Post on 23-Oct-2020
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
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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.
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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.
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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).
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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