HYDRO 2016 Paper 3A2

Sediment classification from multibeam backscatter images using simple histogram analysis

Rozaimi Che Hasan, Mohd Razali Mahmud, Shahrin Amizul Shamsudin


The use of multibeam echo sounder (MBES) has provided an advantage to study how acoustic data can be used for sediment classification. In particular, the availability of backscatter intensity offers alternative method to study seafloor hardness and softness, as compared to side-scan sonar imagery. In many seabed mapping processes, many classification techniques can be used to produce sediment maps from backscatter images, ranges from a simple clustering to the tops machine learning approaches. In this study, the authors attempt to investigate how a simple data arrangement method can be applied for backscatter images from MBES using the histogram generated from the backscatter intensities. The idea is to test whether this simple data arrangement process can produce similar classes as compared to a sediment classification map. To achieve this, acoustic data from WASSP MBES (i.e. model WMB-3250) was used for this purpose, which was acquired at a small area in Pulau Agas, north-west of Peninsular Malaysia. First, the bathymetry was processed using Qinsy and Fledermaus software, and for backscatter author's Matlab code was used to extract the intensity values from the original raw data and rescaled them to 8-bit architecture (0-255). Secondly, "Reclassify" function in ArcGIS was used to reclassify the pixel intensities based on the shape of the histogram. A few data classify techniques in ArcMap were tested to produce classification maps such as using manual approach, equal interval, quantile method, natural breaks, geometrical interval and standard deviation. Classification maps derived from these methods were then validated with ground truth samples collected using underwater videos and grabs to assess their accuracies.

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