Applied Acoustics 70 (2009) 1248–1257

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Applied Acoustics

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Acquisition and processing of backscatter data for habitat mapping – Comparisonof multibeam and sidescan systems

T.P. Le Bas *, V.A.I. HuvenneNational Oceanography Centre, European Way, Southampton SO14 3ZH, UK

a r t i c l e i n f o

Article history:Available online 30 September 2008

Keywords:BackscatterMultibeamSidescanResolutionProcessing

0003-682X/$ - see front matter � 2008 Elsevier Ltd. Adoi:10.1016/j.apacoust.2008.07.010

* Corresponding author. Tel.: +44 (0)23 8059 6557E-mail address: tlb@noc.soton.ac.uk (T.P. Le Bas).

a b s t r a c t

Often marine habitat surveys use multibeam bathymetry systems to model the seafloor. This describesthe morphology but not the terrain lithology or substrate. Backscatter imagery helps the interpreter tobetter classify the physical environment that may support a particular biological community. In this con-tribution, the acquisition performance of both multibeam and sidescan sonar backscatter imagery arecontrasted and examples shown. The logistical factors affecting the two systems during surveying are dis-cussed and data from both systems compared.

Choice of systems for habitat mapping is discussed. A relative cost analysis of the various survey sys-tems is presented with varying resolution and coverage. The size and shape of the footprint, and thus res-olution, is variable dependant on many factors, including ship speed, data processing and sampling. Theresolution and formation of imagery is important, but high sampling rates are shown not to be a completesolution as over-sampling can present a false impression of high resolution. However, it is suggested thatbackscatter imagery should have least 7 bit sensitivity to aid visual and digital inspection. Habitat map-ping examples are shown using multibeam backscatter and sidescan sonar, where the processing hasbeen optimised for backscatter imagery. A key question is how much of high resolution bathymetry datais essential for habitat mapping, and whether backscatter imagery can provide more of the informationrequired at a higher resolution than a bathymetric morphology map.

� 2008 Elsevier Ltd. All rights reserved.

1. Introduction

The aim of this paper is to show the value of acoustic backscat-ter imagery when available for habitat mapping. The correct choiceof the acquisition system and how the data is used and processed,is paramount to useful data being acquired and interpreted. Com-parison is made between multibeam backscatter data and sidescansonar imagery, and their relative strengths and weaknesses areshown, during acquisition and data processing.

For nearly half a century acoustic data has been used to map theshape and type of marine environment. Initially single beam echo-sounders and seismic techniques were used to determine depthand bottom type. This gave line profiles of the seafloor but not fullarea coverage. Today, the two main sources of acoustic data thatare used to map the seafloor are multibeam systems and sidescansonar [1]. Both give full coverage, however, multibeam bathymetrysystems are now often preferred and used routinely for survey in-stead of sidescan sonar. The main advantage is that understandingof bathymetry is considerably easier than backscatter imagery.Sidescan imagery on the other hand gives information which is afunction of both bottom morphology and lithology but is more

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complex to understand. Morphology and depth do give some in-sight into the seafloor environment and often derivatives of thebathymetry such as roughness and slope can be used to delineatesimilar areas of morphology e.g. [2,3]. Together with the backscat-ter information, habitat mapping can then use these areas andcharacteristics to classify the seafloor into neighbourhoods.Ground truth data either from photographic or physical samplescan then be used to test hypotheses of the adherence of these datato the classifications created. Hence, backscatter imagery may indi-cate the environmental conditions for potential habitat of a specificbiological species, but not necessarily predicting whether the spe-cies are actually present.

The two sources of backscatter data (multibeam backscatterdata and sidescan sonar imagery) have many similarities but alsodifferences. One of their greatest differences is the beam patternused for sampling (see Table 1). There are three types of multibeambackscatter data: single beam intensity, individual beam time ser-ies or integrated time series (pseudo-sidescan). The single beamintensity gives a single value for each beam and therefore hasthe same resolution as the bathymetry data (see Fig. 1). This isthe most crude and low resolution backscatter data having thesame resolution as the bathymetry data, but it does provide someidea of the seafloor hardness. The second and potentially datarichest method, is when each beam is sampled over time to give

Table 1Differences between multibeam and sidescan sonar systems beam patterns

Multibeam backscatter (and bathymetry) Sidescan sonar imagery

Beam type Multiple beams Single wide beamSwath width Usually about 5� water depth (in practice) Up to 15� water depthGrazing angle �15–90� Higher incidence (less bathymetric control) �0–90� far range often has shadowsDirectivity power Many null zones (between individual beams) One null zone (near-nadir)Backscatter response Single frequency Separate port and starboard frequencies

