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    14 July 2025, Volume 54 Issue 6
    Review
    Virtual trajectories: conceptual characteristics and research framework
    Huayi WU, Guangsheng DONG, Rui LI
    2025, 54(6):  967-981.  doi:10.11947/j.AGCS.2025.20240409
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    The spatio-temporal interactions between humans and virtual spaces generate virtual trajectories, providing a novel perspective for analyzing the relationship between individuals and virtual/physical spaces. Public map service platforms, as one of the most prevalent forms of virtual space, maintain spatial references consistent with physical space. Virtual trajectories within this space reflect human preferences and can predict potential spatial interaction patterns in the physical space, making them a central focus of current research. However, the conceptual characteristics and research framework of virtual trajectories remain undeveloped, hindering progress in this area. This paper defines the fundamental concepts of virtual trajectories in this space, analyzes the multi-scale and uncertain characteristics of virtual trajectories, and proposes a research framework grounded in modeling and analysis. The modeling methods encompass spatio-temporal representation, including temporal noise reduction, spatial dimensionality reduction, and spatial segmentation; path restoration based on browsing target identification and filtering; and semantic restoration that integrates spatial co-occurrence with semantic matching. The analytical framework identifies research directions for individual patterns, such as domain classification, topic clustering, and dynamic evolution, while outlining the current state of research on group patterns, including spatiotemporal distribution, spatiotemporal prediction, and virtual-physical interaction patterns. Future research directions are explored concerning theoretical foundations, technical approaches, spatial semantics, open-source data, and application scenarios. The proposed research framework offers a new paradigm for understanding human spatial activity patterns within virtual spaces.

    Geodesy and Navigation
    A method for satellite ultra-rapid orbit and clock offset estimation based on the prior information of the GNSS clock parameters
    Qianxin WANG, Chao HU, Tong CHENG
    2025, 54(6):  982-994.  doi:10.11947/j.AGCS.2025.20240451
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    GNSS ultra-rapid orbit and clock products are widely used in the area of real-time and near-real-time fast location-based services. However, due to the restriction of time-consuming and observations quality in the parameters estimation, the correlation between orbit and clock offset parameters in ultra-rapid determination is not considered. In addition, the merits of satellite onboard clock information is ignored. Therefore, in this research, an improved ultra-rapid orbit and clock estimation method is proposed based on the prior constraint on the GNSS clock parameters. First, the time-difference carrier phase algorithm is used to epoch-wisely update the satellite clock offset by fixing satellite orbit. Second, the short-term prediction model of clock offset is constructed to extract the prior information and model the satellite onboard atomic clock parameters. Third, the augmented model of ultra-rapid orbit and clock offset is constructed by the constraint of satellite onboard clock parameters in orbit determination equation. According to the experiment results, it is indicated that the significant correlation among orbit and clock offset parameters is presented, in which the accuracy of ultra-rapid clock offset can be improved with 30.9%~50.7%, compared with the traditional ultra-rapid clock products by fixing the orbit parameters. Meanwhile, the millimeter-level and at least 32.9% for orbit and clock offset accuracy improvements can be obtained by the prior constraint on clock parameters. Additionally, the performances of static PPP solution are respectively improved with 9.9%, 16.9% and 9.3% for E, N and U directions, compared with the traditional ultra-rapid orbit and clock products. Therefore, the proposed GNSS satellite orbit and clock offset method can effectively improve the performances of ultra-rapid products, which will further provide supporting for the high-quality PNT services.

