underwater mapping_2020-2021

Underwater mapping 2020 - 2021

Authors: E. Nocerino, F. Menna, B. Chemisky, P. Drap Date of publication: 2020 Image mosaicing is a proper procedure to visualize large underwater mapped areas, often employed in conjunction with autonomous underwater vehicles (AUVs) and ROVs. In this work, the authors propose using a modified image mosaicing algorithm that coupled with image-based real- time navigation and mapping algorithms provides two visual navigation aids.

Authors: Agung Budi Cahyono, Andreas Catur Wibisono, Dian Saptarini, Rizki Indra Permadi, Yanto Budisusanto, Husnul Hidayat. Date of publication: 2020 Underwater photogrammetry is one of the latest trends in survey techniques in mapping coral reefs. The underwater photogrammetry technique uses a non-metric camera in the 3D reconstruction of coral reefs that will produce photo maps up to in 3D. This article explains the process of data acquisition to create coral reef photo maps.

Authors: Bashar Elnashef, Sagi Filin Date of publication: 2020 While accuracy, detail, and limited-time on-site make photogrammetry a valuable means for underwater mapping, establishing reference control networks in such settings is frequently difficult. In that respect, using the coplanarity constraint becomes a practical solution as it requires neither knowledge of object space coordinates nor setting a reference control network. Nevertheless, imaging in such domains is subjected to non-linear and depth-dependent distortions caused by refractive media that alter the standard single viewpoint geometry. Accordingly, the coplanarity relation, as formulated for the in-air case, does not hold in such an environment, and methods proposed thus far for geometrical modeling of its effect require knowledge of object-space quantities. In this paper, the authors propose a geometrically-driven approach that fulfills the coplanarity condition and requires no knowledge of object space data.

Authors: Raihanah Rusmadi, Rozaimi Che Hasan Date of publication: 2020 The objective of this study is to determine the accuracy of habitat maps derived using side-scan sonar data, Object- based Image Analysis (OBIA) and five different classifier algorithms; Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbour (k-NN), Decision Tree, and Bayes.

Authors: Vijaya Baskar Veeriayan, & V. Rajendran Date of publication: 2020 Underwater ambient noise is primarily background noise, which functions time, location, and depth. The background baseline of the noise in the ocean is represented by ambient noise generated from the ocean surface due to wind and rain. This understanding of ambient noise under various conditions will help to improve marine instruments' signal- to-noise ratio (SNR).

Authors: Bohan Liu, Zhaojun Liu, Shaojie Men, Yongfu Li, Zhongjun Ding, Jiahao He, and Zhigang Zhao. Date of publication: 2020 This paper discusses the concepts of underwater hyperspectral imaging (UHI) technology, covering imaging systems, and the correction methods of eliminating the water column’s influence. The current applications of UHI, such as deep-sea mineral exploration, benthic habitat mapping, and underwater archaeology, are highlighted to show the potential of this technology. This review provides an introduction and overview for those working in the field and offers a reference for those searching for literature on UHI technology.

Authors: Chloe A. Game, & Michael B. Thompson Date of publication: 2020 Imagery is a preferred tool for environmental surveys within marine environments, particularly in deeper waters, as it is non-destructive compared to traditional sampling methods. However, underwater illumination effects limit its use by causing extremely varied and inconsistent image quality. Therefore, it is often necessary to pre-process images to improve the visibility of image features and textures and standardize their appearance. Tone mapping is a simple and effective technique to enhance contrast and manipulate the brightness distributions of images.

Authors: B. Chemisky, E. Nocerino, F. Menna, M.M. Nawaf, P. Drap. Date of publication: 2021 This document describes a low-cost, multi-sensor, underwater survey solution for the identification, tracking, and 3D mapping of targets. The authors also focus on calibrating the sensors.

Authors: Qi Zhao, Zhichao Xin, Zhibin Yu, and Bing Zheng Date of publication: 2021 This document describes the development of an image-to- image framework for underwater image synthesis and depth map estimation in underwater conditions.

Authors: F Muhammad, Poerbandono, & H Sternberg Date of publication: 2021 This paper discusses the small-scale testing of a 3D underwater positioning task. The authors analyse the setting and performance of a standard web camera used for such a task while fully submerged.

25 - Algorithm of Dynamic Forming One Whole Raster Photo Map of the Seabed During its Shooting by an Autonomous Uninhabited Underwater Vehicle

Authors: A A Timoshenko, A V Zuev, & E S Mursalimov. Date of publication: 2021 The paper describes an algorithm developed for creating one whole raster photo map of the seabed from images obtained from vertically downward cameras of autonomous underwater vehicles (AUV) using tile graphics.

