Annex II

Seabed Mapping: Multibeam Bathymetry,

Backscatter and Video Imaging of the Seabed in the South East Coast Scallop Grounds

Gerry Sutton1 & Eimear O’Keeffe2

1= Coastal & Marine Resources Centre UCC

2= Martin Ryan Institute, National University of Ireland, Galway

Final Report of Project 01.SM.T1.07 Funded by the Irish Government and part-financed by the European Union under the National

Development Plan 2000-2006 through the Supporting Measures in the Fisheries Sector.

Video image of sand and gravel seabeds off the south east coast

GRAVELS

SANDS

UNIVERSITY COLLEGE CORK Coláiste na hOllscoile Corcaigh

Introduction

Sediment type is an important factor in the settlement, distribution and abundance of

scallops. Existing knowledge of scallop ecology indicates that population distributions

are patchy (Robert and Butler, 1998), and that high scallop abundance correlates with

coarser sediments such as sands and gravels (Bousfield, 1960; Robert, 1997;

Kostylev, 2005). Multibeam eshosounder (MBES) sonar systems have become the

tools of choice in the mapping of seabed topography, morphology and sediment

characteristics (Mitchell & Summers, 1989; Mitchell & Hughes-Clarke, 1994,

Courtney & Shaw 2000). When used in conjunction with optical imagery (still and

video recordings) and sediment samples the composite view that is generated

facilitates very detailed spatial characterisation of seabed substrates and habitats. In

order to further study the effects of ground type on the population dynamics of

scallop, an acoustic survey of the area exploited by the scallop fishery was

commissioned in 2001 (Figure. 1).

Figure. 1. Map of fishing grounds off the southeast coast with acoustic survey area overlain.

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The objectives of the survey were as follows:

(1) Map the distribution of different sedimentary facies (ground types) in areas

that are fished for scallop to high resolution

(2) To correlate scallop catch data from fishing vessels with the backscatter

values for the area dredged

(3) Refine the extents of areas of high abundance within known scallop

grounds, and provide recommendations for additional areas of high scallop

potential outside existing beds through the application of

backscatter/abundance criteria over extended/alternative survey areas.

Methods

In order to map the seabed, MBES sonar acoustic data were collected by the project

team using the RV Celtic Voyager of the National Marine Institute equipped with a

Simrad EM 1002. Surveys were designed and data acquisition controlled using the

Simrad Merlin/Neptune interface. Coherent overlapping (20-30%) swathes of sonar

coverage were generated within discrete survey blocks. The size location and priority

of survey blocks were set in order to coincide with areas where scallop were likely to

be found at reasonable (commercially viable) densities. The boundaries of these

higher density areas were determined from: a) areas delineated by scallop fishermen

with reference bounding coordinates for fishing tracks recorded by means of chart

plotter software (Figure. 2.), and b) the gridded and countoured results of the initial

broadscale stock assessment surveys (Figure. 3.).

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Figure. 2. Potential survey areas as delimited by corner coordinates donated by scallop fishermen.

Figure. 3. Estimation of the density of scallop in the Inshore and B & H fishing grounds calculated from the 2001 scallop stock survey. The results of this stock assessment highlighted areas with a high density of scallop, thus, prioritising the regions that needed to be surveyed acoustically.

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All MBES data were initially managed and post-processed using CARIS™ HIPS

(Hydrographic Information Processing System, CARIS, 2003). This software contains

a suite of modules and tools designed to facilitate complex quality control (QC) and

data cleaning procedures, and also facilitate reduction of all sounding data to a

common vertical datum (e.g. Mean Sea Level) through application of tidal

corrections. HIPS was also used to produce the other main data products. Relative

backscatter (five and ten metres grids), and sun illuminated bathymetry (three and five

metre grids) were generated in GeoTiff format. Bathymetric data in the form of

individual numerical soundings were also output in ASCII “x,y,z” text file format at

various grid intervals for subsequent use as a fundamental data layer in the GIS and to

support the development of the hydrodynamic numerical model outlined by Marcon

(2006). ASCII text files were also generated for backscatter export.

Simultaneous tidal heights were recorded at Kilmore Quay and Helvick by means of a

portable Valeport 740 water level recorder. Tidal data were logged at five minute

intervals, quality controlled by reference to hand measurements and reduced to Mean

Sea Level Datum with reference to local Ordnance Survey bench marks. This tidal

data was correlated with predicted tide levels and the resulting composite tide files

used to correct bathymetric soundings on the basis of proximity to source data.