    Assessment of GNSS ionosphere models based on FY-3 TEC in polar regions
    Yang SHEN, Guangyun LI, Mingjian CHEN, Linyang LI, Xingyu SHI, Wei CAI, Weifeng HAO
    2025, 54(6):  995-1008.  doi:10.11947/j.AGCS.2025.20240202
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    In view of the lack of detailed reference for the correction accuracy of the existing ionospheric model in the polar region, especially in the polar region where GNSS monitoring stations are lacking, the correction effects of GPS Klobuchar, Galileo NeQuickG, BeiDou-3 BDGIM and IGS GIM models in the polar region were evaluated based on the ionospheric TEC observations of Fengyun satellite in the Arctic and Antarctic in 2021 and 2023. The correction accuracy of four ionospheric models in the whole polar region, different places and different latitudes is analyzed respectively. The results show that the correction effect of the four ionospheric models in the Arctic is better than that in the Antarctic. The model deviation and standard deviation of the high solar activity year 2023 are significantly larger than those of the low solar activity year 2021. The RMS values of Klobuchar, NeQuickG, BDGIM and GIM models are 11.30, 5.74, 6.75 and 4.40 TECu, respectively, and the correction percentages are 33.34%, 58.81%, 44.87% and 65.32%, respectively. The correction percentages of GIM and NeQuickG fluctuate less with local time, while the correction percentages of BDGIM and Klobuchar change greatly with local time, and reach the maximum at 12:00—16:00 pm. The RMS value of Klobuchar fluctuates violently with latitude, which is basically not suitable for ionospheric correction in high latitudes. The RMS values of NeQuickG, BDGIM and GIM models change little with latitude, and the correction percentage generally decreases with the increase of latitude.

    LT-1 InSAR block adjustment considering the impact of penetration depth in forest areas
    Kefu WU, Haiqiang FU, Jianjun ZHU, Qijin HAN, Aichun WANG, Mingxia ZHANG, Zhiwei LI
    2025, 54(6):  1009-1020.  doi:10.11947/j.AGCS.2025.20240426
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    Due to its intense penetration, the first L-band interferometric SAR constellation, LuTan-1 (LT-1), has unique advantages in sub-canopy topography mapping. The block adjustment utilizes height control points (spaceborne LiDAR) and tie-points to calibrate the systematic error, which is the basis for LT-1 to carry out large-scale sub-canopy topography mapping. However, to avoid the problem of InSAR altimetry deviation from LiDAR caused by forest scattering, the existing block adjustment methods only select bare-earth points, which are prone to pathological observations with systematic error. Given this, this paper uses the SINC model that describes the forest scattering process to compensate for the InSAR altimetry deviation and establishes a block adjustment model considering the influence of penetration depth. We used two test sites with forest coverage of about 85% and 50% to verify the algorithm's effectiveness. The results show that the LT-1 DEM estimated in this paper improves the height accuracy by 22.1% and 12.5% compared with the traditional method, and the height accuracy and forest penetration rate are at the highest level compared with COP-DEM, SRTM, and AW3D. Furthermore, the LT-1 sub-canopy topography estimated based on the SINC model improved the height measurement accuracy by 40.6% and 25.5% compared with the LT-1 DEM, with RMSE of 3.15 m and 2.80 m, respectively.

    Fiber optic gyroscope total station temperature compensation algorithm based on BP neural network model
    Chenxi ZOU, Zhen SHI, Di LIU, Ziyi YANG
    2025, 54(6):  1021-1030.  doi:10.11947/j.AGCS.2025.20240467
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    Fiber optic gyroscope total station can determine the geographic north direction by sensing earth rotation. However, it is found that the temperature change is an important factor affecting the accuracy and stability of the fiber optic gyroscope. Based on the correlation analysis between the output data of fiber optic gyroscope and the temperature, a BP neural network modeling temperature compensation method for fiber optic gyroscope is designed. The temperature compensation experiment is designed to verify the feasibility and validity of the model. Compared with the common polynomial model, the zero-bias stability of the compensated gyro output is improved to some extent. The method has been applied to a coal mine's north-seeking orientation measurement and obtained certain orientation effect by comparing with the result of traverse measurement.

