SEABED CLASSIFICATION USING MULTIBEAM SONAR BACKSCATTERChris Esposito and James Kulpa

Foth / CLE Geophysical Surveys 10 Commercial Blvd., Suite 100

Novato, CAChris.Esposito@foth.comJames.Kulpa@foth.com

INTRODUCTION

California Shore and Beach Preservation Association – 2018 Conference

Multibeam echosounders (MBES) were originally developed formilitary applications. In the 1970’s, they were deployed commerciallyto provide swath coverage of the seafloor; and, in the 1980’s and1990’s, higher frequency multibeam systems were developed forshallow water environments to improve the achievable resolution ofthe data. During this period, the sonars were used primarily to studythe bathymetry of the seafloor, using the time it takes for the soundsignal to travel from the sonar to the seafloor and back to calculatethe depth. However, over the last decade, researchers and industrypartners have begun to exploit the fact that the sonar also recordsthe intensity of the returning acoustic signal, providing informationabout the type of substrate from which the signal returns. Nowadays,multibeam backscatter is becoming recognized more and more asan invaluable tool.

Foth / CLE Engineering (Novato, CA) has taken advantage of recentadvances in multibeam sonar and combined this technology withtraditional bathymetric surveying technologies and precise Real-Time Kinematic GPS (RTK-GPS) on one survey platform. The resultis the ability to concurrently map bathymetry, benthic habitat types,and seafloor geology in one pass of the survey vessel

Multibeam backscatter is simply the amount of acoustic energybeing received by the sonar after a complex interaction with theseafloor. This information, though, is highly useful for seafloorclassification, as different substrate types reflect or scatter acousticenergy differently. For example, a hard bottom, such as asubmerged carbonate reef, will reflect back a large portion of theacoustic signal compared to a softer bottom such as mud. Theserelative differences in intensity of the acoustic backscatter can beused to map the substrate and classify the bottom types on theseafloor.Depending on the need of the research team and the multibeamsonar being employed, different methods may be employed torecord the backscatter intensity values:1. Pseudo-Sidescan: produces an image analogous to sidescansonar by combining the starboard beams and combining the portbeams into two wide angle receive beams.2. Beam Average: Each sonar beam’s footprint on the seaflooris reduced to a single value.3. Snippets (Footprint Time Series): A series of intensitiesreflected from a beam‘s footprint on the seafloor, centered aroundeach bathymetric detection point. Snippets data packets containpertinent information such as time stamp, sequential ping number,sample rate, sound velocity and operator settings such as power,gain, absorption and range scale.

Image Source: QPS (not dated)

ACOUSTIC BACKSCATTER

SNIPPETSThe snippet records are typically the preferred backscatter productsfor seafloor classification, compared to the other backscatterproducts listed above. As the wavefront from the multibeam'stransmit array propagates through the water column and finallystrikes the seafloor, the multibeam first processes the bottomdetection information for the bathymetry. It then looks at thefragments of backscatter data, that surround the bottom detectioninformation, for each individual beam, their amplitude and theirreflectivity information. These 'fragments' of data are known assnippets. From this data, seafloor characterization and classificationof the substrate and geomorphology can be derived.

Indeed, the time-series intensities are directly co-registered with aportion of the bathymetric detection point and thus easier to correctfor slant-range. Likewise, the footprint time-series data provides fineracross-track resolution of the imagery than the other methods. Thus,each beam from a multibeam sonar’s ping provides not only abathymetric detection point of the seafloor but also a backscattersnippet record of the time-series of intensities for that beam. The twodata types are co-registered, i.e., geographically co-referenced,ensuring the backscatter snippet imagery will always be positionedaccurately on the seafloor. This positional accuracy is animprovement over traditional sidescan sonars.