Fig. 1. Example of a mosaic created from single beam intensity multibeambackscatter values and corresponding shaded bathymetry (depths varying from300 m to 3600 m). Location is south of Fogo, Cape Verde. The resolution is the sameas the bathymetry data (100 m). However, the backscatter identifies the differencein lithology in the channels flowing south off the island. High backscatter (white) isshown in the channel paths and thus is interpreted as coarser sands and gravels inan active channel. Low backscatter areas (dark) are interpreted as finer sediments.

Fig. 2. Example of a mosaic from north of Sao Antao, Cape Verde, created frommultibeam backscatter data using time series from all the individual beams and thecorresponding shaded relief bathymetry (depths varying from 600 m to 3000 m).The pixel size is much smaller than the bathymetry grid. Compared with Fig. 1, thedata shows the detailed lithological variations and morphology not seen in thebathymetry. The backscatter shows many channels flowing off the island (directionof flow indicated) – white is high backscatter. A large channel (outlined in red) isseen in the bathymetry data but not so evident in the backscatter imagery (mainlylow backscatter) signifying that the channel has a very different lithology orsubstrate. (For interpretation of the references to colour in this figure legend, thereader is referred to the web version of this article.)

T.P. Le Bas, V.A.I. Huvenne / Applied Acoustics 70 (2009) 1248–1257 1249

‘snippets’ of backscatter data. These can then either be stitched to-gether or viewed individually. Fig. 2 has an example of these datastitched together as a mosaic showing differences between brightand dark channels, indicating whether the channel is sand-richor poor and progressing to interpretation on whether the channelis active or inactive. Another advantage is that each snippet mayhave a particular signature that could be classified in the sameway as single beam echosounder records can be characterised[4]. The third type of multibeam backscatter data are provided asa complete time series in a similar way to sidescan sonar (seeFig. 3). Resolution is higher than the corresponding bathymetrydata, having a higher sampling frequency. Fig. 4 shows a 3D modelof the data seen in Fig. 3 and illustrates the greater resolution inthe backscatter imagery compared with the bathymetry.

Cognitive choices of systems, method of acquisition and pro-cessing have to be made. Advanced techniques for characterisationand interpretation are now available for multibeam system data

[5,6]. Sidescan imagery has also been characterised using texturemapping [7]. These complex mathematical processes can be highlysensitive to the acquisition and setup parameters and the process-ing used. Therefore, knowledge of the acquisition parameters isessential for optimal characterisation leading to meaningful habi-tat mapping.

2. Data acquisition and processing

2.1. Acquisition parameters

Sediment (or rock) type, roughness, grainsize, compaction andslope define the acoustic response of the seabed [8]. Thus, the

Fig. 3. Example of the value of pseudo-sidescan backscatter imagery for habitatmapping rather than just bathymetry. Shown here is a multibeam bathymetryshaded relief and backscatter imagery (pseudo-sidescan) from south west of Barra(Outer Hebrides). Water depths vary from 60 to 160 m (red to purple, respectively).Top right shows tabular sand bodies (darker backscatter) showing gaps to the veryslightly deeper gravel windows (irregular shaped bright backscatter) below. Theyare invisible in the bathymetry imagery (purple) but easily stand out in backscatterimagery. (For interpretation of the references to colour in this figure legend, thereader is referred to the web version of this article.)

Fig. 4. Three dimensional backscatter imagery for habitat mapping. This is the samearea as in Fig. 3 and shows the lack of bathymetrical morphology for the sandbodies and gravel windows. Some of the brighter areas are associated withbathymetry features and are interpreted as rock.

1250 T.P. Le Bas, V.A.I. Huvenne / Applied Acoustics 70 (2009) 1248–1257

backscatter imagery provides a representation of the seafloorwhich is a mixture of bathymetry morphology, biological sub-strate, and geological seafloor lithology. Biological influences canoccasionally also affect the imagery if the acoustic wavelength issufficiently short relative to the size of biological feature.

As there are many different systems available for acoustic sur-veying it is useful to be able to appreciate the choices availablein the market and their characteristics. For a good list of systemssee [9]. There are many parameters to be considered in the forma-tion of imagery. Conciliation between these different parametersdefines the geometry and capabilities of the different systems.The parameters can be divided into four characteristic groups:transducer design, water-column, towing and mounting, and datalogging.

