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LASER scanners and LiDARs for underwater operations: A resource guide (Page 2 of 3)

Bibliography

Authors: Thomas Scholz, Martin Laurenzis and Frank ChristnacherSiermontowski, This article discusses the evolution of underwater laser- based imaging systems and data-processing techniques, focusing on civil and naval applications in underwater laser scanning (ULS) and laser gated viewing (LGV). It emphasizes the importance of environmental conditions, such as local and seasonal turbidity, and presents advanced techniques for 3D laser oblique scanning (LOS) and contrast enhancements for gated viewing based on tank and sea experiments.

01 - Laser-based imaging applications in turbid waters

Authors: Miquel Massot-Campos, and Gabriel Oliver- Codina This paper presents a survey on optical sensors and methods for 3D reconstruction in underwater environments. The techniques to obtain range data have been listed and explained, together with the different sensor hardware that makes them possible. The literature has been reviewed, and a classifcation has been proposed for the existing solutions. New developments, commercial solutions and previous reviews in this topic have also been gathered and considered.

Authors: Ricard Campos, Rafael Garcia This paper compares airborne lidar and underwater glider estimates of optical backscattering from ocean particles, both offering denser sampling than ship surveys. A moderate correlation (R = 0.28) was found, with discrepancies attributed to sampling mismatches, particle composition variability, and lidar errors. Two scattering regimes were identified: below 0.001 m-¹, lidar values were typically higher than glider values, while above this threshold, lidar values were generally lower. Despite differences, the findings indicate that airborne lidar and gliders provide comparable and complementary data on optical particulate backscattering.

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.

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: Dandi Wang, Shuai Xing, Yan He, Jiayong Yu, Qing Xu, and Pengcheng This study introduces and evaluates a lightweight, dual- wavelength UAV-mounted airborne LiDAR bathymetry (ALB) system for shallow water mapping, tested at Dazhou Island, China. Using water surface points (fitted planes) and multibeam echosounder data as references, the system achieves decimeter-level precision: 0.1227 m for water surface fitting and 0.1268 m absolute bottom accuracy. It successfully identifies a 1m cube and resolves the rough shape of a 2 m cube on the seafloor at 12 m depth, demonstrating strong potential for flexible, high- resolution shallow-water mapping and underwater object detection.

Authors: Hongbo Yang, Zhizun Xu, and Baozhu Jia Underwater positioning is challenging due to electromagnetic wave attenuation, environmental disturbances, and terrain complexity. Acoustic methods suffer from low update rates, poor resolution, and noise sensitivity, while vision-based approaches struggle with sparse features, variable lighting, and light scattering. To address these issues, this paper proposes a novel visual- inertial-LiDAR system: a LiDAR camera provides robust depth maps via laser scanning, and an inertial measurement unit (IMU) supplies altitude data. Sensor fusion enables UUV position prediction, refined further using Bundle Adjustment to optimize rotation and translation estimates.

Authors: Gang Yang, Zhaoshuo Tian, Zongjie Bi, Zihao Cui, and Qingcao Liu In underwater LiDAR imaging, the conventional constant threshold adjacent frame difference (AFD) method loses target distance information due to the Gaussian distribution of laser light intensity, causing inhomogeneous intensity in images acquired by intensity charge-coupled devices (ICCD). To address this, the paper proposes the novel dynamic threshold adjacent frame difference (DTAFD) method, which adjusts the intensity threshold according to pixel intensities across different parts of a single frame ICCD image.

12 - LiDAR Intensity Completion: Fully Exploiting the Message from LiDAR Sensors

Authors: Weichen Dai, Shenzhou Chen, Zhaoyang Huang, Yan Xu, and Da Kong LiDAR sensors provide illumination-robust depth and intensity data via pulsed lasers, but their sparse, non- camera-like intensity maps are underutilized. This work introduces LiDAR-Net, an end-to-end CNN that jointly completes sparse intensity and depth maps by leveraging their correlation. A novel intensity fusion method generates ground truth for training. Experiments show intensity–depth fusion improves completion performance, and downstream lane segmentation on completed intensity maps retains ambient-light robustness, enabling broader real-world LiDAR applications.

