Seabed Sediment Classification through Multispectral Backscatter Mosaic MBES and Angular Response Analysis

Khomsin, Mukhtasor, Suntoyo, Danar Guruh Pratomo


Classification of seabed sediments plays a significant role in managing coastal and marine areas. This study aims to classify seafloor sediments in shallow waters using a multispectral backscatter mosaic multibeam echo sounder (MBES) and angular response analysis (ARA), which is validated using in situ sediment data. This research was conducted in the coastal area of Gresik City, East Java, Indonesia, with a depth variation of 3.5–24.5 m. The data utilized consist of multifrequency MBES data collected on January 4, 2023, at frequencies of 400, 300, and 200 kHz. The backscatter data from each frequency is processed to become a backscatter mosaic and merged into a multispectral backscatter. Furthermore, the data were processed using the angular response analysis method to classify the seafloor sediments in the survey area. The classification results were tested using in situ sediment data from a van Veen grab sampler. Sample sediment results were classified based on grain size analysis using the sieving method to determine the sediment type. The results showed that the backscatter mosaic of each frequency and the backscatter multispectral mosaic did not differ visually. However, regarding the backscatter values, there is a difference of about ±1 dB between frequencies. The foreshore area (western part) and the area farthest from the foreshore (eastern part) show the hard layers identified by the light backscatter mosaic. The ARA classification results revealed six sediment classes in the survey area, which is different from the four types of sediment found in situ. Sediment classification using ARA demonstrated an accuracy rate of 51% for real sediment samples, with a kappa coefficient of 0.3, indicating a fair level of categorization. This implies that half of the expectation point rises to the real test point.


Keywords: seabed sediment, classification, backscatter, mosaic, multispectral backscatter, angular response analysis, overall accuracy, kappa coefficient.

Full Text:



MAXIM L. D. Nautical chart user's manual. 1st ed. National Oceanic and Atmospheric Administration, 1997.

FONSECA L., & CALDER B. Geocoder: an efficient backscatter map constructor. U.S. Hydrographic Conference, 2005.

ZHENG H. B., YAN P., CHEN J., and WANG Y. L. Seabed sediment classification in the northern South China Sea using inversion method. Applied Ocean Research, 2013, 39: 131-136.

COLBO K., ROSS T., BROWN C., and WEBER T. A review of oceanographic applications of water column data from multibeam echosounders. Estuarine, Coastal and Shelf Science, 2014, 145: 41-56.

CHE-HASAN R., IERODIACONOU D., LAURENSON L., and SCHIMEL A. Integrating Multibeam Backscatter Angular Response, Mosaic and Bathymetry Data for Benthic Habitat Mapping. PLoS ONE, 2014, 9(5): e97339.

LE BAS T. P., & HUVENNE V. A. I. Acquisition and processing of backscatter data for habitat mapping – Comparison of multibeam and sidescan systems. Applied Acoustics, 2009, 70: 1248–1257.

SAMSUDIN S. A., & HASAN R. C. Assessment of multibeam backscatter texture analysis for seafloor sediment classification. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, 42: 177-183.

BROWN C. J., BEAUDOIN J., BRISSETTE M., and GAZZOLA V. Setting the stage for multi-spectral acoustic backscatter research. Geological Survey of Canada, Open File, 2017, 8295: 41.

CLARKE J. E. H., DANFORTH B. W., and VALENTINE P. Areal seabed classification using backscatter angular response at 95 kHz. Proceedings of the Conference “High Frequency Acoustics in Shallow Water,” Lerici, 1997, pp. 243–250.

APPLIED PHYSICS LABORATORY. APL-UW High-Frequency Ocean Environmental Acoustic Models Handbook. Applied Physics Laboratory, University of Washington, Seattle, Washington, 1994.

WILSON M. F. J., O’CONNELL B., BROWN C., GUINAN J. C., and GREHAN A. J. Multiscale Terrain Analysis of Multibeam Bathymetry Data for Habitat Mapping on the Continental Slope. Marine Geodesy, 2007, 30(1-2): 3–35.

EDWARDS B. D., DARTNELL P., and CHEZAR H. Characterizing benthic substrates of Santa Monica Bay with seafloor photography and multibeam sonar imagery. Marine Environmental Research, 2003, 56: 47–66.

