Utilization of Airborne Topo-Bathymetric LiDAR Technology for Coastline Determination in Western Part of Java Island

Soeksmantono, Budhy; Utama, Y. Prita; Syaifudin, Firman

doi:10.1088/1755-1315/925/1/012065

Cited by 2 publications

(1 citation statement)

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“…The airborne laser bathymetry (ALB) method can also be used for auto-classification and mapping of the seafloor based on machine learning classifiers [ 20 ]. The use of LiDAR for acquiring bathymetry is also presented in [ 21 , 22 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Methodology for Creating a Digital Bathymetric Model Using Neural Networks for Combined Hydroacoustic and Photogrammetric Data in Shallow Water Areas

Łącka,

Łubczonek

2023

Sensors

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This study uses a neural network to propose a methodology for creating digital bathymetric models for shallow water areas that are partially covered by a mix of hydroacoustic and photogrammetric data. A key challenge of this approach is the preparation of the training dataset from such data. Focusing on cases in which the training dataset covers only part of the measured depths, the approach employs generalized linear regression for data optimization followed by multilayer perceptron neural networks for bathymetric model creation. The research assessed the impact of data reduction, outlier elimination, and regression surface-based filtering on neural network learning. The average values of the root mean square (RMS) error were successively obtained for the studied nearshore, middle, and deep water areas, which were 0.12 m, 0.03 m, and 0.06 m, respectively; moreover, the values of the mean absolute error (MAE) were 0.11 m, 0.02 m, and 0.04 m, respectively. Following detailed quantitative and qualitative error analyses, the results indicate variable accuracy across different study areas. Nonetheless, the methodology demonstrated effectiveness in depth calculations for water bodies, although it faces challenges with respect to accuracy, especially in preserving nearshore values in shallow areas.

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Section: Introductionmentioning

confidence: 99%

Methodology for Creating a Digital Bathymetric Model Using Neural Networks for Combined Hydroacoustic and Photogrammetric Data in Shallow Water Areas

Łącka,

Łubczonek

2023

Sensors

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Application of Filtering Techniques to Smooth a Surface of Hybrid Digital Bathymetric Model

Lubczonek,

Zaniewicz

2023

Remote Sensing

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The aim of the research is to identify the optimal method for smoothing the surface of a hybrid digital bathymetric model (HDBM). The initiation of this research is justified by the fact that a model created from diverse types of data may have different surface textures and outliers. This diversity may cause problems in subsequent data processing stages, such as generating depth contours. As part of the adopted research methodology, fifteen filters were analysed. Filtering techniques were examined for filter type, the number of iterations, weights, and window size. The result is the adopted research methodology, which enabled the selection of the optimal filtering method. The research undertaken in this work is an extension of the methodology for developing an HDBM. An important aspect of the research is the approach to elaborating on such kinds of models in shallow and ultra-shallow waters adjacent to the land, as well as the use of data obtained by modern measurement platforms, such as unmanned surface vehicles (USV) and unmanned aerial vehicles (UAV). The studies fit into the general context of works related to the development of this type of model and undoubtedly provide a solid reference for further development or improvement of similar methods.

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Utilization of Airborne Topo-Bathymetric LiDAR Technology for Coastline Determination in Western Part of Java Island

Cited by 2 publications

References 1 publication

Methodology for Creating a Digital Bathymetric Model Using Neural Networks for Combined Hydroacoustic and Photogrammetric Data in Shallow Water Areas

Methodology for Creating a Digital Bathymetric Model Using Neural Networks for Combined Hydroacoustic and Photogrammetric Data in Shallow Water Areas

Application of Filtering Techniques to Smooth a Surface of Hybrid Digital Bathymetric Model

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