Authors: Guoqing Zhou, Xiang Zhou, Weihao Li, Dawei Zhao, Bo Song, Chao Xu, Haotian Zhang, Zhexian Liu, Jiasheng Xu, Gangchao Lin, Ronghua Deng, Haocheng Hu, Yizhi Tan, Jinchun Lin, Jiazhi Yang, Xueqin Nong, Chenyang Li, Yiqiang Zhao, Cheng Wang, Lieping Zhang, & Liping Zou This study introduces a lightweight bathymetry LiDAR prototype mounted on an unmanned shipborne vehicle to overcome limitations of traditional airborne LiDAR in narrow urban rivers and mountainous areas. The system includes key modules like emitting/receiving optics, control, and high-speed data processing.

Authors: Bin Hu, Yiqiang Zhao, Guoqing Zhou, Jiaji He, Changlong Liu,, Qiang Liu, Mao Ye, and Yao Li Underwater laser detection is hindered by light attenuation from scattering and absorption in water. This study designs an underwater Lidar system using a paraxial multi-channel detection strategy to improve dynamic range in subsea environments. A multi-channel underwater Lidar simulation (MULS) method based on radiative transfer Lidar equations was developed and validated through experiments under varied water conditions. The prototype achieved range accuracy better than 0.1085 m, with strong correlations between simulated and measured waveforms, confirming the simulation method's reliability.

15 - Simulation and Design of an Underwater LiDAR System Using Non-Coaxial Optics and Multiple Detection Channels

Authors: Yongqiang Chen, Shouchuan Guo, Yan He, Yuan Luo, Weibiao Chen, Shanjiang Hu, Yifan Huang, Chunhe Hou, and Sheng Su Underwater laser detection is hindered by light attenuation from scattering and absorption in water. This study introduces an underwater Lidar system using a paraxial multi-channel detection strategy to improve dynamic range in subsea environments. A multi-channel underwater Lidar simulation (MULS) method, based on radiative transfer Lidar equations, was developed and validated through experiments under varied water conditions. The prototype achieved range accuracy better than 0.1085 m per channel, with strong agreement between simulated and measured waveforms, confirming the simulation's reliability.

Author: Guangbo Xu Underwater LiDAR performance is hindered by laser attenuation and backscattering from suspended particles. To overcome these limitations, this paper presents a high- speed signal processing system for underwater LiDAR utilizing complete waveform sampling. The system features a photodiode preamplifier and a 2 GHz sampling frequency main control board, enabling a ranging accuracy of 0.075 m and backscatter filtering. This work offers a valuable reference for underwater LiDAR signal processing system design.

Authors: Xudong Liu, Liping Zhang, Xiaoyu Zhai, Liye Li, Qingji Zhou, Xue Chen, and Xiaobo Li Polarization lidar (P-lidar) advances traditional lidar by incorporating polarization properties (degree, angle, ellipticity) alongside backscattering intensity and spectrum. This expands detected physical information, enhancing analysis for atmospheric, oceanic, and terrestrial remote sensing. This review introduces P-lidar principles and systems, surveys its applications across these domains, and proposes future research directions to stimulate further development.

18 - Handheld liDAR as a tool for characterizing wood-rich river Corridors - Published by Wiley

Authors: Anna Marshall, Ryan R. Morrison, Brady Jones, Shayla Triantafillou, Ellen Wohl Wood accumulations significantly affect geomorphic, hydraulic, and ecological processes in river corridors, yet accurately characterizing them remains challenging. This study assesses the effectiveness of handheld lidar scanners, specifically the fourth-generation iPad Pro, in collecting 3D wood accumulation data for measuring volume, porosity, complexity, and roughness. Findings indicate that handheld lidar offers a cost-effective alternative to traditional field methods by providing user- friendly data collection and visualization, enabling accurate temporal volume comparisons, aiding porosity measurements, and supporting hydraulic and morphodynamic modeling.

19 - Design of Scanning Units for the Underwater Circumferential- Scanning LiDAR Based on Pyramidal-Shaped Refl ectors and a Rapid Detection Method for Target Orientation

Authors: Bingting Zha, Guangbo Xu, Zhuo Chen, Yayun Tan, Jianxin Qin, and He Zhang Traditional underwater LiDAR faces challenges balancing detection range and sealing. This paper proposes a solution using a pyramidal-shaped reflector in a new scanning unit, alongside a magneto–electric detection module with Hall switches and magnetic rings for precise target orientation. A rapid FPGA-based orientation coding method achieves a 20 ns delay and 15° resolution. Prototype tests confirm reliable scanning, orientation detection, and signal reception through glass into water.

