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Keywords = AUV-based multibeam bathymetry

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19 pages, 35252 KiB  
Article
Erosional and Depositional Features along the Axis of a Canyon in the Northern South China Sea and Their Implications: Insights from High-Resolution AUV-Based Geophysical Data
by Xishuang Li, Lejun Liu, Bigui Huang, Qingjie Zhou and Chengyi Zhang
J. Mar. Sci. Eng. 2024, 12(4), 599; https://doi.org/10.3390/jmse12040599 - 30 Mar 2024
Viewed by 1480
Abstract
Autonomous Underwater Vehicle (AUV)-based multibeam bathymetry, sub-bottom profiles, and side-scan sonar images were collected in 2009 and 2010 to map the geomorphic features along the axial zone of a canyon (referred to as C4) within the canyon system developed on the northern slope [...] Read more.
Autonomous Underwater Vehicle (AUV)-based multibeam bathymetry, sub-bottom profiles, and side-scan sonar images were collected in 2009 and 2010 to map the geomorphic features along the axial zone of a canyon (referred to as C4) within the canyon system developed on the northern slope of the South China Sea. These data significantly improved the spatial resolution of acoustic data, leading to a better understanding of the sedimentary processes within the modern canyon system. The bathymetric data reveal that sections across the canyon axis exhibit either asymmetrical or symmetrical characteristics, which differ from the overall asymmetrical pattern of the entire canyon. This suggests that the overall asymmetrical pattern of the canyon is not primarily due to axial incision. Various morphological elements were identified along the canyon axis, including failure scars, undulating features, knickpoints, flat terraces, furrows, and mass transport deposits (MTDs). Landslides, predominantly located in the upper canyon, were formed after at least 5000 years BP. Between the beginning of the canyon and a water depth of approximately 1300 m, there are alternating flat terraces and knickpoints. The large knickpoints’ low slope gradients are likely formed by the presence of undulating features. The internal configurations of undulating features suggest that they are depositional structures rather than sediment deformation. The formation of small-scale furrows below a depth of 1200 m may be associated with occasional gravity flows down the canyon. It is suggested that the canyon was generally inactive during the Holocene but experienced sporadic processes of sediment erosion, transport, and re-deposition in the axial zone that were triggered by landslide events occasionally in the upper canyon. Full article
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19 pages, 14876 KiB  
Article
A Storage-Saving Quadtree-Based Multibeam Bathymetry Map Representation Method
by Zheng Cong, Teng Ma, Ye Li, Mingxiao Yuan, Yu Ling, Haohan Du, Chi Qi, Ziyuan Li, Shuo Xu and Qiang Zhang
J. Mar. Sci. Eng. 2023, 11(4), 709; https://doi.org/10.3390/jmse11040709 - 25 Mar 2023
Cited by 6 | Viewed by 2472
Abstract
With the rapid advancement of the simultaneous localization and mapping (SLAM) technology, the collaboration of several autonomous underwater vehicles (AUVs) in large-scale seafloor imaging has become a trending topic. Electromagnetic waves are difficult to transfer underwater, the only viable method of communication is [...] Read more.
With the rapid advancement of the simultaneous localization and mapping (SLAM) technology, the collaboration of several autonomous underwater vehicles (AUVs) in large-scale seafloor imaging has become a trending topic. Electromagnetic waves are difficult to transfer underwater, the only viable method of communication is acoustic transmission, but its bandwidth is limited. Therefore, how to compress and process multibeam bathymetry maps so that AUVs can acquire maps gathered by other AUVs has become an important topic of study. This study presents a representation approach for multibeam bathymetry maps based on a quadtree structure. In comparison to the girding approach, the sparse pseudo-input Gaussian processes (SPGPs) method, and the octree-based method, the quadtree-based method suggested in this study preserves precision while compressing storage space. Experiments utilizing field data validate the performance of the proposed technique, and the method’s ability to compress storage space towards an AUV cooperative SLAM’s scenario. Full article
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24 pages, 9471 KiB  
Article
Sidescan Only Neural Bathymetry from Large-Scale Survey
by Yiping Xie, Nils Bore and John Folkesson
Sensors 2022, 22(14), 5092; https://doi.org/10.3390/s22145092 - 6 Jul 2022
Cited by 8 | Viewed by 3013
Abstract
Sidescan sonar is a small and low-cost sensor that can be mounted on most unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs). It has the advantages of high resolution and wide coverage, which could be valuable in providing an efficient and cost-effective [...] Read more.
Sidescan sonar is a small and low-cost sensor that can be mounted on most unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs). It has the advantages of high resolution and wide coverage, which could be valuable in providing an efficient and cost-effective solution for obtaining the bathymetry when bathymetric data are unavailable. This work proposes a method of reconstructing bathymetry using only sidescan data from large-scale surveys by formulating the problem as a global optimization, where a Sinusoidal Representation Network (SIREN) is used to represent the bathymetry and the albedo and the beam profile are jointly estimated based on a Lambertian scattering model. The assessment of the proposed method is conducted by comparing the reconstructed bathymetry with the bathymetric data collected with a high-resolution multi-beam echo sounder (MBES). An error of 20 cm on the bathymetry is achieved from a large-scale survey. The proposed method proved to be an effective way to reconstruct bathymetry from sidescan sonar data when high-accuracy positioning is available. This could be of great use for applications such as surface vehicles with Global Navigation Satellite System (GNSS) to obtain high-quality bathymetry in shallow water or small autonomous underwater vehicles (AUVs) if simultaneous localization and mapping (SLAM) can be applied to correct the navigation estimate. Full article
(This article belongs to the Special Issue Underwater Robotics in 2022-2023)
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19 pages, 1745 KiB  
Article
A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning
by Ivana Golub Medvešek, Igor Vujović, Joško Šoda and Maja Krčum
Appl. Sci. 2021, 11(11), 4966; https://doi.org/10.3390/app11114966 - 28 May 2021
Cited by 3 | Viewed by 4958
Abstract
Hydrographic survey or seabed mapping plays an important role in achieving better maritime safety, especially in coastal waters. Due to advances in survey technologies, it becomes important to choose well-suited technology for a specific area. Moreover, various technologies have various ranges of equipment [...] Read more.
Hydrographic survey or seabed mapping plays an important role in achieving better maritime safety, especially in coastal waters. Due to advances in survey technologies, it becomes important to choose well-suited technology for a specific area. Moreover, various technologies have various ranges of equipment and manufacturers, as well as characteristics. Therefore, in this paper, a novel method of a hydrographic survey, i.e., identifying the appropriate technology, has been developed. The method is based on a reduced elimination matrix, decision tree supervised learning, and multicriteria decision methods. The available technologies were: remotely operated underwater vehicle (ROV), unmanned aerial vehicle (UAV), light detection and ranging (LIDAR), autonomous underwater vehicle (AUV), satellite-derived bathymetry (SDB), and multibeam echosounder (MBES), and they are applied as a case study of Kaštela Bay. Results show, considering the specifics of the survey area, that UAV is the best-suited technology to be used for a hydrographic survey. However, some other technologies, such as SDB come close and can be considered an alternative for hydrographic surveys. Full article
(This article belongs to the Section Marine Science and Engineering)
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