Though sidescan sonar backscatter imagery is still widely regardedas an excellent tool for seafloor classification, the multibeam sonarprovides both bathymetry and accurately positioned backscatterimagery, making it a popular choice for seafloor classification.Furthermore, sidescan sonars are often towed in the water columnto acquire data at a specific angle from features on the seafloor.Towing the sonar not only reduces positioning accuracy but alsoproduces shadow zones (i.e., data holidays) from ensonifying theside of the seafloor feature. Multibeam backscatter, however, doesnot produce as many shadow zones, as the sonar transducer istypically mounted on the survey vessel on the surface of the water,ensonifying the seafloor features from a higher angle.

ACQUISITIONOnly relatively minor improvements can be made to backscatterquality during data processing; thus, the quality of the backscatter ismostly dictated by the quality of the vessel mobilization and thetechniques employed during data acquisition. It is important toemploy a high quality sonar with a proper motion sensor and install itproperly on the survey vessel. If the sonar will be mounted to anover-the-side pole, it is imperative that the pole is stable and robustenough to avoid any flexion in the pole mount that could de-couplethe motion of the sonar from the motion sensor. Likewise, theresearch team must accurately measure the equipment offsets andlever arms from the vessel’s center of motion during the mobilizationprocess. Furthermore, during vessel mobilization, the research teammust perform proper calibrations of all equipment, including acalibration of the best settings to optimize backscatter quality. Oncethese settings are determined, the research team should maintainthese settings with minimal changes.

Thus, during multibeam data acquisition, the following heuristicsshould be observed:

• Do not mix or change sonar frequencies from line to line. Thefrequency of a sonar affects the backscatter results, so the researchteam should choose the correct frequency for an area and maintainthat frequency throughout. In some situations, due to changes inwater depth across a survey area, the team may need to change thefrequency of the sonar. However, proper line planning mitigates theeffects of this change on the backscatter. (It can be useful forseafloor classification to intentionally acquire multibeam backscatterdata at three different sonar frequencies, such as 100-kHz, 200-kHz,and 400-kHz, to create a false color image of the variations inintensity returns. However, in this scenario, the different sonarfrequencies are pre-planned and acquired in an organized manner.)

• Do not mix Frequency Modulated (FM) pulse settings withContinuous Wave (CW) settings.

• Input realistic absorption parameters into the multibeam sonarduring acquisition (or at least overwrite the absorption value duringprocessing with a more accurate value – though it is preferred toenter the correct value during acquisition). In the past, it was astandard process in the industry to enter a default absorption valuein the sonar. However, it has been shown that a more accurateestimate of absorption improves the quality of the backscatter.

• Avoid saturation of the intensity returns. When the backscattervalues become saturated during acquisition from high power and/orgain settings, the system is no longer measuring the true echo level.Thus, the processing of the data over corrects for these power andgain settings, introducing artifacts into the mosaic. To avoid thisissue, monitor the real-time amplitude values during acquisition.

• Keep power, gain, and pulse length settings consistent. If a changeto sonar settings, such as gain, needs to be made, then the changeis made during a turn instead of the middle of a survey line.Similarly, the pulse width should remain consistent. (This heuristic isdependent on the model of the particular multibeam sonar.)

CORRECTING MBES BACKSCATTER DATA• The backscatter (snippet) signal received by the MBES system canbe influenced by various parameters, which can be categorized intosystem settings (power, gain, pulse length), acoustic propagationconditions (absorption and spreading loss), beam geometry (range,incident angle, foot print size) and seafloor properties (roughnessacoustic properties). It is important that the received backscattersignal is fully corrected so that it is invariant to system settings,propagation conditions and beam geometry so that changes in thebackscatter can be attributed to changes in the seafloor properties,and thus, be used to derive information about the substrate andgeomorphology of the seabed.

SEABED CLASSIFICATION METHODOLOGYFor seafloor classification, the multibeam bathymetry and snippetbackscatter maps are typically used in conjunction with seabedsamples as a means of ground-truthing the changes in intensitylevels displayed in the backscatter mosaic. Since the backscatterintensity from the seafloor varies with the angle of incidence of theacoustic signal at the seafloor at the time of data acquisition, astatistical normalization of the backscatter data is performed toproduce a proper backscatter mosaic. Otherwise, the variations inthe backscatter imagery may be due to factors other than changesto the bottom characteristics of the seafloor. Due to thisnormalization of the data, the intensity variations displayed in abackscatter mosaic are relative, providing the ability for qualitativeinterpretation. However, to correlate the intensity variations on abackscatter mosaic to quantitative levels, such as specific sedimentgrain sizes, researchers typically perform a series of sedimentsamples as a means of ground truthing. The required number andgeographic spacing/ pattern of sediment samples is traditionallydetermined after an initial review of the backscatter mosaic toensure areas of interest are sampled.