Continuous georeferenced underwater video imagery was collected along transects of

approximately 1km within 12 selected sub-areas of approx 1km2. A Simrad 1 0E13-

66MK II Underwater Video Camera was mounted in an aluminium sledge (Figure. 4)

and towed behind the survey vessel. The video signal was digitised, logged and

integrated with GPS positions using a proprietary system (BlueGlen Technologies,

2006). GPS positions were subsequently processed to remove layback error using a

standard layback calculation based on cable out, water depth, and towing position

offset. The camera was positioned obliquely with a downward forward view at a

height of approximately 70cm above the seabed giving a field of view of

approximately 1m.

Samples of surficial seabed sediments (typical sample size ~05.-1kg) were collected

during the mapping surveys using a Shipek grab in order to groundtruth acoustic data.

These samples were initially given summary field descriptions on the basis of their

4

physical appearance (e.g. clean fine sand with many small shell fragments).

Subsequent granulometric analyses were conducted using laboratory standard sieves

and laser particle size analysis (Malvern Instuments Mastersizer-X) for finer fractions

(Jantschik et al., 1992).

Figure. 4. Underwater video tow-sledge in position on aft of vessel ready for deployment through A-frame. (left) and close-up of side elevation showing camera position (C) and lights (L).

Figure. 5. Schematic showing details of set-up for video logging system.

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GIS is an essential element of study and ESRI ArcView (V3.3)TM and ArcGIS (8.2)TM

proprietary systems were used to provide a common platform in which all spatial data

were integrated and where various numerical and spatial analytical operations were

undertaken. Tasks ranged from initial operational planning for survey coverage

through to data integration, analysis, presentation and map production. All data were

projected to a common reference frame in UTM based on the WGS 84 geographic

datum. Tabulated point data (sediment samples, photographic locations, scallop

sample tow locations) were normally imported to GIS using SQL (structured query

language), whilst MBES data products were normally imported directly as geotiff

images.

Results and Analyses

Description of Bathymetic data and Submarine Landscape

Good quality coherent MBES data covering approximately 70% of the total extent of

the known south coast scallop grounds was generated. These data were generally of

good quality though some system induced artefacts have been noted, particularly in

data from the initial (2001) field campaign. These are not generally of sufficient

magnitude or extent to effect the utility of the data for the purposes required. From the

sun illuminated imagery and bathymetric data it can be seen that seabed in the study

area slopes gradually from north e.g. 40m isobath to south +/- 90m water depth, over

a distance of 50km. The north of the area is characterised by a narrow band of

outcropping rock which extends further northward to the shore. This rock platform is

bisected by a single large incised sediment channel (palaeochannel) with a range of

other conspicuous glaciofluvial features (Gallaher, Sutton & Bell, 2004). These

features are clearly visible in shown in Figure 6.

6

Figure. 6. Sun illuminated gridded bathymetric image of the northern sector (inshore ground) of the survey area. Depths range from approx 38m (warm colours) to approx 50m (cool colours). Two arcuate glaciofluvial features can be clearly observed.

Complete sediment cover extends southward to the seaward limit of the scallop

grounds, however the northern distinctive terrain gives way to a rather flat submarine

plain dominated by two main acoustically distinct sedimentary facies (Figure. 7). This

area is characterised by a presumed gravel lag overlain by swarms of elongate low

relief arcuate dune-like structures (Figure. 8), which are arranged in organised trains.

These dunes and other mobile sedimentary features with distinct topographic

expressions are also clearly discernable in the backscatter imagery, typically

possessing a distinctive “light” appearance characteristic of lower backscatter

substrates. Intervening areas characterised by coarser gravely sediments have a much

darker signature (higher backscatter).

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Figure. 7. MBES sun illuminated gridded bathymetry of southern section (B & H ground) of survey area. Depths range from approx 50m (warm colours) to approx 90m (cold colours).

Figure. 8. Shows a fragment of the previous image at a higher magnification. Here the predominantly sandy sediment dunes can be clearly seen.

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Normalisation of Acoustic Returns

Data output files in text-file format giving the geographic location, beam number and

amplitude value of all binned soundings were filtered and corrected to remove any

angular effects. The backscatter values mostly affected by a varying angle of

incidence are the acoustic responses directly below the transducer (the specular zone)

and the reflected signals from the outer beams. A procedure was thus adopted where

the data derived from these beams was deleted, and corrective procedures applied to

the acoustic data between these two zones (Figure. 9).

Figure. 9. Schematic drawing of swath identifying specular zone and outer beams.

Backscatter values from two sections of the swath - obtained from beams 10 to 40 and

from 70 to 100 - were corrected using a procedure* which involved correcting all the

data to an angle of incidence of 45°. The corrected amplitude values were imported

into ArcMap as a table and displayed as a point file. The points were interpolated to

create a continuous surface and the resulting ground type image, displaying a range of

backscatter values, was ready to be classified (Figure. 10).

