A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry

Full-waveform airborne LiDAR bathymetry (ALB) technology, in which the analyzed waveforms reflect the temporal positions and attribute information of targets, is effective in shallow water. However, weak seafloor echoes in full-waveform data induced by environmental and device characteristics are co...

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Published in:International Journal of Applied Earth Observations and Geoinformation
Main Authors: Yadong Guo, Wenxue Xu, Yanxiong Liu, Fanlin Yang, Xue Ji, Yikai Feng, Qiuhua Tang
Format: Article
Language:English
Published: Elsevier 2025-09-01
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843225004455
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author Yadong Guo
Wenxue Xu
Yanxiong Liu
Fanlin Yang
Xue Ji
Yikai Feng
Qiuhua Tang
author_facet Yadong Guo
Wenxue Xu
Yanxiong Liu
Fanlin Yang
Xue Ji
Yikai Feng
Qiuhua Tang
author_sort Yadong Guo
collection DOAJ
container_title International Journal of Applied Earth Observations and Geoinformation
description Full-waveform airborne LiDAR bathymetry (ALB) technology, in which the analyzed waveforms reflect the temporal positions and attribute information of targets, is effective in shallow water. However, weak seafloor echoes in full-waveform data induced by environmental and device characteristics are confused with noise signals, leading to difficulties in seafloor detection. This paper proposes a pregeneration–recognition method of detecting weak seafloor echoes for ALB. First, a two-stage local maximum algorithm is developed to identify potential seafloor echoes in waveforms and to pregenerate points. Then, an adaptive ellipsoidal neighborhood related to the point density is used to select neighborhood points, and eigenvalue-based spatial features are calculated. Finally, a back propagation neural network (BPNN) model is constructed using the points generated from surface–seafloor shots, and the seafloor points in seafloor-undefined shots are obtained by optimizing the BPNN results. The proposed method is verified on four swaths collected via the Optech Aquarius ALB system near Wuzhizhou Island and Ganquan Island in the South China Sea. The numbers of additional points detected with the proposed method near these two islands increase by 195.9 % and 40.1 % compared with the Aquarius system, which is better than the Richardson–Lucy deconvolution method. The coverages and maximum depth of seafloor points are improved and the accuracy evaluations demonstrate the credibility of the results. Therefore, the proposed pregeneration–recognition method can effectively improve the detection rate for weak seafloor echoes and the depth performance of ALB systems. Future research will focus on mitigating the impact of seafloor topography on the proposed method to expand its application scenarios.
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spelling doaj-art-e43ac17043384ed7bb759feded1809372025-09-22T04:38:39ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-09-0114310479810.1016/j.jag.2025.104798A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetryYadong Guo0Wenxue Xu1Yanxiong Liu2Fanlin Yang3Xue Ji4Yikai Feng5Qiuhua Tang6College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China; Center for Marine Surveying and Mapping Research, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, ChinaCenter for Marine Surveying and Mapping Research, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, China; Corresponding author at: Center for Marine Surveying and Mapping Research, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China.Center for Marine Surveying and Mapping Research, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China; Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, ChinaCollege of Geoexploration Science and Technology, Jilin University, Changchun 130026, ChinaCenter for Marine Surveying and Mapping Research, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, ChinaCenter for Marine Surveying and Mapping Research, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, ChinaFull-waveform airborne LiDAR bathymetry (ALB) technology, in which the analyzed waveforms reflect the temporal positions and attribute information of targets, is effective in shallow water. However, weak seafloor echoes in full-waveform data induced by environmental and device characteristics are confused with noise signals, leading to difficulties in seafloor detection. This paper proposes a pregeneration–recognition method of detecting weak seafloor echoes for ALB. First, a two-stage local maximum algorithm is developed to identify potential seafloor echoes in waveforms and to pregenerate points. Then, an adaptive ellipsoidal neighborhood related to the point density is used to select neighborhood points, and eigenvalue-based spatial features are calculated. Finally, a back propagation neural network (BPNN) model is constructed using the points generated from surface–seafloor shots, and the seafloor points in seafloor-undefined shots are obtained by optimizing the BPNN results. The proposed method is verified on four swaths collected via the Optech Aquarius ALB system near Wuzhizhou Island and Ganquan Island in the South China Sea. The numbers of additional points detected with the proposed method near these two islands increase by 195.9 % and 40.1 % compared with the Aquarius system, which is better than the Richardson–Lucy deconvolution method. The coverages and maximum depth of seafloor points are improved and the accuracy evaluations demonstrate the credibility of the results. Therefore, the proposed pregeneration–recognition method can effectively improve the detection rate for weak seafloor echoes and the depth performance of ALB systems. Future research will focus on mitigating the impact of seafloor topography on the proposed method to expand its application scenarios.http://www.sciencedirect.com/science/article/pii/S1569843225004455Airborne LiDAR bathymetry (ALB)Weak seafloor echo detectionPregeneration–recognitionTwo-stage local maximumBackpropagation neural network (BPNN)
spellingShingle Yadong Guo
Wenxue Xu
Yanxiong Liu
Fanlin Yang
Xue Ji
Yikai Feng
Qiuhua Tang
A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry
Airborne LiDAR bathymetry (ALB)
Weak seafloor echo detection
Pregeneration–recognition
Two-stage local maximum
Backpropagation neural network (BPNN)
title A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry
title_full A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry
title_fullStr A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry
title_full_unstemmed A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry
title_short A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry
title_sort pregeneration recognition method of detecting weak seafloor echoes for full waveform airborne lidar bathymetry
topic Airborne LiDAR bathymetry (ALB)
Weak seafloor echo detection
Pregeneration–recognition
Two-stage local maximum
Backpropagation neural network (BPNN)
url http://www.sciencedirect.com/science/article/pii/S1569843225004455
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