Once the multibeam backscatter is acquired and processed, theprocess for creating a seabed characterization map will involvecombining multibeam bathymetry, multibeam backscatter, sedimentgrab samples, sediment core samples, and any other availablerelevant data into a GIS software platform. Polygons, polylines, andpoints are typically created to delineate appropriate feature types.Using the variety of datasets, individual seabed characterizationscan be made corresponding to specific macro- or micro-habitatclassification descriptors, such as sand, unconsolidated sediment,coral, and rock. Colors are typically assigned to indicate thehardness or softness of the seabed as well as the general age.Often, these colors are modelled after standard geologic maps. Forexample, yellow or orange colors may represent geologicallyyounger sediments (10,000 years or younger) while darker colors,such as red and purple, indicate older sediment (older than 10,000years). Each type of bottom texture classified during the analysiscan include a number of attributes. Often, texture descriptions andcodes are attributed to the classifications, such as the Folk Sedimentclassification system.

The seabed classification process includes an analysis of multibeambathymetry grids at the highest resolution possible, includingartificially sun-illuminated relief images at varying angles andazimuths, slope-shaded relief models, and bathymetric contours atvarying intervals and depths. These datasets help define thegeologic features. The products derived from the surficial analysesof multibeam bathymetric datasets in a GIS will aid in theinterpretation of the seabed characterization map by revealingdiverse seafloor topography, enhancing areas varying in slope andproviding lines of constant depth. In a GIS, slope values may beassigned to areas of the seafloor with varying slopes. Likewise,seafloor features such as wavelengths and heights of sand wavefields or rocky outcrops can be measured. The morphology of aseafloor feature allows the interpreter to make a determination of thecharacterization for the feature such as sediment wave versus rockyoutcrop. Analysis of a sediment wave field also provides informationon the area itself and can be used as an indication of a dynamicwater environment.

Backscatter data is interpreted by analyzing areas of high and lowreflectivity, delineating fine-grained and coarse-grained sediments.The sediment grab and core samples are used to verifyinterpretations of the backscatter intensity. These data sets provideinformation regarding the location and extent of a variety ofgeological materials and textures, including rock and sand that lieabove the bedrock. Sediment sample data may also includebiogenic material, such as shells, indicating animal habitat on theseafloor.

All available data including multibeam bathymetry, multibeambackscatter, sediment grab and core samples, as well as theknowledge of the geologic history and physical oceanographicconditions of the region, will be used to make the characterizationfor the creation of a seabed classification map. Grain size analysisaids in this characterization when paired with the backscatter data,thus indicating fine- and coarse-grained sediment.

The beam pattern of a sonar is aradiometric distortion of thebackscatter resulting from uniqueanomalies in transmit power.Think of it as the sonar'ssignature on the backscatter. Ifwe can determine the pattern forour sonar's transducers, we cancorrect for this distortion. Mosthydrographic survey softwarepackages have the ability toanalysis and correction for beampattern distortions.

CONCLUSIONSeabed classification technology is advancing. There are newprocedures for measuring multibeam backscatter as a function oftrue angle of ensonification across the seafloor. This process canpotentially use backscatter measurements as a way to remotelycharacterize seafloor properties. Indeed, new developments in GISplatforms can aid in determining the changes of seafloor propertiesand provide a means to verify the seabed characterization map.

Wheeler North Reef – San Clemente, CA.Multibeam Bathymetry – Collected byCLE Engineering

MBES Backscatter Chart – Dark Areasare Reef, Lighter Areas are Sand

MBES Backscatter Chart – SeabedClassification