    Marine Survey
    Evaluation of the accuracy and spatial resolution of SWOT_02 marine gravity model in China's offshore regions
    Xiaodong CHEN, Meng YANG, Yuan YUAN, Wei FENG, Jinway HWANG, Min ZHONG
    2025, 54(6):  1031-1041.  doi:10.11947/j.AGCS.2025.20240487
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    The SWOT satellite, operating in a wide-swath interferometric altimeter mode, is expected to overcome the limitations of traditional nadir altimetry satellites for sea surface height observations, thereby improving the precision and spatial resolution of marine gravity anomaly measurements. In this study, shipborne gravity data provided by Sun Yat-sen University, National Yang Ming Chiao Tung University, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), and National Centers for Environmental Information (NCEI) were utilized to systematically evaluate the accuracy and power spectral characteristics of the SWOT_02, DTU21, V32.1, NSOAS24, and SDUST22 global gravity anomaly models over the Chinese coastal and offshore areas. Particular attention was given to assessing the performance of the SWOT_02 model, which incorporates data from the SWOT satellite, as an enhancement of the V32.1 model. Results indicate that, over the open ocean areas, the SWOT_02 model performs optimally. Specifically, the root mean square (RMS) of the differences between the SWOT_02 model and JAMSTEC shipborne gravity anomalies is less than 4 mGal, reflecting an improvement of approximately 1.3 mGal compared to the V32.1 model, with a corresponding relative accuracy enhancement of ~25%. Furthermore, the SWOT_02 model demonstrates the highest coherence with shipborne gravity anomalies across different wavelength bands, with its power spectral density in the wavelength range below 7 km outperforming those of the DTU21, V32.1, and NSOAS24 models. Additionally, in both the Chinese coastal seas and the deep-water regions of the South China Sea, comparison of spectral characteristics along shipborne survey tracks indicates that the SWOT_02 model exhibits significantly higher coherence with shipborne gravity anomalies provided by Sun Yat-sen University within the 7~60 km wavelength range compared to other models. Compared to other models, SWOT_02 demonstrates significantly improved coherence with seafloor topography at wavelengths shorter than 20 km. However, in some nearshore and shallow sea regions, the accuracy of the SWOT_02 model remains inferior to that of models such as DTU21 and SDUST22. This may be due to the limited quality of currently available SWOT observations, the relatively low accuracy of the base V32.1 model, and the lack of significant improvements in data processing methods for coastal areas. The complex nearshore environment poses substantial challenges for processing SWOT data, highlighting the need for further research to improve the accuracy of marine gravity anomaly models in coastal areas.

    Calibration of placement angle errors of airborne bathymetric LiDAR without field control
    Dianpeng SU, Bin WANG, Xiaozheng MAI, Huang MENG, Chao QI, Fanlin YANG
    2025, 54(6):  1042-1053.  doi:10.11947/j.AGCS.2025.20240185
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    Airborne LiDAR bathymetry (ALB) system is highly effective in acquiring integrated topographic data both land and underwater, making them particularly suitable for rapid exploration of complex terrains such as shallow water islands and reefs. However, the presence of misalignment errors between the laser bathymetric radar and the inertial measurement unit (IMU) can lead to uncertainty in the water depth measurements obtained from the bathymetric process. Aiming at the problems that there are no calibration control points on site in coastal areas and the sparse bathymetric radar point cloud makes it difficult to identify the features with the same name, this paper proposes a calibration algorithm for the placement angle error of airborne bathymetric LiDAR without on-site control. Initially, by constructing an optical zero error correction model that considers the distance differences of corresponding corners, optical zero deviations of internal code devices in the ALB system are corrected, laying the groundwork for installation angle calibration. Subsequently, a calibration model for installation angle deviations is established based on plane feature constraints, combined with random sample consensus (RANSAC) and the least squares adjustment method. The pitch angle error is calibrated with the minimum distance between the two planes in a single flight strip as a constraint; the roll angle error is calibrated with the minimum angle between the normal vectors of the two planes in a two-way flight strip as a constraint; the heading angle error is calibrated with the minimum distance between the centers of the spires of the characteristic buildings in a two-way flight strip as a constraint. Two ALB dataset captured from Mapper 20KU are utilized to verify effectiveness. Experimental results demonstrate that the root mean square errors (RMSE) of land points (compared to RTK-measured land points) and seabed points (compared to single-beam shipborne depth measurements) accuracy are 8.1 cm and 13.4 cm, respectively. The bathymetric result can satisfy the requirements of the “Marine Engineering Topographic Survey Specifications”. The proposed method can effectively reduce installation angle deviations of ALB, not only providing technical support for the refined processing of airborne LiDAR bathymetry data but also offering high-precision data for underwater topographic measurements in coastal areas. Consequently, this work promotes research and application development in marine science and hydrographic surveying fields.