20 - An Evaluation of Low-Cost Terrestrial Lidar Sensors for Assessing Hydrogeomorphic Change - Published by AGU - Advancing earth and space sciences

Authors: M. T. Perks, S. J. Pitman, R. Bainbridge, A. Díaz- Moreno, and S. A. Dunning Accurate topographic data is crucial for geomorphic research, with advances in remote sensing enabling high- resolution surveys. Small-form-factor (SFF) 3D lidar sensors, deployable on mobile and fixed systems, show potential for geomorphic studies, though their use in fixed installations remains unassessed. In a 3-month fluvial channel change study, SFF lidar sensors produced change detection results comparable to conventional lidar and small median differences in eroding zones (0.02–0.04 m). The data enabled precise analysis of river channels, assessment of bank retreat, and extraction of water surface elevations.

21 - An Optimal Denoising Method for Spaceborne Photon- Counting LiDAR Based on a Multiscale Quadtree - Published by MDPI

Authors: Baichuan Zhang, Yanxiong Liu, Zhipeng Dong, Jie Li, Yilan Chen, Qiuhua Tang, Guoan Huang, and Junlin Tao IIce, Cloud, and Land Elevation Satellite-2 (ICESat-2) has great potential for gathering water depth information around islands and reefs. A new method is proposed for denoising photon-counting lidar data by using techniques like DBSCAN and multiscale quadtree analysis. This involves preprocessing point cloud data with kernel density estimation, setting thresholds to remove noise, and using quadtree segmentation for fine denoising. Tests show this method significantly improves accuracy, achieving a determination coefficient of 94.59% and an RMSE of 1.01 m, enhancing underwater terrain mapping.

22 - The Impact of LIDAR- Assisted Pitch Control on Floating Offshore Wind Operational Expenditure

Authors: Andrew J. Russell, Jade McMorland, Maurizio Collu, Alasdair S. McDonald, Philipp R. Thies, Aidan Keane, Alexander R. Quayle, David McMillan, James Carroll, Andrea Coraddu Floating offshore wind (FOW) is critical for climate action and sustainability but faces higher operational costs due to deep-water deployment challenges. LIDAR-assisted pitch control, leveraging nacelle-mounted LIDAR for wind measurements, offers potential cost savings by reducing structural load variations. A study translating feedforward pitch control results to future ScotWind sites predicts up to 5% OpEx reduction (11% with workability constraints), with greater benefits at sites farther offshore. This approach could lower the levelized cost of energy for future FOW projects.

23 - Coastline Bathymetry Retrieval Based on the Combination of LiDAR and Remote Sensing Camera - Published by MDPI

Authors: Yicheng Liu, Tong Wang, Qiubao Hu, Tuanchong Huang, Anmin Zhang, and Mingwei Di This paper introduces the Compact Integrated Water–Land Survey System (CIWS), which combines a remote sensing camera and a LiDAR module to propose an innovative technique for underwater topography retrieval. The method uses high-precision LiDAR-derived water-depth points as control points, integrated with grayscale values from aerial photogrammetry images, to construct a bathymetry retrieval model capable of large- scale shallow-water mapping. Experimental validation successfully generated 3D seabed topographic maps, demonstrating the feasibility and accuracy of this integrated scanning method.

24 - Sequential Multimodal Underwater Single-Photon Lidar Adaptive Target Reconstruction Algorithm Based on Spatiotemporal Sequence Fusion

Authors: Tian Rong, Yuhang Wang, Qiguang Zhu, Chenxu Wang, Yanchao Zhang, Jianfeng Li, Zhiquan Zhou, and Qinghua Luo This paper presents a sequential multimodal underwater single-photon LiDAR adaptive target reconstruction algorithm based on spatiotemporal sequence fusion, designed for long-range, high-resolution imaging of slow- moving small underwater targets. The method comprises three stages: data preprocessing, sequence-optimized extreme value inference filtering, and collaborative variation–based image optimization—enabling robust extraction of depth and reflectivity from sparse, noisy photon echoes.

25 - How Accurate Can 2D LiDAR Be? A Comparison of the Characteristics of Calibrated 2D LiDAR Systems

Authors: Adam Ziebinski, and Piotr Biernacki 2D LiDAR measurements often lack the precision required to accurately determine the motion range or recalibrate the position of Autonomous Guided Vehicles (AGVs). To address this, this article proposes a multi-sectional calibration (MSC) method with median filtration (MF) to improve measurement accuracy. By dividing the measurement range into sections and optimizing the MF window width, the method enhances sensitivity to deviations and improves distance measurement accuracy by up to 89%. Experiments confirm its significant impact on the precision and accuracy of 2D LiDAR systems.

