Akademik Veri Yönetim Sistemi
FRESENIUS ENVIRONMENTAL BULLETIN, cilt.27, sa.4, ss.2555-2561, 2018 (SCI-Expanded)
The presence of life on the sea bed causes significant problems during acoustic post-processing, including spurious targets, background noise, artificially generated noise, reverberations, dead zones, interference, "lost" bottoms, and spurious strong and weak scatterers. In particular, the problem of "lost" bottoms in stock assessments creates challenges when attempting to recover bottom echoes. In some cases, commercial software and computer scripts are required to manually recover "lost" bottoms; however, this can be time-consuming due the sheer volume of acoustic data involved. In this paper, we propose three new algorithms to estimate the biomass of Posidonia oceanica seagrass. The first algorithm includes autonomous "lost" bottom and dead zone detection (referred to as ABDEZD) and autonomous real bottom estimation (referred to as ARBE). The second algorithm removes spurious targets as well as artificial and background noise. By considering the noise sources, we developed an algorithm to remove spurious noise and echoes, and estimate the absolute biomass of the seagrass without interference from other acoustic scatters. The third algorithm consists of an acoustic biomass estimator of macro seagrass (referred to as ABEMSI) and a script called "Sheat-Finder", which acoustically detects sheats, which are the vertical rhizomes of Posidonia seagrass.