* In order to reduce the dynamic range of the recorded data, all backscatter values were adjusted by the same number of decibels required to bring the amplitude value of the beam with an angle of incidence of 45° to the normal (as noted by a fitted line model of the data which plotted amplitude against beam number) to the median value recorded for that beam.

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Figure. 10. Backscatter intensity image of entire area surveyed depicted in grey scale. Strong echo returns are shown in dark tones and weaker returns are displayed as lighter tones.

Seabed Classification

Classification of the seabed according to the dominant sedimentary facies was

undertaken based on detailed analyses of MBES acoustic data in combination with

groundtruthing information from sediment particle size analysis and video imagery.

Sampling locations are shown in Figure 11.

Classification of the acoustic data involved:

(a) Classifying areas on the backscatter image that corresponded to sand and

gravel using video footage of the seafloor;

(b) Extracting amplitude values for sand and gravel ground types from the

acoustic imagery previously created.

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Figure. 11. Location of sediment samples and video footage to aid in seabed classification.

Analysis of video data

Video footage from 21 tows were analysed to identify sand and gravel areas. Each

tow, measuring approximately 1 km in length, collected a continuous sequence of

seabed imagery, which could be viewed using BlueGlen CamNav Browser (V3.0.,

2004). The browser enabled photographs of the seabed to be viewed alongside an

acoustic interpretation of the same area (Figures. 12 & 13). The spatial location of

areas defined as sand and gravel were noted for each tow.

11

Figures. 12 & 13. Video footage of the seafloor (right-hand side of picture) can be viewed simultaneously with an acoustic representation of the same area (left-hand side of picture).

12

Spatially referenced points from the navigational files for each individual video tow

track were classified as either sand or gravel. The points in these files were colour

coded according to ground type and displayed over the backscatter image in ArcMap

(Figure. 14). Thus, with the aid of the video footage, the acoustic backscatter data

could be classified into two principal ground types - substrates dominated by either

sand or gravel. Amplitude values for sand and gravel thus classified were extracted

from the acoustic images using the Spatial Analyst tool.

Figure. 14. Backscatter imagery with towlines along which video data was collected overlain.

The results of the analysis showed that gravel and coarser sediment-dominated areas

were represented by higher backscatter values (darker tones on the image), defined by

an acoustic range between –20db to –45db. In contrast, the lighter regions of the

image, highlighted by an acoustic range of –50 to –90db, identified areas where sandy

sediments are the predominant substrate.

Analysis and Classification of Sediment Samples

A total of 79 seabed sediments samples were collected with a broad spatial spread

across the study area. In most cases samples were collected on a random basis,

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however one series of samples deliberately targeted alternate light and dark acoustic

facies along transects designed to traverse the regular dune characterised topography

of the southern sector. As described in the main methods section the relative

proportions of various particle size fractions (more than 80 for some samples) were

determined. In order to integrate and visualise along with the other data sets it was

then necessary to simplify the complex detailed results thus obtained. For this purpose

the Folk (1954) convention for the classification of unconsolidated sediments was

adopted. The Folk system is based on the relative percentage of three principal units

of sand, gravel and mud of which each sample is comprised. Thus all the multiple

narrow size range particle size fractions were aggregated into these three broad

particle sizes ranges. Table 1. illustrates an extract from the tabulated results of the

Folk classification showing typical Sandy Gravel and Sand samples, whilst Figure 15

below illustrates the 11 sediment types represented in the dataset as a whole, together

with the percentage of samples that fall into each Folk class. The Folk classification

scheme (tri-plot) is illustrated in Figure 16.

Sample Name

Latitude DD

LongitudeDD

Mud (%)

2mm Folk Sediment

Type SC01_7 51.607717 -6.822550 1.16 21.15 77.70 Sandy Gravel SC01_14 52.048650 -6.816517 4.36 95.20 0.44 Sand

Table 1. Extract from tabulated results of Folk classification of sediment samples.

40%

14%

13%

10%

9%

5%

3%

3%

1%

1%

1%

Sandy Gravel

Sand

Gravel

Slightly Gravelly Sand

Gravelly Sand

Muddy Sandy Gravel

Gravelly Mud

Gravelly Muddy Sand

Muddy Gravel

Muddy Sand

Slightly Gravelly MuddySand

Figure 15. Pie chart showing the range of Folk sediment classes represented in the study area and the relative proportions of each class within the data set as a whole. This clearly shows that sands and gravels and mixtures of these comprise more than 80% of the samples collected.

