distribution are not an issue when it comes to performance. Instead, insufficient metadata constrain the assessment and harmonisation of data sets and introduce uncertainty into the predictions.
Towards a statistically valid method of textural sea floor characterization of benthic habitats
Marine Geology, 2006
Multibeam bathymetric sonar technology and benthic habitat research require the systematic characterization of the seafloor, necessitating reliable and accurate sea floor descriptors in combination with a robust means to statistically assess descriptor associations. Historically, geoscientific sea floor characterisation involves identifying the spatial extent and relationship of geological units, broadly following litho-or chronostratigraphic criteria, but these conventions may not be meaningful biologically because they incorporate temporal elements that stem from a geochronological qualifier. Textural properties of geological facies are typically given in terms of distribution-dependent statistics, which have been shown to be inappropriate with multimodal marine sediments, such as on glaciated shelves. As habitat classification is aimed at boundary definition, the boundaries between groups in such cases could be arbitrary, or based on very subtle differences, or noise (e.g., sampling bias). This study uses an independent statistical approach pioneered by Calinski and Harabasz (C-H) which offers significant advantages in determining the appropriate number of groups that might exist in any sample population. Used in conjunction with a multivariate extension to informationentropy, grain size populations can be clustered into statistically validated groups. This study utilizes a 30-yr legacy of 4-class grain size data collected from the Scotian Shelf, Canadian Atlantic continental margin, we show that a traditional stratigraphic approach does not provide clear discrimination between basic textural types, and hence, basic benthic habitats. Considerable improvements in textural zonation are obtained using a combination of information entropy-clustering and C-H technique. Two high resolution, 32-class particle-size data sets yield a solution where no obvious textural groups exist, contrary to published field-based studies. Comparison of sediment grab samples to bottom photographs from other shelf sites show that photos capture (sample) a wider range of textural variability, particularly the coarsest-gravel component that is sometimes absent from grabs, and therefore, classification from photos creates more groups. This study emphasizes that data resolution and sea-floor sampling strategies should be intimately linked, and to fully unravel high-resolution textural data might require in excess of a four order of magnitude increase in the number of bottom sediment samples. Therefore, data should be collected at the highest practical resolution but be reduced to a resolution meaningful for statistical analysis, in accordance with the total sample population. D