(1) Transducer design is obviously important in the productionof the acoustic pulse. These parameters are generally pre-definedby manufacturers but can sometimes be altered during acquisition.Transducer frequency defines the range of useful signal, the lowerthe frequency the greater the range, for example a 12 kHz systemwill give about 10 km slant-range thus being suitable for hull-mounting and deep water survey, whereas 30 kHz will give 3 kmslant-range and thus either needs to be deep-towed (e.g. TOBI) orin shallower seas. 100 kHz and 400 kHz systems are only usedclose to the seafloor as the pulse is lost to attenuation after about400 m or 100 m, respectively. Radius and shape of individual trans-ducer plates defines the shape and narrowness of each beams. Ori-entation and shaping between transducer rows further define howthey interact constructively and destructively. Directivity of theconstructed beams is defined often by the boresight – the angleof dip of the maximum beam [10]. Longer arrays give tighter beampatterns (higher resolution) but a longer pulse length will givelonger range but poorer resolution.

(2) Characteristics of the water-column define the spreadingand absorption of the acoustic signal. The salinity, temperatureand pressure profile of the water-column will define the soundvelocity. Refraction of the acoustic wave through the layers ofthe water-column can affect the imagery, though generally onlyto a minor extent. Significant temperature changes in the water-column layers and poor mixing can produce anomalous soundvelocity gradients but is unusual.

(3) The length of cable when towing of sidescan sonar systemsand the speed of survey define the positioning of the imagery. Forhull-mounted systems positioning of the imagery is generallymuch more precise but at the expense of being further from theseafloor and causing an inherent lower resolution. Height of thevehicle above the seafloor is important for defining swath width,the greater the altitude above the seafloor the wider the swath. Arule that is often used for towed sidescan sonar systems, is the alti-tude of the system above the seafloor is about 10% of the swathwidth. This can be difficult to achieve in rugged terrain and thuscompromise must be made with achievability and safety.

(4) As the acoustic wave is received it needs to be sampled. Dig-ital data logging is dependant on the sampling rate. Too high asampling rate will create data that is simply oversampled andmay just represent the original transducer pulse shape, whereasa low sampling rate will give low resolution imagery. The pulseinterval will define the range available for imagery.

Differences between sidescan imagery and multibeam back-scatter imagery are defined by the above acquisition parameters.The distinctive effects on the acquisition are tabulated in Table 2.Multibeam systems collect both backscatter and bathymetry dataand thus compromises have been made during this comparisonof characteristics so that both datasets can be used. For examplemultibeam backscatter imagery (pseudo-sidescan) can haveapproximately the same swath width as sidescan, however, thebathymetry far range beams do not have the same across-track

Table 2Comparison of generalised acquisition characteristics for multibeam backscatter and sidescan sonar imagery systems

Multibeam backscatter (and bathymetry) Sidescan sonar imagery

Speed of survey (for 100%coverage)

Slightly higher Slightly lower (limited by ping rate and along-track resolution)

Line spacing Requires good overlap between lines (for IHObathymetry standards)

Minimal overlap is acceptable (although far range may have large shadows)

Ends of lines Quick turns acceptable Large curved turns required to keep towed fish from sinkingRange Better backscatter range than bathymetry but

still limitedGood range

Coverage Approximately half of sidescan coverage Approximately double of multibeam coverageInstallation Hull-mounted (dry dock required?) or pole

mountedWinch for cable required?

Ease of launching Lower pole and secure or just switch on Lower fish into water and pay out of cableInstallation calibration Calibration ‘‘Patch test” required – time

needed to completeCalibration testing not required – though some sidescan system now give a response indB.

System watchkeeping Minimal watchkeeping required Cable length needs constant adjustment to keep fish flying at suitable altitudeNavigation Line following critical for multibeam coverage Not absolutely critical because of data overlapHardware costs Expensive BUT free if already collecting

bathymetry dataRelatively inexpensive

Positioning of data Data very accurately placed, due to attitudesensor and transducers fixed to boat

Layback of cable – does the fish follow the boat track? Positioning much less accurateunless using separate system (e.g. USBL – ultra short baseline transponder)

Data fusion (addingbathymetry and otherdatasets)

Automatic registration with bathymetry Requires registration

Power settings/pulse length Usually set for bathymetry returns (notbackscatter)

Automatic gain settings when in use to use fullest dynamic range. Pulse length can beuser defined

Weather/tide Medium seastate maximum tidal correctionmay be needed

Seastate can be high if towing with long cable, Tide immaterial

Resolution Lower (further from the seafloor) Higher (closer to the seafloor)

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range due to noise, energy and angular spacing. Therefore, theinterline spacing is reduced for multibeam systems to maintain fullcoverage with bathymetry, thus the effective range is much smal-ler (see Fig. 5).