    Photogrammetry and Remote Sensing
    Visual-perception-oriented LOD adaptive visualization for realistic 3D building scenes
    Haojia LIN, Renzhong GUO, Biao HE, Xi KUAI, Ding MA, Chengpeng LI
    2025, 54(6):  1054-1070.  doi:10.11947/j.AGCS.2025.20240347
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    Multi-resolution representation of 3D models is an important technique for visualizing 3D scenes. However, when it comes to visualizing realistic 3D building scenes with high realism, large scale span, and large data volume, problems such as inaccurate visualization quality metrics, discontinuous level switching, and unstable rendering efficiency make it difficult to maintain visual comfort during viewpoint transformation. This study proposes a visual-perception-oriented LOD adaptive visualization method for realistic 3D building scenes. Firstly, the process of 3D rendering and the mechanism of visual perception are considered comprehensively, and the visual perception process and characteristics of LOD visualization are summarized. Secondly, based on the transformation process of “3D space-screen space-visual perception”, the visual perception of simplified model errors in LOD visualization is quantified, and a visual-perception-based quality metric for LOD visualization is proposed. Finally, an LOD selection criterion is established based on the LOD visualization quality metric and the impact of visual attention and viewpoint motion. Combined with multi-threaded scheduling technology, an LOD adaptive scheduling method that considers visual perception characteristics is proposed. Experimental results demonstrate that the proposed method effectively maintains visual comfort during LOD switching, ensuring a dynamic balance between visual quality and operating efficiency. Furthermore, the method facilitates adaptive scheduling and rendering of LOD for realistic 3D building scenes according to human visual perception.

    A Markov model for estimating camera pose using target changes
    Jiayin LIU, Jiatian LI, Guokun CHEN, Xiaohui A, Jingjing WEI, Hao HU
    2025, 54(6):  1071-1081.  doi:10.11947/j.AGCS.2025.20230077
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    Different from the joint solution of object-image point correspondences for camera pose estimation, we propose a Markov model for estimating camera pose using target changes, which considers the pose parameters as random variables based on the observation of object changes. The specific contributions are as follows. Firstly, using the least squares method to obtain the Markov regression model for solving the state transition matrix. Secondly, based on the priori information, determining the pose transition matrix based on the a priori information to construct a Markov model about the pose parameters. Lastly, a multi-temporal attitude matrix is embedded to correct the pose estimation bias, resulting in a robust Markov pose model. The experimental results show that the Markov model performs well under translation, rotation and composite variations of the observed target, and can realize the effective estimation of camera pose, which can overcome the deficiencies of the existing methods in the case of restricted feature points.

    An efficient filtering method considering terrain features for large-scale airborne LiDAR point clouds
    Lianzhong XU, Chuanfa CHEN, Dongxing CHEN, Xingjie WANG, Ziming YANG, Shufan YANG, Zhuangzhuang HONG, Jinda HAO
    2025, 54(6):  1082-1093.  doi:10.11947/j.AGCS.2025.20240484
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    To solve the problems of low accuracy, slow computing speed and poor accuracy of the existing filtering methods for large-scale point cloud data in complex landscapes, an efficient filtering method considering terrain features for large-scale airborne LiDAR point clouds is proposed in this paper. Firstly, radius filtering and elevation histogram method are used to remove outliers from the raw point cloud. Secondly, a large number of evenly distributed ground seed points are efficiently extracted by combining the sliding grid with the M-estimation sample consistency algorithm. Then, the ground reference surface is constructed using a global weighted finite difference thin plate spline (TPS). Finally, a terrain-adaptive elevation threshold is designed to capture various types of ground points. In order to verify the effectiveness of the proposed method, a large-scale point cloud named OpenGF is used in the experiments. The results show that the average total error and Kappa coefficient of the proposed method are 2.45% and 94.54%, respectively, and its overall performance is much better than those of the 10 representative filtering methods. Moreover, the proposed method has a high computational efficiency.

