Marine Geodesy最新文献

{"title":"Acoustic Ray-Trace Correction for UUVs Cooperative Localization in Deep Ocean Applications","authors":"Zhenqiang Du, Hongzhou Chai, Zeyu Li, Minzhi Xiang, Fan Zhang, Jun Hui","doi":"10.1080/01490419.2022.2059601","DOIUrl":"https://doi.org/10.1080/01490419.2022.2059601","url":null,"abstract":"Abstract Precise position of Unmanned Underwater Vehicles (UUVs) plays a decisive role in optimal formation control, reasonable path planning, and efficient cooperative operation. However, the traditional method has the deficiency of low ranging accuracy and contains systematic deviation in the deep ocean applications, which seriously affects the accuracy of UUVs position and makes the goal of UUVs optimal configuration no longer applicable. A novel acoustic ray-trace correction method is proposed for UUVs cooperative localization in deep ocean applications. Considering the bending of underwater sound ray and the variation of sound velocity, the model of UUVs cooperative localization based on ray-trace correction is established. Two master UUVs in shallow ocean and one slave UUV in deep ocean under five configurations are simulated. The experimental results show that the average position bias of UUVs cooperative localization under the five configurations are reduced by 57.97%, 62.29%, 68.51%, 74.93% and 82.54%, respectively, which can expand the application scenarios of UUV. Furthermore, the proposed method can overcome the drawback of systematic deviation in the traditional method, so as to be consistent with the goal of UUVs optimal configuration.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46372703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Realization and Evaluation of Real-Time Uncombined GPS/Galileo/BDS PPP-RTK in the Offshore Area of China’s Bohai Sea","authors":"Xiao Yin, Hongzhou Chai, W. Xu, Liang Zhao, Huawei Zhu","doi":"10.1080/01490419.2022.2057628","DOIUrl":"https://doi.org/10.1080/01490419.2022.2057628","url":null,"abstract":"Abstract The real-time kinematic (RTK) technology has been widely used as the high-precision positioning method in the offshore area. However, RTK requires a bi-directional communication and groups measurement errors together, thereby limiting its mass-market applications. Combining the advantages of precise point positioning (PPP) and RTK, PPP-RTK has become one of the hotspot technologies in the mass market. In this contribution, we propose the uncombined multi-GNSS PPP-RTK model using uncalibrated phase delays (UPDs) estimated from the legacy ionosphere-free and Melbourne-Wübbena combination. With the UPDs estimated based on 14 regional stations, we conduct PPP ambiguity resolution (AR) at 3 augmentation stations and derive precise atmospheric corrections, i.e., RMS of zenith tropospheric and slant ionospheric correction can be up to 4.89 mm and 2.20 cm, respectively. After applying atmospheric correction, the correct fixed solution of four on-board kinematic experiments can be better than 95% and the positioning accuracy can be better than 5 cm in both horizontal and vertical direction, showing the encouraging performance similar to RTK in the offshore area.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43174760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework for Automatic Coral Reef Extraction Using Sentinel-2 Image Time Series","authors":"Qizhi Zhuang, Jian Zhang, Liang Cheng, Hui Chen, Yanruo Song, Song Chen, Sensen Chu, Shengkun Dongye, Manchun Li","doi":"10.1080/01490419.2022.2051648","DOIUrl":"https://doi.org/10.1080/01490419.2022.2051648","url":null,"abstract":"Abstract Using supervised and unsupervised classification on a single image to extract coral reef extent results in missing data and wrong extraction results. To improve the accuracy of coral reef extraction, this study proposes a novel technical framework for automatic coral reef extraction based on an image filtering strategy and spatiotemporal similarity measurements of pixel-level Sentinel-2 image time series. This method was applied to the Anda Reef, Daxian Reef, and Nanhua Reef, China, using 1464 Sentinel-2 images obtained from 2015–2020. Sentinel-2 images were automatically selected considering space, time, cloud cover, and image entropy after atmospheric correction. With the binary classification measurement standard using the digitization coral reef results of the Sentinel-2 images as the true value, the time series established by the modified normalized difference water index demonstrated high robustness and accuracy. Analyzing the time series curves of the coral reef and deep water verified that the spatiotemporal similarity measurement of this framework can stably extract the boundaries of the coral reef.