When choosing a system for habitat mapping there are threeconsiderations that usually define what type of survey is chosen;the resolution, the size of the area to be surveyed, and the moneyavailable (see Fig. 6). An ideal solution would be high resolution,high coverage and low cost. Sidescan sonar imagery comes closestto fit these criteria, though resolution may not be high enough forsome purposes. Also sidescan sonar systems do not usually givehigh resolution bathymetry and this may be a requirement, thougha newer generation of interferometric systems are now available.Two non-acoustic methods of photography and sampling are in-cluded to complete the list of survey methods available. Both havevery small footprints (coverage) but very high resolution withinthat coverage.

Fig. 5. Two backscatter mosaics of the Western Solent (off the NW Isle of Wight, UK) shohand imagery was acquired by sidescan sonar of 325 kHz frequency with 105 m range,with 50 m range. Both datasets were acquired simultaneously. Twice as many lines wermultibeam bathymetry. Notice the higher resolution and dynamic range in the sidescan

2.2. Navigation

Accuracy of navigation for sidescan and multibeam data is obvi-ously important. With the advent of DGPS, ship positions can bedetermined with sub-metre accuracy. It may be required for loca-tional data of the transducers relative to motion sensors and GPSantennae to be fixed by total station surveying. Accuracy is oftenrequested for positioning precision to be a few millimetres accu-racy when doing very shallow water surveys to IHO (InternationalHydrographic Office) standards. Whilst this accuracy is admirableit often is not achievable and a slightly larger error can be toleratedfor environmental surveys. This has the advantage of ships of con-venience being utilised, without extra costs being unnecessarily in-curred for installation. Seafloor shape is not unduly compromisedand errors here have little or no effect on backscatter data.

Navigation of towed systems can lead to mis-positioning of thevehicle and thus the imagery. Ultra-short baseline (USBL) systems

wing gravel waves and darker sand ribbons in water depths of about 20 m. (a) Left(b) right hand imagery was acquired by a multibeam system of 200 kHz frequencye surveyed than were required by the sidescan sonar, to gain 100% coverage for the

mosaic.

Fig. 6. Two graphs illustrating the considerations when defining survey require-ments and types of equipment to be used. Seafloor resolution from low to high areplotted against costs of survey per day (low to high) and daily coverage (low tohigh). There will be some variation and overlap between different systems. Allsystems are compared against other systems applicable for the same water depthand thus values are relative depending on survey area and depth.

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give distance and azimuth from the ship with accuracies of 5 m infull ocean depth [11]. These systems can be bulky, and thus forsmall shallow-water surveys the standard basic navigationalparameters collected are the cable length, towing speed and vehi-cle depth, from which the vehicle position can be calculated(approximately). Occasionally only cable length and towing speedare recorded and thus towing configuration is lacking depth infor-mation. In reality the vehicle position depends on many variables;towed body weight (with possible depressor), lift and drag, cablediameter, cable length and weight [12]. The cable and towed bodythen interplay to define the cable shape. External forces such ascurrents and track changes also affect the positions of the towedsystems. Positional uncertainty from towed systems are usuallythe main factor in problems with mosaic mismatches.

2.3. Image formation

Backscatter imagery is usually viewed in monochrome. Themost popular polarity of the imagery seems to be a strong signalprints darker than a weak signal. This was an effect of the workingsof early thermal printers of the 1970s and has remained in usesince then. The disadvantage is that acoustic shadows appear aswhite shapes rather than dark, which is counter-intuitive. Invert-ing the display polarity is often done to correct this inconsistencyand the imagery frequently exhibits different features in the imag-ery for interpretation. Using both polarities can assist the inter-preter to identify features though keeping mindful which is highor low backscatter. Image processing packages can contrast en-hance the imagery but will be limited by the level of noise and sig-nal content [13].