Authors: Chloe A. Game, Michael B. Thompson, and Graham D. Finlayson. Date of publication: 2021 Image enhancement is often used to alleviate the low contrast, blurring, and colour reduction effects common in underwater imagery. Tone Mapping is a technique that improves the quality of the image to a more desirable tonal distribution. This document discusses new algorithms that simplify manipulations and increase the conspicuousness of pictures based on this technology.

Authors: S. Raghuram, Sai Anoop Sadineni. Date of publication: 2021 This paper discusses techniques to produce perceivable maps of the shallow seabed using AUVs, the Scale- Invariant Feature Transform(SIFT) algorithm for collecting images' features, and the Brute-force matcher to match the pictures producing 2-dimensional rectangular maps by applying the proposed algorithm.

Authors: Kai Sun, Weicheng Cui, and Chi Chen Date of publication: 2021 This paper summarizes the ocean sensing technologies applied in some critical underwater scenarios, including geological surveys, navigation and communication, marine environmental parameters, and underwater inspections. To contain as many submersible-based sensors as possible, the authors make a trade-off on breadth and depth. To finish, they try to predict the development trend of underwater sensor technology based on the future ocean exploration requirements.

29 - Subtidal Natural Hard Substrate Quantitative Habitat Mapping: Interlinking Underwater Acoustics and Optical Imagery with Machine Learning

Authors: Giacomo Montereale Gavazzi, Danae Athena Kapasakali, Francis Kerchof, Samuel Deleu, Steven Degraer, & Vera Van Lancker. Date of publication: 2021 This document discusses new scientifically validated methodologies for the quantitative spatial demarcation of Subtidal Natural Hard Substrates (SNHS) occupancy by rich benthic communities using high-resolution Multibeam Echosounder (MBES) depth and backscatter data and derivates, underwater imagery (UI) by video drop-frame, and grab sediment samples, all acquired within Belgian offshore waters.

Authors: Daniele Ventura, Luca Castoro, Gianluca Mancini, Edoardo Casoli, Daniela Silvia Pace, Andrea Belluscio, Giandomenico Ardizzone. Date of publication: 2021 This article explains how, using structure from motion photogrammetric workflow, the authors produced high spatial resolution 2D raster maps and 3D outputs such as dense points clouds and textured meshes of an underwater seagrass restoration site.

Authors: Gideon Billings, Richard Camilli, & Matthew Johnson- Roberson. Date of publication: 2021 This paper presents a novel visual scene mapping method for Underwater Vehicle Manipulator Systems (UVMSs), with specific emphasis on robust mapping in natural seafloor environments.

Authors: Jarina Raihan, P.G. Emeroylariffion Abas, & Liyanage C. De Silva. Underwater images are very much different from images taken on land due to a higher disturbance ratio caused by the presence of a water medium between the camera and the target object. These distortions and noises result in unclear details and reduced output image quality. An underwater image restoration method is proposed in this paper, which uses blurriness information, background light neutralization information, and red-light intensity to estimate depth.

Authors: Zhengliang Hu, Jinxing Huang, Pan Xu, Mingxing Nan, Kang Lou, and Guangming Li. Fiber-optic hydrophones have received extensive research interest due to their advantage in ocean underwater target detection. This study introduces the kernel extreme learning machine (K-ELM) to source localization in underwater ocean waveguides. As a data-driven machine learning method, K-ELM does not need a prior environment information compared to the conventional method of match field processing. The acoustic source localization is considered a supervised classification problem, and the normalized sample covariance matrix formed over several snapshots is utilized as an input.

Authors: Tiago C. A. Oliveira, Ying-Tsong Lin, and Michael B. Porter. Three-dimensional (3D) effects can profoundly influence underwater sound propagation in shallow-water environments, affecting the underwater soundscape. Various geological features and coastal oceanographic processes can cause horizontal reflection, refraction, and diffraction of underwater sound. This study explores the ability of a parabolic equation (PE) model to simulate sound propagation in the highly complicated shallow water environment of Long Island Sound (United States east coast) is investigated.

Authors: Manish Mathnikar & Uday Patkar The system described provides information in three degrees of freedom motion capability while profiling the water column and includes large customizable data. This docking infrastructure enables long-term resident functionality of the system. Operational variables include ascent rate, descent rate, depth range, and profiling frequency.

Authors: Joonas Syrjälä, Risto Kalliola, and Jukka Pajala Shipping is the most pervasive source of anthropogenic underwater continuous noise and local intermittent noise. This study focused on the separation of anthropogenic intermittent noise from dynamic background noise in the Gulf of Finland using an adaptive threshold level (ATL) technique.

