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Abstract ▼ AI-Helper

Recently many researches are carried out related to the coastal erosion from many points of view, and the monitoring for the changes in bathymetry in very shallow water regions becomes more important in the relevant researches. However, it is very difficult to perform the bathymetry survey in these ...

Recently many researches are carried out related to the coastal erosion from many points of view, and the monitoring for the changes in bathymetry in very shallow water regions becomes more important in the relevant researches. However, it is very difficult to perform the bathymetry survey in these areas by use of echo sounder which is the most popular device to obtain the bathymetric information due to too small clearance to use the sonar device. Therefore it might be good alternatives to survey the bathymetry by use of a set of water-level gauges and/or LiDAR instead. However, there are still several shortcomings associated with the discrete and limited number of measurement points in the case of water-level gauges and the high cost of LiDAR device. In this study, more economic and efficient bathymetry survey method is proposed based on Beer-Lambert law and artificial neural networks using an aerial image of a very shallow water region taken by drones equipped with a digital camera, and the applicability for this optic-based method is investigated through the bathymetry survey at HuJeong Beach in Korea.

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