Visual inspection either on-screen or on paper is dependant onthe ability of the human visual system to discern intensities. Thehuman eye adapts to localised intensity variations when lookingat complex imagery, and sees about 18 different grey levels. How-ever, to gain a complete picture of imagery there should be 2% con-trast differences (the ‘Weber fraction’) which for a computermonitor requires a contrast ratio of 10 (per channel) gives about100 grey levels [14]. In today’s PC market this is a 1000:1 contrastratio (3 channels; red, green and blue). This therefore requires aminimum of 7 bits per pixel. It has been observed that some acqui-sition and processing systems have only 5 bit detail in the back-scatter and thus are being limited in their dynamic range.

Noise, whether from speckle or from other sources, reduces theimage quality considerably. High sampling regimes can help toeliminate some higher frequency sources by averaging severalsamples and assuming that the decorrelated nature of noise willcancel it out [14]. Thus oversampling and averaging of signalscan be used to improve the signal-to-noise ratio. Fig. 7 shows anexample of a sidescan mosaic processed in two ways, both withthe same pixel resolution. The first is subsampled and the secondis averaged. It can be noted that the dynamic range is higher onthe former image but more correlated and interpretable on the lat-ter. Some image processing software use a pyramid of layers sothat when displaying imagery the optimal averaging layer is usedwhen viewed on a limited output device. For example viewing amosaic of size 4000 by 3000 pixels on a 1024 by 768 resolutionscreen will require only a 16th of the data and thus a 4 by 4 aver-aged value will give a better representation of the acoustic charac-ter of the whole pixel area.

2.4. Processing

Once data is acquired its processing is critical to proper inter-pretation. Often much of the costs are used in acquisition and verylittle is left to spend on processing and interpretation. Whilst rawdata can be viewed and interpreted by experienced users, it is oftenthe integration of multiple passes, their geometric shape or fusionwith other datasets which solidify ideas and interpretations. Mapproduction relies on good data processing.

Calibration of multibeam backscatter imagery to decibel back-scatter strength can now be obtained. However, the systematiccorrections must be done to a very high degree of accuracy andthe system calibrated over a known patch of seafloor [15]. Quanti-tative analysis is therefore often foregone and qualitative analysisused in conjunction with various seabed sampling techniques orseafloor photography. The returning backscatter strength is a func-tion of three parameters: Source power, absorption in water andinteraction with the seafloor. The first and last parameters areangular dependant and absorption is dependant on range. Com-pensation for these effects (sometimes known as ‘shading’) canbe calculated from the collected data. If it is assumed that a fullrange of backscatter returns are collected at all angles and rangesa pseudo-calibration curve can be determined. Using this curvethe data can be compensated for average transducer directivity(angular), attenuation and spreading in the water-column (range)and seafloor incidence (angular). The effect is to equalise the levelof insonification of the seafloor all across the swath and can beused on multibeam backscatter and sidescan imagery [16].

All acoustic data uses the conversion of time delay from thetransducer ping to interaction with the seafloor and return to areceiving array, to a distance. For this a speed of sound in wateris required, either in the form of a single value or as a continuouslyaltering velocity profile with depth. Occasionally software pack-ages can take the velocity profile into a third dimension by usingmultiple sound velocity profiles in different locations. A paradigmarises as velocity dips are taken at different times in different loca-

Fig. 7. Comparison of subsampled imagery (left) or averaged pixel imagery (right). Area of gravel waves and sand ribbon in the Solent, north west of Isle of Wight.

1.0 oise

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tions and may be influenced by water current movements. Varia-tions in sound speed are approximately ±1% of the overall speedand thus could give a similar slant-range variation. Sound velocityprofile error calculation is possible with crossing survey lines [17].However, in most cases, using a single velocity profile should re-duce errors considerably to a level that is well within the requiredaccuracy for non-navigational mapping.

Slant-range correction of backscatter imagery is essential togain the complete across-track geometrical shape. No bathymetryinformation comes with sidescan sonar apart from the depth tothe first return, which is assumed to be an altitude value from di-rectly below the vehicle. The sampled time series can be convertedinto a line of equally distanced samples ready for orientating on amap, using the altitude, the sound velocity profile, and the flat-bot-tom assumption. The assumption that the seafloor is flat is notaccurate – especially if there are regional slopes, seamounts or can-yons. The question therefore is the degree of error. If a constantseafloor slope is assumed over the swath width a function can bedefined for the slant-range error as a percentage of the full slant-range with the only variable being slope angle. It is assumed thatthe sonar fish is flying at the optimal altitude i.e. 10% of range.Fig. 8 shows the error curves for seafloor slopes from �10� to 10�in 2� intervals. For example a 4� sloping seafloor and using a100 m range sidescan system will locate features incorrectly by45–90 cm. The angle for continental slopes may be as high as 10�and thus some error may become apparent. Increases in slant-range also bring uncertainties in navigational positioning, as wellas an increasing footprint size.

