Limitations of Boulder Detection in Shallow Water Habitats Using High-Resolution Sidescan Sonar Images

Stones and boulders in shallow waters (0–10 m water depth) form complex geo-habitats, serving as a hardground for many benthic species, and are important contributors to coastal biodiversity and high benthic production. This study focuses on limitations in stone and boulder detection using high-resolution sidescan sonar images in shallow water environments of the southwestern Baltic Sea. Observations were carried out using sidescan sonars operating with frequencies from 450 kHz up to 1 MHz to identify individual stones and boulders within different levels of resolution. In addition, sidescan sonar images were generated using varying survey directions for an assessment of range effects. The comparison of images of different resolutions reveals considerable discrepancies in the numbers of detectable stones and boulders, and in their distribution patterns. Results on the detection of individual stones and boulders at approximately 0.04 m/pixel resolution were compared to common discretizations: it was shown that image resolutions of 0.2 m/pixel may underestimate available hard-ground settlement space by up to 42%. If methodological constraints are known and considered, detailed information about individual stones and boulders, and potential settlement space for marine organisms, can be derived

Hydroacoustic Mapping of Geogenic Hard Substrates: Challenges and Review of German Approaches

Subtidal hard substrate habitats are unique habitats in the marine environment. They provide crucial ecosystem services that are socially relevant, such as water clearance or as nursery space for fishes. With increasing marine usage and changing environmental conditions, pressure on reefs is increasing. All relevant directives and conventions around Europe include sublittoral hard substrate habitats in any manner. However, detailed specifications and specific advices about acquisition or delineation of these habitats are internationally rare although the demand for single object detection for e.g., ensuring safe navigation or to understand ecosystem functioning is increasing. To figure out the needs for area wide hard substrate mapping supported by automatic detection routines this paper reviews existing delineation rules and definitions relevant for hard substrate mapping. We focus on progress reached in German approval process resulting in first hydroacoustic mapping advices. In detail, we summarize present knowledge of hard substrate occurrence in the German North Sea and Baltic Sea, describes the development of hard substrate investigations and state of the art mapping techniques as well as automated analysis routines

Quantitative Comparison of Benthic Habitat Maps Derived From Multibeam Echosounder Backscatter Data

In the last decade, following the growing concern for the conservation of marine ecosystems, a wide range of approaches has been developed to achieve the identification, classification and mapping of seabed types and of benthic habitats. These approaches, commonly grouped under the denominations of Benthic Habitat Mapping or Acoustic Seabed Classification, exploit the latest scientific and engineering advancements for the exploration of the bottom of the ocean, particularly in underwater acoustics. Among all acoustic seabed-mapping systems available for this purpose, a growing interest has recently developed for Multibeam Echosounders (MBES). This interest is mainly the result of the multiplicity of these systems’ outputs (that is, bathymetry, backscatter mosaic, angular response and water-column data), which allows for multiple approaches to seabed or habitat classification and mapping. While this diversity of mapping approaches and this multiplicity of MBES data products contribute to an increasing quality of the charting of the marine environment, they also unfortunately delay the future standardization of mapping methods, which is required for their effective integration in marine environment management strategies. As a preliminary step towards such standardization, there is a need for generalized efforts of comparison of systems, data products, and mapping approaches, in order to assess the most effective ones given mapping objectives and environment conditions. The main goal of this thesis is to contribute to this effort through the development and implementation of tools and methods for the comparison of categorical seabed or habitat maps, with a specific focus on maps obtained from up-to-date methodologies of classification of MBES backscatter data. This goal is attained through the achievement of specific objectives treated sequentially. First, the need for comparison is justified through a review of the diversity characterizing the fields of Benthic Habitat Mapping and Acoustic Seabed Classification, and of their use of MBES data products. Then, a case study is presented that compare the data products from a Kongsberg EM3000 MBES to the output map of an Acoustic Ground Discrimination Software based on data from a Single-beam Echosounder and to a Sidescan Sonar mosaic, in order to illustrate how map comparison measures could contribute to the comparison of these systems. Next, a number of measures for map-to-map comparison, inspired from the literature in land remote sensing, are presented, along with methodologies for their implementation in comparison of maps described with different legends. The benefit of these measures and methodologies is demonstrated through their application to maps obtained from the acoustic datasets presented previously. Finally, a more typical implementation of these measures is presented as a case study in which the development of two up-to-date classification methodologies of MBES backscatter data is complemented by the quantitative comparison of their output maps. In the process of developing and illustrating the use of methods for the assessment of map-to-map similarity, this thesis also presents methodologies for the processing and classification of backscatter data from MBES. In particular, the potential of the combined use of the spatial and angular information of these data for seabed classification is explored through the development of an original segmentation methodology that sequentially divides and aggregates segments defined from a MBES backscatter mosaic on the basis of their angular response content