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45195113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved Seafloor Geodetic Positioning via Sound Velocity Correction Based on the Precise Round-Trip Acoustic Positioning Model","authors":"Dajun Sun, Miao Yu, C. Zheng, Yunfeng Han, Zongyan Li","doi":"10.1080/01490419.2022.2054884","DOIUrl":"https://doi.org/10.1080/01490419.2022.2054884","url":null,"abstract":"Abstract Seafloor geodetic positioning is crucial for evaluating the marine geodetic network and monitoring various marine activities. We propose a sound velocity correction method based on the precise round-trip acoustic positioning model to improve the accuracy of seafloor geodetic positioning. The proposed method models the sound velocity error related to sound velocity profile (SVP) deviation and time-varying error and reduces the propagation error of the acoustic rays in the ocean. The SVP deviation and seafloor position parameters are resolved simultaneously by the Bayesian estimation using the round-trip acoustic travel time. The time-varying errors of SVP are corrected through symbolic regression using multi-gene genetic programming (MGGP) even without any accurate pre-specified mathematical form of marine environmental variations. The results from sea trial conducted in the South China Sea at a depth of 3000 m demonstrate that the developed method compensates for the sound velocity errors and improves the positioning precision of the seafloor transponder, with the position difference between different data sets better than 46.12 cm, the standard deviation of acoustic time residuals better than 0.15 ms, and the square root of the variance of the position better than 0.41 cm.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45693516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Nonlinear Gauss-Helmert Model and Its Robust Solution for Seafloor Control Point Positioning","authors":"Yingcai Kuang, Zhiping Lu, Fangchao Wang, Kaichun Yang, Linyang Li","doi":"10.1080/01490419.2022.2054883","DOIUrl":"https://doi.org/10.1080/01490419.2022.2054883","url":null,"abstract":"Abstract Using GNSS-Acoustic (GNSS-A) technology to establish the seafloor geodetic datum is both feasible and flexible and thus has become an important way to obtain the absolute positions of seafloor control points. However, numerous errors are inevitable in marine surveying, including systematic errors and gross errors caused by GNSS dynamic positioning, inaccurate sound velocity profile measurements, and ocean ambient noise, and their interference will be directly reflected in the positioning results. To accurately calculate the seafloor control point coordinates, this paper first notes that the general error propagation law (EPL) method is defective in dealing with various error factors in GNSS-A positioning. A more rigorous method incorporates the time-varying term of the sound velocity ranging error into the coefficient matrix of the underwater observation equation, and the transducer position error should be considered. Therefore, a Gauss-Helmert (GH) model is used for seafloor control point positioning. Then, considering the dual nonlinearity of the model, a Lagrange objective function is constructed to derive its solution algorithm. On this basis, considering the gross errors polluting of the observations, the robust estimation principle is introduced, and the robust solution steps are given. Finally, simulation experiments and a testing experiment in the sea area near Jiaozhou Bay are used to verify the performance of the new method. The results show that the functional relationship and stochastic model of the nonlinear GH model for seafloor point positioning are reasonably described. Under ideal conditions with no gross errors and either different water depths or different transducer position errors, the accuracy and stability of the new method are both higher than those of the EPL method. When the observations are polluted by gross errors, the robust algorithm of the new method can accurately identify the abnormal information. By improving the robustness of the observation and structure spaces, the positioning precision of the 3D point deviation results can be optimized, and the solution performance of the new method is superior to that of the general method.