Department of Geodesy, Gdańsk University of Technology, Gabriela Narutowicza 11-12, 80-233 Gdańsk, Poland.
Marine Technology Ltd., Wiktora Roszczynialskiego 4-6, 81-521 Gdynia, Poland.
Sensors (Basel). 2023 Jun 4;23(11):5331. doi: 10.3390/s23115331.
Autonomous technologies are increasingly used in various areas of science. The use of unmanned vehicles for hydrographic surveys in shallow coastal areas requires accurate estimation of shoreline position. This is a nontrivial task, which can be performed using a wide range of sensors and methods. The aim of the publication is to review shoreline extraction methods based solely on data from aerial laser scanning (ALS). This narrative review discusses and critically analyses seven publications drawn up in the last ten years. The discussed papers employed nine different shoreline extraction methods based on aerial light detection and ranging (LiDAR) data. It should be noted that unambiguous evaluation of shoreline extraction methods is difficult or impossible. This is because not all of the methods reported achieved accuracy, the methods were assessed on different datasets, the measurements were conducted using different devices, the water areas differed in geometrical and optical properties, the shorelines had different geometries, and the extent of anthropogenic transformation. The methods proposed by the authors were compared with a wide range of reference methods.
自主技术越来越多地应用于科学的各个领域。在浅海沿海地区使用无人车进行水道测量需要准确估计海岸线的位置。这是一项艰巨的任务，可以使用各种传感器和方法来完成。本出版物的目的是回顾仅基于航空激光扫描（ALS）数据的海岸线提取方法。本叙述性评论讨论并批判性地分析了过去十年中编写的七篇出版物。所讨论的论文采用了基于航空光探测和测距（LiDAR）数据的九种不同的海岸线提取方法。值得注意的是，对海岸线提取方法的明确评估是困难的或不可能的。这是因为并非所有报告的方法都达到了精度，所使用的方法是在不同的数据集上进行评估的，测量是使用不同的设备进行的，水域在几何和光学特性上有所不同，海岸线的几何形状不同，以及人为改造的程度也不同。作者提出的方法与广泛的参考方法进行了比较。