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Figure 16. Folk (1954) classification scheme. Standardised scheme adopted for classification of seabed

Kosteylev & Todd (2005, A) demonstrated the existence of a significant log-linear

correlation between acoustic return strength and average grain size from sediment

samples, where the variability of grain sizes in a sample generally decreases with

backscatter intensity. Observations on the average fraction of sand and gravel in grab

Figure. 15. Percent sand/gravel from a select number of grab samples.

sediment samples. Colour scheme here based on British Geological Survey 1:250,000 scale seabed sediment map series.

samples from the study area also conform to this relationship (Figure. 15).

Particle Sediment Analysis

0%

25%

50%

75%

100%

-27 -28 -32 -33 -36 -38 -47 -50 -52 -58 -60 -61 -66 -69 -70 -71

Rel

ativ

e Pr

opor

tion

of S

edim

ents

GRAVEL

SAND

MUD

Amplitude (db)

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The graph shown in Figure 15. highlights a select number of samples, and adds

weight to the results obtained from the video analysis, which in general correlate a

low backscatter response with fine-grained sediments and a higher (amplitude)

acoustic echo with coarse-grained sediments. However, some inconsistencies were

noted where sediment samples did not fall onto their expected acoustic class. Despite

these anomalies there were many areas where the classified sediment samples

coincided well with acoustic class as inferred from the backscatter image (Figure. 16).

Figure. 16. Classified sediment samples displayed as a layer over the acoustic backscatter image. Samples defined as sand in the Folk Classification overlie low echo returns and samples classified as gravel overlap the higher amplitude values on the image.

As a final step the entire acoustic image could now be classified and areas of sand and

gravel colour-coded to clearly and intuitively display the spatial distribution of the

two predominant ground types over the whole survey area (Figure. 17).

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Figure. 17. Classified backscatter map colour coded to highlight areas of gravel and sand.

Conclusions

The primary objective of the acoustic survey was to create a map highlighting areas

at could be exploited for the scallop fishery (further details on how the map was

sed for scallop stock assessment are to be found in Tully & Hervas, 2005). Although

not all the sediment types could be identified by amplitude value alone, the ground

types that yield a high abundance of scallop could be readily distinguished from areas

that are not favourable to scallops by analysing the returning backscatter signal.

Several reasons are cited for the apparent inconsistencies in the sediment

type/backscatter correlation noted above. Firstly the backscatter images are composed

of five meter square pixels over which the backscatter values are averaged. Evidence

from the video imagery confirms that there is considerable variability in seabed

morphology and with this particle size distribution over very fine spatial scales e.g. in

the order of one to two meters. As the grab samples from a small area (typically

to an acoustic determination of sediment type. Another reason for locally poor

correlation is likely to be associated with the disproportionate affect that larger grain

sizes, particularly shell hash can have on backscatter intensity (Goff, Olson &

Duncan, 2000). The presence of this material has been clearly noted in sediment

samples and video imagery. A third reason may be associated with the morphology or

gross roughness of seabed. The darker areas of high backscatter are often

characterised by the presence of regular patterns of substantial ripples. These

“megaripples” are typically 0.1-0.2m in height with a wavelength of around 1.0-1.5m

and occur throughout the survey area. In addition to the coarser grainsizes present,

these features impart a gross textural roughness to the seabed that is in stark contrast

to intervening more planar sandier bodies with their finer grained texture.

The protocols for classification should be further developed for future surveys in

order to render maps of a higher resolution that incorporate a fuller and more robust

understanding of the factors contributing to fine scale variability and heterogeneity in

seabed habitats. In order to further classify the acoustic data a multivariate approach

promising

pproach involves the use of automated (supervised) statistically based image

lassification software analyses with QTC Multiview. This classification is currently

the Geological Survey of Ireland (GSI) and the results of that

lassification will be used to update the maps created.

incorporating more features of the raw acoustic data is required. One

a

c

underway at

c

Acknowledgments.

The authors gratefully acknowledge the help, encouragement and generous support of

staff and colleagues in the Marine Institute, Geological Survey of Ireland, Coastal and

Marine Resources Centre, Dept of Geography-University College Cork, Dept of

Geography-UCD, Bord Iascaigh Mhara, Martin Ryan Institute and the National

University of Ireland, Galway. In particular we would like to thank the crew of the

RV Celtic Voyager whose contribution to the success of the seabed mapping

programme cannot be overstated.

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Annex IIIntroductionResults and AnalysesDescription of Bathymetic data and Submarine LandscapeNormalisation of Acoustic Returns

Figure. 10. Backscatter intensity image of entire area surveyed depicted in grey scale. Strong echo returns are shown in dark tones and weaker returns are displayed as lighter tones.Seabed ClassificationMarcon (2006). An Investigation into Scallop Larvae Transport and Settling Patterns off the Southeast Coast of Ireland. Final report of project 01.SM.T1.07