{"title":"2024 Index IEEE Journal of Oceanic Engineering Vol. 49","authors":"","doi":"10.1109/JOE.2024.3487337","DOIUrl":"https://doi.org/10.1109/JOE.2024.3487337","url":null,"abstract":"","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1-28"},"PeriodicalIF":3.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10738844","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Call for papers: Special Issue on the IEEE UT2025 Symposium","authors":"","doi":"10.1109/JOE.2024.3470608","DOIUrl":"https://doi.org/10.1109/JOE.2024.3470608","url":null,"abstract":"","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1695-1696"},"PeriodicalIF":3.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10719024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hierarchical Interactive Attention Res-UNet for Inland Water Monitoring With Satellite-Based SAR Imagery","authors":"Yemao Yang;Weiliang Tao;Yan Liu;Lei Cheng;Yuan Gao","doi":"10.1109/JOE.2024.3447782","DOIUrl":"https://doi.org/10.1109/JOE.2024.3447782","url":null,"abstract":"The extraction and change detection of river-lake boundaries has a wide range of applications. Especially in flood monitoring, river-lake boundary monitoring systems can provide important information support for relevant departments in flood prevention and relief. Aiming at the problem that the existing research has low accuracy and poor boundary quality in complex terrain, we propose a hierarchical interactive attention Res-UNet. By introducing a cross-dimensional attention mechanism with hierarchical interactions, the model's ability to perceive key features is improved. In addition, we propose contour-aware mixed loss, which pays more attention to difficult samples and edge pixels. Based on Sentinel-1A satellite data, we produce a synthetic aperture radar data set of river and lake water bodies. Through comparative experiments, the effectiveness of this method in improving water body segmentation accuracy and boundary quality is proved. The final F1 score is 0.973 and HD95: Hausdorff distance (HD) with a 95% confidence level is 2.219. Finally, we apply our methodology to study the changes in the water body near Wuhan Sancha Harbor during the 2020 Yangtze River flood, which proves the effectiveness of the scheme.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1265-1274"},"PeriodicalIF":3.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"NWSP: A Novel Indicator for Ocean–Land Interface Extraction Using Bathymetric LiDAR","authors":"Xinglei Zhao;Hui Xia;Fengnian Zhou","doi":"10.1109/JOE.2024.3436907","DOIUrl":"10.1109/JOE.2024.3436907","url":null,"abstract":"Because of water-surface uncertainty, green lasers used in airborne bathymetric LiDAR cannot accurately detect the water surface, as they reflect near-water surface penetration (NWSP) into the water column. The existence of the NWSP of a green laser in water is not beneficial for high-accuracy depth measurements; however, it can be useful for ocean–land interface (OLI) extraction. In this study, novel ocean–land discrimination and interface extraction methods based on the NWSPs of green lasers are proposed. First, the NWSPs of different green laser channels are calculated and averaged to obtain a robust NWSP for each laser footprint. Second, a novel NWSP-based ocean–land discriminator is proposed based on the different characteristics of the NWSPs in land and ocean areas. Third, density-based spatial clustering of applications with noise algorithm is used to identify and correct the misclassified points of the NWSP-based ocean–land discriminator, and the OLIs are formed by connecting the land boundary points. Finally, the novel NWSP method is verified using a raw ABL data set collected via Optech coastal zone mapping and imaging LiDAR. The OLIs derived by waveform clustering are used as reference to evaluate the performance of the proposed NWSP method. OLI extraction based on the proposed NWSP method and the traditional point elevation method can reach accuracies of 1.9 and 4.8 m, respectively, in the research area. The proposed NWSP method provides a novel and convenient means for OLI extraction using the NWSPs of green lasers.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1472-1487"},"PeriodicalIF":3.8,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Entropy-Based Automatic Detection of Marine Mammal Tonal Calls","authors":"Yue Liang;Kerri D. Seger;Nicholas J. Kirsch","doi":"10.1109/JOE.2024.3436867","DOIUrl":"10.1109/JOE.2024.3436867","url":null,"abstract":"Hydrophones are deployed throughout the ocean to perform passive acoustic monitoring. This technique is a powerful tool for marine mammal sound detection due to its advantage of being able to collect data overnight, year-round, and in inclement weather. However, hundreds of terabytes of data produced each year pose a significant challenge for data analysis. The aim of this study was to investigate the use of entropy-based techniques to achieve automatic detection of marine mammal tonal calls in passive acoustic monitoring data. A weighted spectral entropy technique was developed to alleviate the impact of underwater noise along with a novel algorithmic detector. The detector includes an adaptive bandpass filter, a time–frequency domain transform, and a likelihood ratio test for calculating the optimal detection threshold in addition to the Weighted Spectral Entropy Technique. The proposed entropy-based technique and the automatic detector were assessed with synthetic and real-world data and the performance was compared to other state-of-the-art techniques. The results indicate that the proposed method outperforms the other techniques when evaluated using various types of low signal-to-noise ratio tonal signals.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1140-1150"},"PeriodicalIF":3.8,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using Cross-Mission SAR Data for a Multidecadal Coastline Change Monitoring and Assessing the Influences of SAR-Related Factors","authors":"Ya-Lun S. Tsai","doi":"10.1109/joe.2024.3425968","DOIUrl":"https://doi.org/10.1109/joe.2024.3425968","url":null,"abstract":"","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"65 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giovanni Battista Rossi, Gabriele Nardone, Marco Picone, Giulio Settanta, Francesco Crenna, Marta Berardengo