Multibeam backscatter data does not rely on slant-range correc-tions as each beam already is placed in space using the beam angle

-4

-3

-2

-1

0

1

2

3

0 20 40 60 80 100Percentage of full slant range

Slan

t ran

ge e

rror

(% o

f sw

ath

rang

e)

10°

0°

-10°Slope angle

Fig. 8. Graph to show slant-range error as a percentage of swath width when usingthe assumption of a horizontal seafloor rather than possible regional slopes (up to10�). Regional slopes are usually much less than 5� and thus the slant-range error inposition is generally less than 1%. For example the TOBI sidescan has 3000 m fullrange thus the error at far range is probably less than 30 m which is equivalent to5 � 6 m pixels.

and range time. This is equivalent of a true slant-range correctionwhich can be done to sidescan data if bathymetry data is available.

Tidal corrections for bathymetry data are essential in shallowwater. Predicted tides only measure the astronomical contribu-tions to tide. Measured tidal data can differ considerably from pre-dicted tides due to weather surges, geographical position, densitychanges and currents [18]. Therefore, tide gauges must be moni-tored for navigational quality bathymetry. Bottom topography rel-ative shape is less affected by errors in tide level and thus can beignored. However, the tidal state is not used in the process of posi-tioning for backscatter imagery (multibeam or sidescan) and doesnot significantly alter backscatter strength thus tidal correctionsare not essential here.

Multiple swaths of backscatter imagery are usually acquired tobuild up a complete mosaic coverage (e.g. Fig. 3). Imagery gener-ally is collected so that overlap at far range is about 10–15% ofrange which is enough to allow for correlation of features fromone swath to the next and secondly to permit minor errors in nav-igation and still retain 100% coverage. Then a decision must bemade on map production where data overlaps which data is tobe used in the final map. Easiest choice is to use a mask where,for example, the latest imagery overwrites previously acquiredimagery. Issues here relate to whether the latest data is better thanthe older data. Second choice is to create an equidistant cut line be-tween both tracks and only use the imagery closest to the track. Avariation of this is for the user to define the position of cut-line

0 16 32 640.0

0.2

0.4

0.6

0.8

Averaging factor

Rat

io o

f im

age

cont

ent t

o ra

ndom

n

8

Fig. 9. Graph of the effect of subsampling and averaging the imagery against theimage content. It shows the ratio of the filesize of compressed backscatter imagerycompared with a similar sized random image against the averaging factor used tocreate the image. A random image (i.e. with high image content) will give a ratio ofone whereas a simple monotone image (i.e. with no variation in image content) willgive a ratio of zero. A maximum is seen at an averaging factor of 3 whichcorresponds to the pulse length used in this particular data acquisition system(TOBI). Thus the system seems to be oversampled by a factor of three.

Fig. 11. TOBI sidescan sonar imagery processed at full resolution and dynamicrange showing the Darwin mounds and their tails, after [20].

1254 T.P. Le Bas, V.A.I. Huvenne / Applied Acoustics 70 (2009) 1248–1257

manually and thus noisy or particular good imagery can be cutaround and selected. This is time-consuming but does allow theuser to closely appreciate any features that are insonified fromtwo directions. Last choice is to feather (average) the overlap ofthe two imagery datasets around the equidistant cut line as de-scribed above. Disadvantages of this last method are that featureswill be insonified from different directions and thus may be look-ing at different facets of the same feature, or if navigation issub-optimal, may average different features together. Data thathas little or no overlap is very difficult to interpret as featurescan be discontinuous or sporadic.

2.5. Resolution

Fusion of different datasets together is fundamental to habitatmapping. It is essential to have an understanding of the area inson-ified (footprint) and therefore the imagery’s effective resolution.The insonified footprint of seafloor changes shape dependant onwhether it is at near or far range. Near range the footprint is longacross-track but narrow along-track and changes at far-range toshort across-track and wide along-track. Mid range the footprintis rounder and thus gives more balanced resolution. Increases inthe acoustic frequency allow higher sampling and thus give betterresolution but have the disadvantage of shorter range (caused byattenuation). Higher resolution can therefore be obtained withtransducers closer to the seafloor, thus towed instruments oftenhave finer resolution than hull-mounted systems. The differencebetween resolution footprints often causes interpretations to bemodified. One cause of this is that lower acoustic frequencies(<30 kHz) penetrate the surface of the sediments and provide a sig-nal return from the scatter within a certain volume of sediment ofsubsurface strata. Higher frequencies (>50 kHz) show mainly thesediment–water interface and little volumetric scattering.