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47638118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Offsets and Outliers on the Sea Level Trend at Antalya 2 Tide Gauge within the Eastern Mediterranean Sea","authors":"M. Ayhan","doi":"10.1080/01490419.2022.2047843","DOIUrl":"https://doi.org/10.1080/01490419.2022.2047843","url":null,"abstract":"Abstract Antalya 2 tide gauge (TG) station is located on the coast of Turkey within the Eastern Mediterranean Sea. Relative sea level trends 6.0 ± 1.5 and 6.44 ± 0.45 mm/year over 1985–2009 at Antalya 2 TG are different from the trend (1.6 ± 1.5 mm/year over 1935–1977) at Antalya TG within 10 km. In order to investigate this trend discrepancy, the monthly mean series at Antalya 2 TG is re-analyzed for offsets, outliers and trend estimation. The Zivot-Andrews method and the outlier test result in one offset at 1994.0417 year with magnitude of 71.24 ± 13.48 mm and nine outliers. The series, corrected for the offset and outliers, de-seasonalized and filled for missed points, is identified as trend-stationary process and analyzed for trend estimation by various models. The optimal model providing the lowest Akaike Information Criteria is polynomial linear trend with multiplicative seasonal Autoregressive Moving Average (ARMA(2,0)x(1,0)12). The estimated relative sea level trend by the optimal model is 1.77 ± 0.65 mm/year. The large trend discrepancy at Antalya 2 TG is accounted for by one offset primarily (∼71%) and nine outliers (∼3%).","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49090421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Investigation of the Hydrography of Chabahar Bay Using FVCOM Model and EOF Analysis","authors":"Alireza Bahmanzadegan Jahromi, M. Ezam, K. Lari, Abbas-Ali Ali Akbari Bidokhti","doi":"10.1080/01490419.2022.2042434","DOIUrl":"https://doi.org/10.1080/01490419.2022.2042434","url":null,"abstract":"Abstract Chabahar Bay is a semi-enclosed and shallow omega-shaped bay, located on the south-eastern coasts of Iran. The 3D unstructured-grid Finite-Volume Coastal Ocean Model was employed to study the physical characteristics of water in Chabahar Bay. The correlation coefficients between the model and available measurements were 0.99 and 0.84 for water level and current velocity, respectively. The numerical results show that the depth averaged temperature of the Bay generally decreases from north to south and varies between 20-26 °C during the year. The basin average of annual salinity is 36.1 psu. Hence, the density increases from north to south and is strongly affected by temperature changes. The vertically average of sigma-t varies between 21.5-24.0 kg/m3. In the northern half of the Bay a warm center eddy is formed from March; during July, it strengthened and peaked in August. With Applying EOFs analysis on model surface temperature four principal patterns were determined. EOF1 corresponds to the bathymetry of the region and shows the heat capacity of the Bay, it is in accordance with the monsoon conditions. EOF2, 3, and 4 are corresponding to the effect of the wind. Due to dominant winds a strong upwelling was determined along the western coast.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47248882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Compensation Algorithm with Motion Constraint in DVL/SINS Tightly Coupled Positioning","authors":"Kaidi Jin, Hongzhou Chai, Chuhan Su, Minzhi Xiang","doi":"10.1080/01490419.2022.2040662","DOIUrl":"https://doi.org/10.1080/01490419.2022.2040662","url":null,"abstract":"Abstract Integration of strapdown inertial navigation system (SINS) and doppler velocity log (DVL) is usually applied in underwater applications, wherein DVL provides the three-dimensional velocity, and hence the accumulated error of SINS can be compensated. However, the DVL/SINS loosely coupled approach fails in the complex environments on the condition of fewer than three available beams. And the tightly coupled approach divergences with only one direction velocity information from the beam measurement. To solve the problems, a novel tightly coupled method is proposed in this paper, in which the state of UUV motion is considered, and a robust adaptive Kalman filter is utilized to dynamically estimate the observation noise. Experiment results indicate that the proposed method is efficient in UUV missions for beam limited environment.