FONSECA L., & MAYER L. Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data. Marine Geophysical Research, 2007, 28: 119-126.

FONSECA L. E., & CALDER B. R. Clustering Acoustic Backscatter in the Angular Response Space. U.S. Hydrographic Conference, 2007, 384.

FARIHAH R. A., MANIK H. M., and HARSONO G. Measurement and Analysis of Acoustic Backscatter Using Multibeam Echosounder Technology for Sediment Classification of the Gulf of Palu. Jurnal Ilmu dan Teknologi Kelautan Tropis, 2020, 12(2): 437-453.

FAHRULIAN F., MANIK H. M., JAYA I., and UDREKH U. Angular Range Analysis (ARA) and K-Means Clustering of Multibeam Echosounder Data for Determining Sediment Type. ILMU KELAUTAN: Indonesian Journal of Marine Sciences, 2016, 21(4): 177-184.

PRATOMO D. G., KHOMSIN, CAHYADI M. N., AKBAR K., and APRILIA E. Analysis of Seafloor Sediment Distribution using Multibeam Backscatter Data. MATEC Web of Conferences, 2018, 177: 01026.

LAMARCHE G., & LURTON X. Recommendations for improved and coherent acquisition and processing of backscatter data from seafloor-mapping sonars. Marine Geophysical Research, 2018, 39(1): 5-22.

GAIDA T. C., ALI T. A. T., SNELLEN M., SIMKOOEI A. A., VAN DIJK T. A. G. P., and SIMONS D. G. A Multispectral Bayesian Classification Method for Increased Acoustic Discrimination of Seabed Sediments Using Multi-Frequency Multibeam Backscatter Data. Geosciences, 2018, 8(12): 455.

BROWN C. J., BEAUDOIN J., BRISSETTE M., and GAZZOLA V. Multispectral multibeam echo sounder backscatter as a tool for improved seafloor characterization. Geosciences, 2019, 9(3): 126.

R2SONIC. Multibeam Echosounder Specifications, 2020.

BRENNAN C. W. Multibeam Calibration: The Patch Test. R2Sonic, 2017.

INTERNATIONAL ATOMIC ENERGY AGENCY. Collection and Preparation of Bottom Sediment Samples for Analysis of Radionuclides and Trace Elements. IAEA, Vienna, 2003.

RETSCH. Sieve analysis: taking a close look at quality. An expert guide to particle size analysis. 2015.

FRANCE-LANORD C., SPIESS V., KLAUS A., ADHIKARI R. R., ADHIKARI S. K., BAHK J.-J., BAXTER A. T., CRUZ J. W., DAS S. K., DEKENS P., DULEBA W., FOX L. R., GALY A., GALY V., GE J., GLEASON J. D., GYAWALI B. R., HUYGHE P., JIA G., LANTZSCH H., MANOJ M. C., MARTOS MARTIN Y., MEYNADIER L., NAJMAN Y. M. R., NAKAJIMA A., PONTON C., REILLY B. T., ROGERS K. G., SAVIAN J. F., SCHWENK T., SELKIN P. A., WEBER M. E., WILLIAMS T., and YOSHIDA K. Site U1452. In: FRANCE-LANORD C., SPIESS V., KLAUS A., SCHWENK T., and THE EXPEDITION 354 SCIENTISTS. Bengal Fan. Proceedings of the International Ocean Discovery Program, 354. International Ocean Discovery Program, College Station, Texas, 2016.

LURTON X., & LAMARCHE G. (eds.) Backscatter Measurements by Seafloor‐Mapping Sonars: Guidelines and Recommendations, 2015.

COSTA B. Multispectral Acoustic Backscatter: How Useful Is It for Marine Habitat Mapping and Management? Journal of Coastal Research, 2019, 35(5): 1062–1079.

WANG J., LI G., KAN G., HOU Z., MENG X., LIU B., LIU C., and LEI S. High frequency dependence of sound speed and attenuation in coral sand sediments. Ocean Engineering, 2021, 234: 109215.

CUNNINGHAM M. More Than Just the Kappa Coefficient: A Program to Fully Characterize Inter-Rater Reliability between Two Raters. Proceedings of the SAS Global Forum, 2009.

LANDIS J. R., & KOCH G. G. The measurement of observer agreement for categorical data. Biometrics, 1977, 33: 159-174.


  • There are currently no refbacks.