{"title":"Testing High Directional Resolution Sea-Spectrum Estimation Methods in View of the Needs of a National Monitoring System","authors":"Giovanni Battista Rossi, Gabriele Nardone, Marco Picone, Giulio Settanta, Francesco Crenna, Marta Berardengo","doi":"10.1109/joe.2024.3436771","DOIUrl":"https://doi.org/10.1109/joe.2024.3436771","url":null,"abstract":"","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"4 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proximal Policy-Optimized Regularized Least Squares Algorithm for Noise-Resilient Motion Prediction of UMVs","authors":"Yiming Zhong;Caoyang Yu;Xianbo Xiang;Lian Lian","doi":"10.1109/JOE.2024.3436770","DOIUrl":"https://doi.org/10.1109/JOE.2024.3436770","url":null,"abstract":"To enhance the accuracy of motion prediction in unmanned marine vehicles (UMVs), an innovative proximal policy-optimized regularized least squares (PPO-RLS) algorithm is proposed in this article. This article begins by developing a dynamics model for UMVs that incorporates viscous damping and external forces to minimize modeling errors. However, this model does not account for data noise, making accurate parameter identification difficult when using traditional least squares (LS) algorithms. To overcome this limitation, the PPO-RLS algorithm is proposed, incorporating a regularization term within the LS framework and utilizing proximal policy optimization for adaptive regularization term tuning. The performance of the PPO-RLS algorithm is thoroughly evaluated using both simulation data and lake trial data, demonstrating significant improvements over both the traditional LS algorithm and a state-of-the-art algorithm. Specifically, in simulation tests, the PPO-RLS algorithm achieves a notable reduction in root mean square error for surge velocity (8.49E-03 m/s) and heading angle (2.32\u0000<inline-formula><tex-math>$^circ$</tex-math></inline-formula>\u0000), markedly outperforming the LS algorithm (2.36E-02 m/s for surge velocity and 4.14\u0000<inline-formula><tex-math>$^circ$</tex-math></inline-formula>\u0000 for heading angle). In addition, the PPO-RLS algorithm displays enhanced stability, as indicated by a more than 50% reduction in condition number (1.46E+04 for PPO-RLS versus 2.89E+06 for LS). These improvements are further validated by lake trial data, confirming the algorithm's advanced motion prediction capabilities with quantitatively lower errors and greater robustness.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1397-1410"},"PeriodicalIF":3.8,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joseph L. Walker;Zheng Zeng;Chengchen L. Wu;Jules S. Jaffe;Kaitlin E. Frasier;Stuart S. Sandin
{"title":"Underwater Object Detection Under Domain Shift","authors":"Joseph L. Walker;Zheng Zeng;Chengchen L. Wu;Jules S. Jaffe;Kaitlin E. Frasier;Stuart S. Sandin","doi":"10.1109/JOE.2024.3425453","DOIUrl":"10.1109/JOE.2024.3425453","url":null,"abstract":"There is increasing interest in using deep learning–based object recognition algorithms to automate the labeling of image data collected from marine surveys. However, underwater object detection is a particularly challenging problem due to changes in scattering and absorption of light, and spotty data collection efforts, which rarely capture the broad variability. Using deep learning–based object detection systems for long-term or multisite marine surveying is further complicated by shifting data distributions between training and testing stages. Using data from the 100 Island Challenge, we investigate how object detection performance is impacted by changes in site characteristics and imaging conditions. We demonstrate that the combined use of data augmentation and unsupervised domain adaptation techniques can mitigate performance drops in the presence of domain shift. The proposed methodologies are broadly applicable to observational data sets in marine and terrestrial environments where a single algorithm needs to adapt to and perform comparably across changing conditions.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1209-1219"},"PeriodicalIF":3.8,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10679365","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Causality-Free Modeling and Validation of a Semisubmersible Floating Offshore Wind Turbine Platform With Tuned Mass Dampers","authors":"Doyal Sarker;Tajnuba Hasan;Tri Ngo;Tuhin Das","doi":"10.1109/JOE.2024.3436773","DOIUrl":"10.1109/JOE.2024.3436773","url":null,"abstract":"This article introduces an acausal modeling approach for constructing a hydrodynamic module within the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS), a wind turbine simulator under development by the authors, to facilitate control codesign (CCD) for floating offshore wind turbines. Verification and validation of the model are conducted using numerical data from the industrial-standard simulation platform OpenFAST and experimental data from the Floating Offshore-wind and Controls Advanced Laboratory Project. The validation results highlight the qualitative ability of the hydrodynamic module in CRAFTS to accurately capture loads and responses under wave excitation, including the stabilizing effects of tuned mass dampers across various load cases. Modeling the VolturnUS-S semisubmersible floater in CRAFTS, known for its complexity compared to other floaters like spar-buoy or tension leg platforms, demonstrates the versatility of this modeling approach for different support structures. Furthermore, runtime simulation comparisons reveal the enhanced computational efficiency of CRAFTS compared to OpenFAST, indicating significant improvements and underscoring its suitability for CCD applications.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1430-1454"},"PeriodicalIF":3.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}