    MAFNet: building extraction method from remote sensing images based on multi-scale atrous fusion network
    Zibo DONG, Jingxue WANG, Lijing BU, Lin FANG, Zhenghui XU
    2025, 54(6):  1094-1106.  doi:10.11947/j.AGCS.2025.20240439
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    Building extraction from remote sensing images is of great significance to disaster management, urban planning, and change monitoring. Due to the different sizes of urban buildings, there are buildings of multiple spatial scales in a remote sensing image, which makes the accuracy of building extraction in the image insufficient. In order to improve the extraction accuracy of buildings of different scales in the image, this paper proposes a remote sensing image building extraction method using a multi-scale atrous fusion network. Based on the U-Net network, the residual structure is first fused in the encoder and decoder parts to better propagate the gradient during the training process. At the same time, a multi-scale atrous fusion (MAF) module is proposed in the bridge part of the encoder-decoder. This module uses multiple atrous convolutions to capture global context features, and further enhances feature expression through channel and spatial attention mechanisms, effectively improving the extraction accuracy of buildings of different scales in the image. Finally, a hybrid loss function is designed to improve the overall boundary extraction effect. This paper conducts experiments based on the WHU building and Massachusetts building datasets, and compares the proposed method with the current mainstream semantic segmentation network. Experimental results show that the proposed method can significantly improve the accuracy of building extraction in images, can adapt to the extraction of buildings of various sizes, and can extract building boundaries more completely and smoothly.

    Cartography and Geoinformation
    Ship trajectories clustering method considering similarity in geometric position and mobility features
    Xiaoya AN, Weiru GUO, Pengxin ZHANG, Xinxin LI, Lei SHI
    2025, 54(6):  1107-1121.  doi:10.11947/j.AGCS.2025.20240384
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    With the widespread application of the automatic identification system (AIS) in maritime management, a large amount of vessel trajectory data is being recorded. By applying clustering analysis to this data, typical navigation routes and maritime area distribution information of vessels can be effectively mined, providing data support for shipping safety. However, existing clustering methods tend to focus on the spatial shape characteristics of vessel trajectories, and while some studies have addressed the movement characteristics of vessels, the exploration of deep-level information remains insufficient. This paper proposes a vessel trajectory clustering method that comprehensively considers both geometric position and movement feature similarity. Firstly, a trajectory classification model based on a one-dimensional convolutional neural network (U-net) is trained, and the feature vectors obtained before the model predicts the vessel type are used as deep-level features representing the vessel's movement pattern. Next, the Euclidean distance is employed to measure the similarity between these deep-level features, quantifying the similarity of vessel trajectories in terms of movement feature. Meanwhile, the Hausdorff distance is used to measure the geometric position similarity between different vessel trajectories. Subsequently, the fusion distance, combining geometric position and movement feature similarity, is calculated. Based on this distance, an adaptive density-based spatial clustering of applications with noise (DBSCAN) algorithm is applied for clustering analysis. Experimental results show that the proposed clustering method achieves superior clustering performance compared to baseline models in complex vessel trajectory application scenarios, effectively classifying trajectories with similar geometric shapes but different motion patterns into different clusters, thus providing more granular clustering results.