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

Habitat mapping and identifying suitable habitat of Redfish Rocks Pilot Marine Reserve, Port Orford, Oregon

Establishment of marine protected areas (MPAs) has been documented to effectively manage marine resource's diversity and enhance fisheries productivity. However, there must be a critical consideration of how these sites are selected and the actual description of the site itself. Its effectiveness is greatly dependent on understanding these habitats and the species that thrive in them. In 2008, the State of Oregon embarked on an effort to create a network of marine reserves within its territorial sea. Together with the active participation of the public sector in the selection process, it has to identify two (2) pilot sites and four (4) other sites that need further evaluation. During the selection process, thematic surficial geologic habitat (SGH) maps played a critical role in identifying potential sites. SGH was sufficient to identify specific sites, however a clearer and a habitat map with higher resolution is necessary in effectively managing these pilot marine reserves. Development of a more detailed habitat map will guide local and state managers in initiating specific management interventions to unique marine reserve sites such as Redfish Rock Pilot Marine Reserve. This aim of this study is to develop a detailed habitat map of the Redfish Rock Pilot Marine Reserve to supersede the initial SGH map, and utilize it to predict species occurrence within each habitat type. The use of acoustic information collected from multibeam echo sounder will be used to produce a high resolution habitat map of its marine environment. The backscatter data along with co-registered bathymetric information can be utilized to describe marine topography and define habitat based on its surficial geologic characteristic. Information derived from the bathymetry data utilized Benthic Terrain Modeler (BTM) as a guide in identifying seafloor features and classified zones like high relief and flat zones as well as derivative layers such as hillshade layer. Further delineation of habitat boundaries were made using the backscatter mosaic and angular response analysis (ARA) to classify layers created from the Interactive Visualization System (IVS3D) Fledermaus (FM) Geocoder. Manual digitizing of habitat polygon with automated classified layer as a guide was conducted using ArcGIS. Substrate classifications were verified from the remotely operated vehicle (ROV) videos collected by Oregon's Department of Fish and Wildlife (ODFW). Species occurrences were predicted using the depth, latitude and substrate type and species information queried from the National Marine Fisheries Service (NMFS) Habitat Use Database (HUD). A total of 89 species mostly ground fish were predicted to be present inside the marine reserve. With the habitat map created successfully from high resolution multibeam surveys, managers now have a more detailed picture of the seafloor. This is necessary to design specific management strategies such as development of biophysical monitoring protocol, deployment of marker buoy, conduct of specific species-habitat relationship research. This study was done specifically on the Redfish Rocks Marine Reserve primarily due to the fact that this site already has available data pertinent to the creation of this habitat map; however, this approach could also be applied and replicated at other identified MPA sites including other areas of the Redfish Rocks Pilot Marine Reserve, Otter Rocks Pilot Marine Reserve and the four other sites that are being considered for the creation of MPA networks