17 - The Utility of Satellites and Autonomous Remote Sensing Platforms for Monitoring Offshore Aquaculture Farms: A Case Study for Canopy Forming Kelps

Authors: Tom W. Bell, Nick J. Nidzieko, David A. Siegel, Robert J. Miller, Kyle C. Cavanaugh, Norman B. Nelson, Daniel C. Reed, Dmitry Fedorov, Christopher Moran, Jordan N. Snyder, Katherine C. Cavanaugh, Christie E. Yorke, and Maia Griffith This document evaluates the efficacy of remote sensing from satellites and aerial and underwater autonomous vehicles as potential monitoring platforms for offshore kelp aquaculture farms.

Authors: Qi Zhao, Ziqiang Zheng, Huimin Zeng, Zhibin Yu, Haiyong Zheng, and Bing Zheng Underwater environment complexity results that depth estimation in a data-driven manner is still a challenging task. To tackle this problem, The authors propose a system including two modules for underwater image synthesis and underwater depth map estimation.

Authors: Gillian S. L. Rowan, Margaret Kalacska, Deep Inamdar, J. Pablo Arroyo-Mora, and Raymond Soffer. Optical remote sensing has been suggested as a preferred method for monitoring submerged aquatic vegetation (SAV). However, due to the limited prior application of remote sensing to mapping freshwater vegetation, major foundational knowledge gaps remain, specifically in terms of the specificity of the targets and the scales at which they can be monitored.

Authors: Yuliang Li, Mingliang Chen, Yuliang qi, Jinquan qi, Chenjin Deng, Longkun Du, Zunwang Bo, Chang Han, Zhihua Mao, Yan He, Xuehui Shao, Shensheng Han Underwater ghost imaging is a technique that involves the use of light to capture images of objects in underwater environments. This paper discusses a theoretical and experimental study of underwater ghost imaging is carried out by combining the description of underwater optical field transmission with the inherent optical parameters of the water body.

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Authors: Xiyun Ge, Hongkun Zhou, Junbo Zhao, Xiaowei Li, Xinyu Liu, Jin Li, and Chengming Luo This paper proposes a novel method for enhancing underwater location accuracy by combining distributed estimation and particle swarm optimization to address substantial errors arising from uncertain underwater signals and sampling. It utilizes a unique technique to correct errors in underwater sound measurements caused by anomalous readings and missing data. The method also develops a way to estimate underwater positions in one go without constraints, based on how signals are mapped from arrays to responders.

Authors: Chun-Feng Chou, Cheng-Mu Tsai, Chao-Hsien Chen, Yung-Hao, Wong, Yi-Chin Fang, Chan-Chuan Wen, Hsiao- Yi Lee, Hien-Thanh Le, Shun-Hsyung Chang, and Hsing- Yuan Liao This text describes the development and advantages of a novel underwater camera designed for photogrammetry in various fields such as biology, archaeology, and industry. It explains the challenges of underwater photography due to different optical phenomena and how the new camera design addresses these issues, highlighting the use of prime and zoom lenses, the optimization for various water depths and spectra, and the application of a genetic algorithm to reduce chromatic aberration.

36 - A Multidisciplinary Approach for the Mapping, Automatic Detection and Morphometric Analysis of Ancient Submerged Coastal Installations: The Case Study of the Ancient Aegina Harbour Complex

Authors: Nikos Georgiou, Xenophon Dimas, Elias Fakiris, Dimitris Christodoulou, Maria Geraga, Despina Koutsoumpa, Kalliopi Baika, Pari Kalamara, George Ferentinos, and George Papatheodorou Giaco This study focuses on the documentation and analysis of underwater cultural heritage (UCH) at Aegina Island, Greece, to support sustainable maritime development by using a multidisciplinary, non-intrusive approach to gather detailed geomorphological and archaeological information. It highlights the methods used, such as marine geophysical mapping, seafloor segmentation, and photogrammetry, to document and analyze submerged structures.

38 - Autonomous navigation in unknown environment using sliding mode SLAM and genetic algorithm

Authors: Salvador Ortiz, Wen Yu In this paper, sliding mode control is combined with the classical simultaneous localization and mapping (SLAM) method. This combination can overcome the problem of bounded uncertainties in SLAM. With the help of genetic algorithm, our novel path planning method shows many advantages compared with other popular methods.

Authors: Joseph H. Tarnecki, William F. Patterson This article presents a novel method for retrieving subsea instruments using a commercially available mooring hook integrated with a mini remotely operated vehicle (ROV). This method effectively circumvents the limitations of diver retrieval and the expense of acoustic release technology. Tested in various marine environments, the method achieved a 100% success rate in retrieving equipment from depths ranging from 28 to 80 meters in the Gulf of Mexico, demonstrating its potential applicability for a variety of underwater recovery operations.

