Sargassum beds play important ecological roles in coastal ecosystems. However, it is difficult to estimate the spatial distribution of their biomass, because traditional surveys require a great deal of time and work. In this study, we tried to estimate the distribution using an acoustic method. For this purpose, we measured the acoustic intensity per unit dry weight, and field surveys were conducted in the coastal waters (12 km²) of Kuruminose, Yamaguchi, Japan, in spring 2007, autumn 2007, and spring 2008. The acoustic data were geostatistically interpolated to estimate the distribution. Acoustic data were collected using a quantitative echosounder at 200 kHz. The acoustic intensity per unit dry weight was -19.9 dB/kg. Using the intensity, the estimated biomass of the Sargassum bed in spring 2007, autumn 2007, and spring 2008 were 466 t (2.18 km²), 59 t (1.05 km²) and 287 t (2.36 km²), respectively. A spatial characteristic of the distribution was that the Sargassum beds were distributed from 0 to 11 m in depth. In particular, Sargassum beds were most often distributed at a depth of around 5 m. Because the distribution and its characteristics were able to be estimated, it was suggested that the acoustic method is adequate for estimating the spatial distribution of the biomass of Sargassum beds.

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This paper presents a measurement method combining conventional and coherent Doppler sonar using an adaptive algorithm to reduce measurement error at a wide range of SNRs. In our previous paper, we proposed a combined method to provide accurate and precise velocity using a fixed range of ambiguity velocity. The combined method worked well at high SNRs, but at low SNRs it was not as accurate. In order to provide accurate velocity at a wide range of SNRs, an adaptive algorithm for the range of ambiguity velocity is proposed at navigators' request. The results of theoretical and numerical error analyses showed that the combined method using the adaptive algorithm provides accurate and precise velocities at a wide range of SNRs.

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