Resolution of sidescan sonar imagery is generally requested tobe as high as possible. If the ping interval (period between pings)is set to be long, the distance due to the speed of the vehicle be-tween pings becomes an issue. The data on each side of the vehicle

Fig. 10. Series of across-track averaging factors on TOBI sidescan imagery: (a) Original rawusing a factor of 4. (d) using a factor of 8. (e) using a factor of 16. (f) using a factor of 32. Thfaults on a rafted block on the upper part of a large debris flow near the Canary Islands

are subdivided into a number of equal samples per ping and toequalise the pixel size along-track and across-track a simple for-mula can be approximated to:

across-track pixel size �No: of samples per side

¼ ping interval � 15002

ð1Þ

and if ping spacing ¼ along� track pixel size

¼ ping interval � speed ð2Þ

TOBI image (unsubsampled). (b) The same TOBI image averaged by a factor of 2. (c)e area is approximately 900 by 900 m and shows a series of small failure scarps and

.

T.P. Le Bas, V.A.I. Huvenne / Applied Acoustics 70 (2009) 1248–1257 1255

Therefore : Maximum speed

¼ 15002 �No: of samples per side

ðin m s�1Þ ð3Þ

Thus ping interval is immaterial if these sizes are set to be equal. Forexample the TOBI sidescan sonar system is towed at 3 knots(1.5 m s�1), with 4000 samples per side and has a ping interval of4 s. The speed would have to be 0.188 m s�1 (0.364 knots) to equal-ise pixel edge size. Such slow speeds are difficult to navigate andthus it is usually towed at 1.5 m s�1 (3 knots) which means No. ofsamples per side need only be 500 (for instance subsampling andaveraging by a factor of 8) and pixel size would be set to 6 m. If mis-match of pixel sizes are allowed then the final mosaic may havegaps between pings. Interpolation can be used to fill these gaps,however, if the gaps are large, the interpreter’s eye may be dis-tracted by the apparent smoothness of interpolated values. To coun-ter this, noise can be added to the interpolation values, to give asimilar texture and variance of the acquired data. In practice a mis-match of 2–3 times pixel edge length is found to be acceptable (seeFig. 9). This will improve its visual outlook but may affect auto-mated classification systems and thus must be used only when vi-sual interpretation is to be done.

The desire to have as high resolution imagery as possible maycope with the mismatch between along and across-track foot-

Fig. 12. (a) Multibeam backscatter mosaic processed at a resolution of 1 m but is displaychosen using the backscatter imagery. The area is north west of the Orkney Islands in wshaded relief. Note that some of the facies may have able to be predicted but not withResolution used was 5 m. (For interpretation of the references to colour in this figure le

prints. Thus sampling can be done at a higher rate to gain higherresolution across-track. But when do high sampling rates stop giv-ing seafloor information and start giving over-sampled ping shape?Compression of imagery is often used to reduce the required datastorage. The compression must be non-destructive so that the datacan be reconstituted without data loss. The amount of compressionis therefore dependant on the imagery content; the less the detail(such as features or texture) within the imagery the greater thecompression. A typical compression algorithm that avoids data lossis the ‘‘Lempel-Ziv” coding [19], which cannot distinguish betweenwhat might be called features, noise or oversampling. The advan-tage of this algorithm is that it runs linearly through the dataand looks for coherent blocks of data of variable length.

The hypothesis presented here is that compression size is ameasure of imagery content, whether the content is oversampledimagery or geological features. If this backscatter file is compressedand compared to an image created by a random number generator,this provides a measure of the oversampling content. The ratio ofcompressed backscatter imagery to compressed random imageryis shown in Fig. 9 for a variety of averaging levels (averaging pixelsacross-track) for a sample piece of TOBI sidescan imagery. Thehighest ratio for these data is found at an averaging factor of 3.As the original sampling was 1 ms this is therefore suggesting thatthe optimal sampling period is 3 ms. As the pulse length is 2.8 ms

ed at 2 m to improve the signal-to-noise ratio. Video trawl tracks (green lines) wereater depths 70 to 140 m. (b) Corresponding bathymetry grid for Fig. 12, shown inthe detail seen in backscatter or with the confidence as seen in the backscatter.

gend, the reader is referred to the web version of this article.)