26 - Empirical Quantification of Topobathymetric Lidar System Resolution Using Modulation Transfer Function

Author: K. W. Sacca, and J. P. Thayer Topobathymetric scanning lidar on unmanned aircraft systems enables high-resolution mapping of terrain and underwater interfaces but lacks standardized empirical resolution validation methods. Theoretical models often fail to account for instrument, platform, or environmental uncertainties, particularly in bathymetry where water conditions significantly impact performance. To address this, the study extends modulation transfer function (MTF) methods, traditionally used for passive imaging, to active scanning lidar by employing compact retroreflectors as calibration targets. These targets facilitate empirical resolution assessment using height data alone, independent of intensity measurements.

27 - Hyperspectral LiDAR for Subsea Exploration: System Design and Performance Evaluation Method

Authors: Huijing Zhang, Linsheng Chen, Haohao Wu, Mei Zhou, Jiuying Chen, Zhichao Chen, Jian Hu, Yuwei Chen, Jinhu Wang, Yifang Niu, Meisong Liao, Xiaoxing Wang, Wanqiu Xu, Tianxing Wang, and Shizi Yu his study introduces an advanced underwater hyperspectral LiDAR (UDHSL) system operating from 450–700 nm, with adjustable spectral bandwidth (10–300 nm) and repetition rate (50 kHz–1 MHz). It achieves high precision (≤1 mrad divergence, 7 ns pulse width, 7.5 µJ energy, 1.13 cm ranging resolution, 1.02 m accuracy at 27 m).

28 - Enhancing Underwater LiDAR Accuracy Through a Multi- Scattering Model for Pulsed Laser Echoes

Authors: Ruichun Dong, Xin Fang, Xiangqian Meng, Chengyun Yang, & Tao Li This study introduces a Monte Carlo-based mathematical model for airborne LiDAR bathymetry to address the inaccuracy caused by neglecting multiple scattering events in conventional processing. The model simulates laser propagation through water, accounting for these scattering events using the Beer-Lambert law and the H-G phase function. Unlike existing research that focuses on laser emission, this work analyzes the probability of light reception in LiDAR returns. Results show that incorporating three or more scattering events significantly improves detection accuracy: by approximately 7% at 10m depth and 15-33% at 50m depth, thereby enhancing the efficiency of experimental systems.

29 - Spaceborne LiDAR Systems: Evolution, Capabilities, and Challenges

Authors: Jan Bolcek, Mohamed Barakat A. Gibril, Jirí Veverka, Šimon Sloboda, Roman Maršálek, and Tomáš Götthans This paper reviews space-borne LiDAR instruments, highlighting their evolution, capabilities, and contributions to Earth observation. It examines high-level LiDAR design, components, and operational parameters, and illustrates their role in studying environmental and atmospheric phenomena through select space missions. The paper also explores the ongoing development of advanced LiDAR technologies for future applications.

30 - Sensor Synergy in Bathymetric Mapping: Integrating Optical, LiDAR, and Echosounder Data Using Machine Learning

Authors: Emre Gülher, and Ugur Alganci This study integrates multi-sensor datasets to improve bathymetric mapping in coastal and inland waters, leveraging sensor strengths via data fusion and machine learning for better spatial coverage, resolution, and accuracy.

31 - LGMMFusion: A LiDAR-guided multi-modal fusion framework for enhanced 3D object detection

Authors: Haixing Cheng, Chengyong Liu, Wenzhe Gu, Yuyi Wu, Mengye Zhao, Wentao Liu, Naibang Wang LGMMfusion is a novel LiDAR-guided multimodal fusion framework for autonomous driving object detection, designed to improve small-object detection by addressing limitations of sparse LiDAR points and low-resolution image features. Unlike conventional methods that fuse LiDAR and camera features only at the detection head, LGMMfusion leverages LiDAR depth priors to guide the generation of higher-quality image Bird’s Eye View (BEV) features before fusion. It enables early spatial interaction between point clouds and pixels via multi-head, multi- scale self-attention and adaptive cross-attention mechanisms, thereby ensuring better alignment

32 - Detection of Submerged Targets Beyond Eyes' Observation Using Satellite LiDAR and Multispectral Data

Authors: Hao Liu, Jian Yang, Yue Ma, Yao Li, and Xiao Hua Wang Underwater image quality is degraded by light absorption and scattering, hindering applications in marine robotics and archaeology. Existing enhancement methods often fail to recover fine details without artifacts. This work proposes a hybrid U-Net-Transformer (UTR) architecture that combines local feature extraction with global context modeling. Its key innovation is the Recurrent Multi-Scale Feature Modulation (R-MSFM) mechanism, a gated, multi- scale iterative refinement strategy in the decoder that preserves spatial fidelity during upsampling.