Guidelines for the study of the epibenthos of subtidal environments

These Guidelines for the Study of the Epibenthos of Subtidal Environments document a range of sampling gears and procedures for epibenthos studies that meet a variety of needs. The importance of adopting consistent sampling and analytical practices is highlighted. Emphasis is placed on ship‐based techniques for surveys of coastal and offshore shelf environments, but diver‐assisted surveys are also considered

Using remote sensing, in situ observations, and geographic information systems to map benthic habitats at Heceta Bank, Oregon

Dramatic declines in many species of demersal fishes off the West Coast have resulted in the designation of nine commercially important species as being overfished. While the causes of those declines are not clearly understood, the fact remains that a paucity of life history and abundance data exists for many demersal species, also known as groundfish. Due to this uncertainty, only 21 of the 82 species of groundfish managed under the Groundfish Fishery Management Plan of the Pacific Fishery Management Council (PFMC) have been fully assessed. One challenge in designing a systematic survey of groundfish resources is that many species associate with heterogeneous substrate of varying relief. In many areas, the rugosity of the substrata precludes sampling by conventional techniques (e.g. bottom trawl gear). This has stimulated research that characterizes fish-habitat associations for use in design of new survey methodology. Using a combination of remote sensing, in situ observations, and spatial analytical techniques, four benthic habitat classes were mapped for a large rocky bank off the central Oregon coast known as Heceta Bank. Observational data from human-occupied submersible and remotely operated vehicle dives in the late 1980s, 2000 and 2001 were used to establish habitat classes with specific substrate characteristics that have been statistically shown to correlate with demersal fish distributions. The observational habitat data was then extrapolated over the extent of a multibeam sonar survey conducted in 1998 using quantitative parameters derived from high-resolution bathymetric and backscatter imagery of the seafloor. The resultant map predicts the locations of four habitat classes: Ridge-Gully, High-Relief Rock (boulders, cobbles), Unconsolidated Sediment 1 (muds), and Unconsolidated Sediment 2 (sands). The main utility of the habitat map developed as part of the current study is that it provides a context for analyses of a variety of spatial data. For instance, habitat data provides one additional spatial component besides depth and latitude that can be used to stratify catch per unit effort data from surveys and commercial logbooks. Also, essential fish habitat for many demersal species can now be identified in more detail. Finally, habitat data like those presented here can aid in the design of marine reserves and protected areas by providing a context for spatial analyses of data of ecological importance