1256 T.P. Le Bas, V.A.I. Huvenne / Applied Acoustics 70 (2009) 1248–1257

this result is reasonable. Fig. 10 shows the practical effect of aver-aging on some raw TOBI imagery. Visual differences between fac-tors 1, 2 and 4 are very slight, reinforcing the hypothesis thatimagery content is maximum at factor 3.

3. Habitat classification

Using the above techniques for imagery acquisition and manip-ulation can have significant effect on the detection and quality ofobservation. Fig. 11 shows an example of a TOBI sidescan sonarmosaic of the Darwin mounds (north west of the Hebrides). Themounds appear on the mosaic as lozenge shaped areas of brightbackscatter of about 70 m diameter. Most of the mounds (but notall) have ‘‘tails” of slightly less bright backscatter which are onlyjust brighter than the background sediments. The data has beenprocessed using the highest resolution the data allows (2.25 m),and averaged to reduce noise. The mounds now are clearly mani-fest from the background and interpretable. Subsequent seafloorphotography and sampling have shown these mounds to be cov-ered with living colonies of the coral Lophelia pertusa [20]. Themounds have virtually no topography (maximum 5 m) but are lo-cated in 1000 m of water. The tails are obviously connected tomounds but have no topographic signature and have been seento have higher density of the xenophyophore Syringammina fragi-lissima [20]. The detection of these mounds and tails would nothave been possible using hull-mounted multibeam systems asthe resolution would have been too poor to resolve these as signif-icant features (in the order of 50–100 m pixel size). The use ofhigher frequency sidescan imagery (e.g. 30 kHz), towed closer tothe seafloor (e.g. 300 m off seafloor) led to the discovery of theirexistence, whilst still giving 100% coverage of the area.

An example of multibeam backscatter imagery is shown inFig. 12. This shows the continental shelf north west of the OrkneyIslands in water depths of about 100 m. Again the backscatter mo-saic shows considerably greater classification of the terrain thanthe bathymetry alone, and allowed three targeted video transectswith a much higher degree of accuracy and use [21]. The informa-tion was then used to extrapolate habitat mapping to regions notcovered by the video tows.

Texture mapping is often used to help in classifying acoustic re-sponse imagery. There are many different systems for classificationwhich rely either, on identification of differences in the acousticsignal character returning to the transducer, or, on the texture ofthe backscatter imagery, or on a mixture of both. Papers later inthis issue describe these techniques in detail. It must be remem-bered that all techniques require good acquisition practices andappropriate processing.

4. Conclusion

A comparison of multibeam backscatter and sidescan sonar sys-tems has shown their similarities and differences. Choice of whichsystem to use must be made by individual users. A key question iswhether bathymetry is really required at high resolution or woulda basic contour map of the highs and lows be sufficient, togetherwith a higher resolution sidescan sonar mosaic? Whilst good reso-lution bathymetry data goes some way to delineate morphologicalregions and thus habitats, the value of higher resolution backscat-ter data for interpretation and classification is possibly of greateruse, when trying to produce detailed habitat maps. Other questionsto be asked are what systems are available, the reason for the sur-vey, whether wide coverage is required or if it is important to havedetailed high resolution imagery? A consideration should be madefor the type of ship required and its suitability to the task such asweather. For example, sidescan sonar systems are much more

stable in bad weather but more difficult to launch or recover insuch conditions.

Correct processing can turn unclear raw data into feature-richmaps [15,22]. Various techniques have been shown to get the mostfrom the data, minimising the effect of noise and reinforcing thesignal. High resolution imagery is a compromise between over-sampling, survey speed and data averaging. Contrast range shouldhave at least 7 bits per pixel. Good navigation is important whentrying to match different datasets together or when using theinterpretation to revisit the locality. However, minor navigationalerror can be ignored if the required result is a calculation of habitatareas or recommendations for marine protected areas with bufferzones.

Backscatter maps have indisputable value for the prediction ofhabitats and allow subsequent targeting by even higher resolutionsampling techniques. Once sufficient groundtruth data is availablethe backscatter maps can be used to extrapolate the habitat classi-fication to give much greater coverage.

Acknowledgements

The authors would like to thank all the contributors of dataused here as examples, in particular Annika Mitchell, Doug Masson,Colin Jacobs, Ingo Grevemeyer and Veit Hühnerbach. We wouldalso like to thank Russell Wynn for discussion of this manuscriptand his support.

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