33 - Applying Deep Learning to Bathymetric LiDAR Point Cloud Data for Classifying Submerged Environments

Authors: Nabila Tabassum, Henri Giudici, Vimala Nunavath, and Ivar Oveland Subsea environments are crucial for biodiversity, climate regulation, and human activities like fishing and resource extraction, necessitating accurate mapping for sustainable management. Airborne LiDAR bathymetry (ALB) offers high-resolution underwater data but generates large, complex datasets that challenge efficient analysis. This study applies deep learning models, Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM), to multi- class classification of ALB waveform data. A preprocessing pipeline extracted and labeled waveform peaks into five classes: sea surface, water, vegetation, seabed, and noise. Experiments on two datasets showed high classification accuracy:

34 - Mapping River Bed Topography in Whitewater Rapids Using Bathymetric LiDAR

Authors: Jan Rhomberg-Kauer, Theresa Himmelsbach, Florian Pöppl, Lucas Dammert, Martin Pfennigbauer, Gottfried Mandlburger Bathymetric LiDAR struggles to detect riverbeds in turbulent whitewater rapids of mountain rivers. This study introduces a novel full-waveform processing method that uses curve fitting to model and subtract the water column signal, isolates residual energy, and applies peak detection to recover previously undetected bottom returns. Validated across three rivers using total station ground truthing, the method reduces median vertical errors from 20.6 cm to 9.2 cm and from 40.4 cm to 22.5 cm, significantly filling data gaps in whitewater zones.

35 - A Review of Solid-State LiDAR Principles and Metasurface-Based LiDAR Sensors

Authors: Elif Demirbas, Braden Boucher, Matthew Baker, Joshua Andrews, William Cruz, Sara Mueller, and Samuel Serna-Otalvaro LiDAR is a promising technology for autonomous vehicles, with solid-state alternatives like microelectromechanical systems (MEMS) and optical phased arrays (OPAs) offering compact and robust solutions compared to traditional mechanical LiDAR systems with rotating mirrors. Two- dimensional optical metasurfaces enable beam steering by shifting the phase of incoming light; static metasurfaces are suitable for fixed beam directions, while dynamic (tunable) metasurfaces are essential for real-time beam scanning. Metasurface-based LiDAR provides advantages such as flat optics design, robustness, and absence of moving parts.

36 - Robust Localization of Flange Interface for LNG Tanker Loading and Unloading Under Variable Illumination a Fusion Approach of Monocular Vision and LiDAR

Authors: Mingqin Liu, Han Zhang, Jingquan Zhu, Yuming Zhang and Kun Zhu This paper addresses the challenge of accurately localizing flange interfaces in LNG tankers under extreme illumination conditions. While monocular vision fails in glare or low light, and LiDAR lacks texture information, the authors propose a vision-LiDAR fusion method with three key innovations: an illumination-adaptive framework that dynamically adjusts parameters based on grayscale evaluation, a multi-constraint flange detection strategy using physical constraints and K-means clustering, and a customized fusion pipeline combining ROI extraction, plane fitting, and 3D circle solving to compensate for individual sensor limitations.

37 - Analysis of Underwater Single-Photon LiDAR Signals: A Comprehensive Study on Multi-Parameter Coupling Effects

Authors: Ceyuan Wang, Shijie Liu, Shouzheng Zhu, Wenhang Yang, Chenhui Hu, Yuwei Chen, Chunlai Li, and Jianyu Wang Underwater laser signal attenuation poses challenges for conventional detection, but single-photon LiDAR (SPL) with high sensitivity offers a promising solution. Prior studies mainly examined isolated parameters, leaving the coupled effects of environmental and system factors underexplored. This research developed a 532 nm underwater SPL system to systematically investigate multi- parameter coupling in laboratory water tanks, varying turbidity, detection distances, laser energy levels, integration times, and target types.