    From component to scene: basic concept, framework and application of scene construction
    Chen ZHANG, Biao HE, Weixi WANG, Ding MA, Xi KUAI, Renzhong GUO
    2025, 54(6):  1122-1138.  doi:10.11947/j.AGCS.2025.20240237
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    The concept of “digital twin” has gained considerable momentum in the past, primarily reflecting the increased production and accumulation of 3D data on the internet. This trend has led to new challenges in mirroring the physical world into the virtual one, as a high level of immersion is a prerequisite. However, the 3D modeling of urban scenes poses significant challenges because it demands a comprehensive mapping of all geographical entities including buildings, roads, vegetation, grasslands and many others. The diversity and complexity of urban scenes make it difficult to develop a universal 3D modeling method for each entity. This paper aims to outline a conceptual framework named “scene construction” for three requirements, i.e., realism, controllability, and volume of modelling. Firstly, we review the connotation of digital twin city and 3D real scene to derive a general introduction of scene construction. Then, we discuss the core concept of scene construction method based on reductionism. The method is detailed through a three-part framework of “deconstruction-representation-combination”. Furthermore, we present case studies on three typical urban objects: roads, ground, and grasslands. These case studies highlight the advantages of the proposed method in terms of realism, controllability, and volume. Finally, we contemplate the theoretical significance of the scene construction method from the perspective of cartography and list the key points in the subsequent research.

    Time optimal path planning method based on Gaussian mixture regression and improved A* algorithm
    Ruixin ZHANG, Qing XU, Zheng LÜ, Guo ZHANG, Xia CHU, Xiang CHENG
    2025, 54(6):  1139-1151.  doi:10.11947/j.AGCS.2025.20240478
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    Path planning plays an important role in emergency rescue and emergency rescue. In these scenarios, vehicles are often able to get faster routes through a combination of off-road and on-road routes. Therefore, a time optimal path planning method based on Gaussian mixture regression and improved A* algorithm is proposed. First, a time optimal traffic cost model is constructed using the A* algorithm combined with a vehicle speed coefficient, accounting for various factors affecting vehicle traffic, including road conditions. Second, the Gaussian mixture model is employed to collect trajectory information for the proposed rescue route. Combined with Gaussian mixture regression, this model constrains the search radius of the A* algorithm, enhancing its search efficiency. Finally, experimental verification is conducted using data from Dengfeng, Henan province. The results show that compared with the four algorithms of 2D A*, 3D A*, 2D time optimal A* and improved time optimal A* without Gaussian mixture regression constraints, the proposed algorithm reduces the path passage time by 2.02% to 32.31%, decreases code running time by 38.76% to 83.6%, and reduces node traversal by 38.69% to 79.77%. When compared to the recommended path from AutoNavi, the proposed algorithm shortens the path distance by 6.86% to 9.53% and reduces passage time by 8.41% to 17.22%.

    Summary of PhD Thesis
    Moon-based SAR system parameter analysis and InSAR deformation phase simulation for macro-scale solid Earth movement observation
    Dewei LI
    2025, 54(6):  1152-1152.  doi:10.11947/j.AGCS.2025.20230569
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    Virtual restoration of stained ancient calligraphy and paintings with hyperspectral data
    Pingping ZHOU
    2025, 54(6):  1153-1153.  doi:10.11947/j.AGCS.2025.20230576
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    Study on the theories and methods of geocenter motion estimation by fusing GNSS/ISL/SLR/LEO techniques
    Shiwei GUO
    2025, 54(6):  1154-1154.  doi:10.11947/j.AGCS.2025.20240003
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    Study on spatio-temporal variations and influencing factors of landslides in High Asia under climate change—a case study in the northern mountainous area of China-Pakistan Economic Corridor
    Jia LIU
    2025, 54(6):  1155-1155.  doi:10.11947/j.AGCS.2025.20240006
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    Research on positioning method of smart phone based on BDS/bluetooth array/PDR fusion
    Chenhui LI
    2025, 54(6):  1156-1156.  doi:10.11947/j.AGCS.2025.20240007
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