Seabed biotope characterisation based on acoustic sensing

The background to this thesis is Australia’s Oceans Policy, which aims to develop an integrated and ecosystem-based approach to planning and management. An important part of this approach is the identification of natural regions in regional marine planning, for example by establishing marine protected areas for biodiversity conservation. These natural regions will need to be identified on a range of scales for different planning and management actions. The scale of the investigation reported in this thesis is applicable to spatial management at 1 km to 10 km scale and monitoring impacts at the 10s of m to 1 km biotope scale. Seabed biotopes represent a combination of seabed physical attributes and related organisms. To map seabed biotopes in deep water, remote sensing using a combination of acoustic, optical and physical sensors is investigated. The hypothesis tested in this thesis is that acoustic bathymetry and backscatter data from a Simrad EM1002 multi-beam sonar (MBS) can be used to infer (act as a surrogate of) seabed biotopes. To establish a link between the acoustic data and seabed biotopes the acoustic metrics are compared to the physical attributes of the seabed in terms of its substrate and geomorphology at the 10s m to 1 km scale using optical and physical sensors. At this scale the relationship between the dominant faunal functional groups and both the physical attributes of the seabed and the acoustic data is also tested. These tests use data collected from 14 regions and 2 biomes to the south of Australia during a voyage in 2000. Based on 62 reference sites of acoustic, video and physical samples, a significant relationship between ecological seabed terrain types and acoustic backscatter and bathymetry was observed.These ecological terrain types of soft-smooth, soft-rough, hard-smooth and hard-rough were chosen as they were the most relevant to the biota in their ability to attach on or burrow into the seabed. A seabed scattering model supported this empirical relationship and the overall shape of backscatter to incidence angle relationship for soft and hard seabed types. The correlation between acoustic data (backscatter mean and standard deviation) and the visual and physical samples was most consistent between soft-smooth and hard-rough terrain types for a large range of incidence angles (16o to 70o). Using phenomenological backscatter features segmented into 10 common incidence angle bins from -70o to 70o the length resolution of the data decreased to 0.55 times depth. The decreased resolution was offset by improved near normal incidence (0o to 30o) seabed type discrimination with cross validation error reducing from 32% to 4%. A significant relationship was also established between the acoustic data and the dominant functional groups of fauna. Faunal functional groups were based on the ecological function, feeding mode and substrate preference, with 8 out of the 10 groups predicted with 70% correctness by the four acoustically derived ecological terrain types. Restricting the terrain classification to simple soft and hard using the acoustic backscatter data improved the prediction of three faunal functional groups to greater than 80%. Combining the acoustic bathymetry and backscatter data an example region, Everard Canyon, was interpreted at a range of spatial scales and the ability to predict the preferred habitat of a stalked crinoid demonstrated.Seabed terrain of soft and hard was predicted from the acoustic backscatter data referenced to a common seabed incidence angle of 40o. This method of analysis was selected due to its combined properties of high spatial resolution, consistent between terrain discrimination at the widest range of incidence angles and consistent data quality checking at varying ranges. Based in part on the research reported in this thesis a mid-depth Simrad EM300 multibeam sonar was purchased for use in Australian waters. A sampling strategy is outlined to map all offshore waters with priority within the 100 m to 1500 m depths

Machine learning methods for discriminating natural targets in seabed imagery

The research in this thesis concerns feature-based machine learning processes and methods for discriminating qualitative natural targets in seabed imagery. The applications considered, typically involve time-consuming manual processing stages in an industrial setting. An aim of the research is to facilitate a means of assisting human analysts by expediting the tedious interpretative tasks, using machine methods. Some novel approaches are devised and investigated for solving the application problems. These investigations are compartmentalised in four coherent case studies linked by common underlying technical themes and methods. The first study addresses pockmark discrimination in a digital bathymetry model. Manual identification and mapping of even a relatively small number of these landform objects is an expensive process. A novel, supervised machine learning approach to automating the task is presented. The process maps the boundaries of ≈ 2000 pockmarks in seconds - a task that would take days for a human analyst to complete. The second case study investigates different feature creation methods for automatically discriminating sidescan sonar image textures characteristic of Sabellaria spinulosa colonisation. Results from a comparison of several textural feature creation methods on sonar waterfall imagery show that Gabor filter banks yield some of the best results. A further empirical investigation into the filter bank features created on sonar mosaic imagery leads to the identification of a useful configuration and filter parameter ranges for discriminating the target textures in the imagery. Feature saliency estimation is a vital stage in the machine process. Case study three concerns distance measures for the evaluation and ranking of features on sonar imagery. Two novel consensus methods for creating a more robust ranking are proposed. Experimental results show that the consensus methods can improve robustness over a range of feature parameterisations and various seabed texture classification tasks. The final case study is more qualitative in nature and brings together a number of ideas, applied to the classification of target regions in real-world sonar mosaic imagery. A number of technical challenges arose and these were surmounted by devising a novel, hybrid unsupervised method. This fully automated machine approach was compared with a supervised approach in an application to the problem of image-based sediment type discrimination. The hybrid unsupervised method produces a plausible class map in a few minutes of processing time. It is concluded that the versatile, novel process should be generalisable to the discrimination of other subjective natural targets in real-world seabed imagery, such as Sabellaria textures and pockmarks (with appropriate features and feature tuning.) Further, the full automation of pockmark and Sabellaria discrimination is feasible within this framework