Authors: JungHwan Moon and Minwoo Jung This study presents a compact LiDAR sensor operating at 905 nm, designed for field deployment during oil spill incidents. A custom algorithm successfully distinguishes oil from seawater, and experiments demonstrate detection of three oil types (light crude, bunker A, bunker C) across volumes from 1 to 50 mL. The sensor reliably identified oil coverage (exceeding 50% of the detected area) and reflected viscosity differences—e.g., bunker C’s high viscosity (~73%). Oil films were predominantly 1–2 mm thick, confirming expected geometric behavior. Future work should quantify oil slick thickness accuracy and validate system performance in real-world pollution scenarios.

Authors: César Debeunne, and Damien Vivet Autonomous navigation relies on precise and robust mapping and localization, where Simultaneous Localization and Mapping (SLAM) is a key solution. While visual and visual-IMU SLAM are well-developed, LiDAR- SLAM methods have seen little advancement in recent decades. Research on vision-LiDAR fusion remains limited despite its potential benefits, such as improved performance in challenging conditions like aggressive motion, low light, or sparse visual features. This study surveys visual-LiDAR SLAM, reviewing foundational concepts, state-of-the-art advancements, and fusion-based approaches.

Authors: Simon Collings, Tara J. Martin, Emili Hernandez, Stuart Edwards, Andrew Filisetti, Gavin Catt, Andreas Marouchos, Matt Boyd, and Carl Embry Underwater LiDAR, traditionally used in the oil and gas industry for precise seabed measurements, was tested on a moving platform alongside a multibeam echosounder (MBES) at Kingston Reef, Australia. The study compared their accuracy and potential synergies for benthic habitat mapping and underwater SLAM for AUVs. Results showed that LiDAR reflectivity and MBES backscatter complement each other in habitat discrimination. While SLAM aids navigation with both technologies, it significantly improves LiDAR data consistency even when GNSS is available, unlike multibeam data.

Authors: Huu Thu Nguyen, Eon-Ho Lee,, Chul Hee Bae, and Sejin Lee Multiple object detection is challenging yet crucial in computer vision, particularly due to noise effects. This study applies K-Means and DBSCAN clustering algorithms to deep learning outputs from underwater sonar images and 3D LiDAR point clouds to remove outliers, cluster meaningful data, and improve detection performance. Results highlight potential applications in object detection, autonomous driving systems, and related fields.

Author: Pawel Tysiac This study evaluates an airborne bathymetric LiDAR system for coastal monitoring in the Baltic Sea, addressing ongoing erosion despite existing surveillance. It innovatively integrates topographic and bathymetric data—rarely combined in geotechnical analyses—to assess erosion drivers, including underwater geomorphological changes. To overcome LiDAR limitations in shallow water, the CANUPO point cloud classification method was applied. The research represents the first interdisciplinary approach merging geotechnical computations with remote sensing for coastal hazard assessment, enhancing understanding of climate- and human-induced environmental processes.

Authors: Chang Yuan, Shusheng Bi, Jun Cheng, Dongsheng Yang, and Wei Wang This paper addresses the significant error in 3D point clouds generated by rotating 2D lidars due to misalignment with the motor's rotation. Existing methods require expensive angular sensors for synchronization. The proposed low-cost calibration method eliminates this error without sensors. It first optimizes the lidar-motor sequence to correct shape errors, then uses a triangular plate to eliminate attitude errors. Finally, the Levenberg-Marquardt method calibrates the plate's installation. Experimental results show this method ensures accuracy for 3D mapping in indoor autonomous mobile robots, even with a standard lidar, while significantly reducing costs.

Authors: Young-Hyun Lee, Jin-Hoo Kim, Sang-Hee Lee, and Sung-Bo Kim Visual identification via diving is the most effective method for surveying underwater archaeological sites, but it is hindered by turbid water, high costs, and time constraints. This study utilized acoustic geophysical survey equipment at three South Korean sites to improve underwater imaging. Scanning sonar proved most effective, outperforming side scan sonar and multibeam echo sounder. Further refinements confirmed that scanning sonar generates more accurate images than on-site drawings in turbid conditions. Combined with high- frequency geophysical techniques, it enhances the reliability of detecting buried underwater remains and relics.

Authors: Aurora Maccarone, Giulia Acconcia, Ulrich Steinlehner, Ivan Labanca, Darryl Newborough, Ivan Rech, and Gerald S. Buller An optical depth imaging system designed for underwater environments uses time-correlated single-photon counting (TCSPC) and time-of-flight techniques to generate depth profiles. The system employs a linear array of optimized single-photon avalanche diode (SPAD) detectors, a 670 nm pulsed laser source, and cylindrical lenses for light collection. Laboratory experiments achieved single-photon depth imaging at 1.65 m range under highly scattering conditions (8.3 attenuation lengths) with 15 mW optical power, with depth and spatial resolution evaluated across varying scattering scenarios.