Authors: Kai Zhang, Fanlin Yang, Hande Zhang, Dianpeng Su, and QianQian Li Recent studies have identified a correlation between seafloor morphological features and biological complexity. This research developed a standard deviation (STD)-based method to quantitatively characterize terrain complexity, incorporating robust estimation to correct for irregular bathymetry and calibration for depth-dependent measurement noise. Airborne lidar and shipborne sonar bathymetry data from Yuanzhi Island, South China Sea, were merged to create seamless, high-resolution coverage from shoreline to deep water. Applying the new algorithm generated quantitative terrain complexity maps, which showed a significant correlation with in situ video observations of coral abundance.

39 - Coastal Ecosystem Investigations with LiDAR (Light Detection and Ranging) and Bottom Reflectance: Lake Superior Reef Threatened by Migrating Tailings

Authors: W. Charles Kerfoot, Martin M. Hobmeier, Sarah A. Green, Foad Yousef, Colin N. Brooks, Robert Shuchman, Mike Sayers, Lihwa Lin, Phu Luong, Earl Hayter, and Molly Reif Over a century ago, two stamp mills released 22.7 million metric tons of copper-rich tailings into Grand Traverse Bay, which differ in properties from natural bedrock and quartz sands. LiDAR surveys from 2008 to 2016, along with ground sampling and bottom reflectance studies, showed how tailings have spread. They are now moving onto Buffalo Reef, affecting fish production. Predictions suggest 60% reef coverage in 10 years, with CASI imaging estimating 25–35% tailings coverage.

40 - Habitat Classification of Temperate Marine Macroalgal Communities Using Bathymetric LiDAR

Authors: Richard Zavalas, Daniel Ierodiaconou, David Ryan, Alex Rattray, and Jacquomo Monk This study evaluated bathymetric LiDAR's potential for characterizing shallow water (<30 m) benthic habitats in high-energy subtidal coastal environments. Habitat classification of benthic substrata and macroalgal communities was achieved by combining LiDAR data, underwater video groundtruthing, and automated classification techniques using the Quick Unbiased Efficient Statistical Tree (QUEST) decision tree algorithm. Bathymetry and reflectance datasets were used to produce secondary terrain derivatives that influence benthic patterns. The resulting habitat maps showed overall accuracy exceeding 70%.

Authors: Joaquim Santos, Hans H. Jakobsen, Paul M. Petersen, and Christian Pedersen Plankton is vital for aquatic ecosystems by contributing to the biological carbon pump, yet climate change threatens these communities, necessitating their monitoring for ecosystem health assessment. Existing underwater imaging techniques are limited to small, fixed volumes, prompting the development of a novel scanning multispectral confocal LiDAR system. This system captures high-resolution 4D morphological and spectroscopic data, enabling AI models to classify microplastics by color and size and identify zooplankton and microalgae genera through in vivo autofluorescence.

Authors: Calebe Pereira Mendes, Norman T-Lon Lim Commercially available LiDAR scanners are expensive, limiting their use in research, especially in developing countries. To address this, a simple, affordable ground- based LiDAR scanner was designed and built costing under $400 (USD, 2021), which is easy to assemble with minimal engineering expertise. This scanner provides sufficient performance for various ecological research projects and produces quality point clouds for common LiDAR products. While its range is limited for large-scale mapping, the open-source, customizable design costs approximately 1% of market "low-cost" scanners, making LiDAR accessible for budget-constrained projects and opening new opportunities, particularly in developing nations.

43 - Classification of Underwater Sediments in Lab Based on LiDAR Full-Waveform Data

Authors: Libin Du, Dawei Wan, Xiangqian Meng, Wenjing Li, Guangxin Liang and Hongyu Li The classification of shallow sea sediments using airborne LiDAR bathymetry represents a significant advancement in marine science and engineering, providing high accuracy and mobility. Despite its value, accurately classifying shallow marine sediments remains challenging due to differentiation difficulties and accuracy limitations. This paper proposes a feature selection method combining Sequential Forward Selection with Random Forests, tested in a laboratory setting. The model achieved 94.1% overall classification accuracy and a Kappa coefficient of 91.11%, enabling precise and efficient underwater sediment classification.

44 - High Resolution Mapping of Submerged Sediment Size and Suitable Salmon Spawning Habitat Using Topo-Bathymetric LiDAR in the Santiam River Basin, Oregon