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44691683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrated Approach for Determining the Anthropogenic Stress Responsible for Degradation of a Ramsar Site – Wular Lake in Kashmir, India","authors":"Saleha Jamal, Wani Suhail Ahmad, Uzma Ajmal, Mohammad Aaquib, Md. Ashif Ali, Md. Babor Ali, Shafiq Ahmed","doi":"10.1080/01490419.2022.2034686","DOIUrl":"https://doi.org/10.1080/01490419.2022.2034686","url":null,"abstract":"Abstract During the last one and half decade, Kashmir valley's water bodies have been facing widespread water quality deterioration due to anthropogenic interferences' enhancement. In this context, the present study aims to monitor the water quality of Wular Lake by subjecting the acquired datasets to statistical approaches to infer status about distinctions and similarities among different sampling sites under investigation. The study integrated multiple data sets pertaining to analysis and assessment of water quality parameters, physicochemical concentration values, land use change systems, and water quality index through remote sensing and GIS environments. For limnological characterization of the lake, surface water quality data have been collected from seven randomly selected site pertaining to 22 physicochemical parameters, which were further analyzed. Settlements, agriculture, and horticulture in the lake's immediate vicinity were mapped using LISS IV satellite data of the year 2008–2019. The water quality index under this study comprises 12 measurable physicochemical parameters – pH, electrical conductivity, dissolved oxygen, total hardness, calcium content, magnesium content, nitrate nitrogen, chloride, turbidity, potassium, sodium and total alkalinity. Based on WQI values, the whole lake was divided into five zones, comprising least polluted zone (<50), moderately polluted zone (50–100), highly polluted zone (100–200), very highly polluted zone (200–300) and extremely polluted zone (>300). From this study, it has been found that WQI values for site S1, S2, S3, S4, S5, S6 and S7 are 179.62, 149.8, 160.61, 205.21, 200.5, 164.95 and 183.74, respectively. Thus, revealing that site S4 and S5 fall under the 'very highly polluted zone' and the remaining sites S1, S2, S3, S6 and S7 under 'highly polluted zone'. Land use category settlement record a growth rate of +50.79%, horticulture +25.96%, agriculture −11.8% and water body (open waters) −24.3% from the year 2008–2019. The reckless use of fertilizers, insecticides, pesticides in orchards and agricultural farms reinforced by concrete jungles in the immediate vicinity of Wular Lake have also enhanced the nutrient enrichment and deterioration of the water quality. Thus, escalating its scope towards the process of eutrophication.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46260486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multi-Source Convolutional Neural Network for Lidar Bathymetry Data Classification","authors":"Yiqiang Zhao, Xuemin Yu, Bin Hu, R. Chen","doi":"10.1080/01490419.2022.2032498","DOIUrl":"https://doi.org/10.1080/01490419.2022.2032498","url":null,"abstract":"Abstract Airborne Lidar bathymetry (ALB) has been widely applied in coastal hydrological research due to outstanding advantages in integrated sea-land mapping. This study aims to investigate the classification capability of convolutional neural networks (CNN) for land echoes, shallow water echoes and deep water echoes in multichannel ALB systems. First, the raw data and the response function after deconvolution were input into the network via different channels. The proposed multi-source CNN (MS-CNN) was designed with a one-dimensional (1 D) squeeze-and-excitation module (SEM) and a calibrated reference module (CRM). The classification results were then output by the SoftMax layer. Finally, the accuracy of MS-CNN was validated on the test sets of land, shallow water and deep water. The results show that more than 99.5% have been correctly classified. Besides, it has suggested the best robustness of the proposed MS-CNN compared with other advanced classification algorithms. The results indicate that CNN is a promising candidate for the classification of Lidar bathymetry data.","PeriodicalId":49884,"journal":{"name":"Marine Geodesy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47469919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}