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    11 April 2025, Volume 54 Issue 3
    Review
    Prospects for the development of deep space navigation technologies
    Gang LI, Fang XIE, Yifan WU, Jun LU, Shuren GUO, Yingchun LIU, Chengeng SU, Xiaoheng YANG
    2025, 54(3):  397-409.  doi:10.11947/j.AGCS.2025.20230493
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    Deep space navigation is a fundamental element ensuring the efficient implementation of all kinds of deep space missions. With the substantial increase in the number of cislunar and Mars missions, as well as the great extension in distance of interplanetary missions, the entire process of spacecraft cruise, flyby, orbiting, descent landing, and surface activities pose increasingly higher demands for navigation. The traditional methods, such as deep space network, are hard to fulfill the requirements for multi-task, real-time and autonomous navigation. The main characteristics of deep space missions are analyzed, such as increasing in number, focusing on Moon and Mars, transforming from exploration to development and extending in distance. The paper summarizes three typical navigation requirements for cislunar transfer space, the outer space and surface of planets (like Moon and Mars), and ultra-far deep space. Then the paper studies the characteristics and trends of currently in-use, available and potential technologies. Moreover, the suggestions for the development of deep space navigation technology are proposed, including continuously improving the performance of in-use technologies, actively promoting the experimental deployment of available technologies, and strengthening the fundamental research of potential technologies. This study can provide reference for the technical development in the field of deep space navigation.

    Geodesy and Navigation
    A general method for determining the key parameters of GNSS water vapor tomography modeling
    Qingzhi ZHAO, Duoduo JIANG, Hongwu GUO, Zufeng LI, Chen LIU, Yibin YAO
    2025, 54(3):  410-421.  doi:10.11947/j.AGCS.2025.20240293
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    The existing global navigation satellite system (GNSS) water vapor tomography is mostly empirically selected in the determination of key parameters such as tomography height, vertical stratification, horizontal step size, etc., and lacks a general determination method, resulting in large differences in tomography results and difficulty in realizing the application of general water vapor tomography results. Because of this situation, this study proposes a theoretical method for determining the generality of key parameters of GNSS water vapor tomography to solve the problem that the optimal modeling parameters cannot be determined in the process of water vapor tomography. Firstly, the principle of determining the optimal height of the tomographic region by combining the vertical layered profile data and the water vapor density threshold is proposed. Secondly, the optimal vertical resolution determination method based on the equal weight principle of vertical stratified water vapor is proposed. Thirdly, considering the information on station density and satellite cut-off elevation angle, the optimal horizontal step size determination method based on the idea of joint grid coverage maximization and non-uniform symmetric horizontal grid division is developed. The data of 12 GNSS stations and 1 radiosonde station in Hong Kong from May 1 to 14, 2013 were selected for experiments. Compared with the existing classical methods, compared with radiosonde data, the average improvement rate of the retrieved water vapor density profile is 12%. Compared with the slant water vapor (SWV) calculated by the fifth-generation reanalysis dataset (ERA5) released by the European Centre for medium range weather forecasts (ECMWF), the average improvement rate of SWV obtained by the proposed scheme is 29.5%.

    An index of multicollinearity diagnosis based on Rayleigh quotient
    Xinna LI, Songhui HAN, Ke CHEN, Jie GUO
    2025, 54(3):  422-431.  doi:10.11947/j.AGCS.2025.20240338
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    Multicollinearity widely exists in measurement data processing, and its harms are very serious. The premise of effective treatment of multicollinearity problem is to effectively diagnose and measure the multicollinearity of design matrix. In view of the shortcomings of multicollinearity indicators such as the condition number and orthogonal degree of matrix, based on the nature of multicollinearity, the paper adopts the Rayleigh quotient of normal matrix as the measure of linear correlation between the array vectors of the design matrix, and proposes a multicollinearity indicator according to the properties of the Rayleigh quotient and the eigenvalues of the edge-matrix. This indicator can be used to diagnose multiple multicollinearity relationships. The effectiveness and superiority of the proposed indicator for multicollinearity diagnosis are demonstrated by experiments. When the multicollinearity relationships are strong, the rate of accuracy in diagnosing the multicollinearitycan reach 100%. When the multicollinearity relationships are weak, the diagnostic accuracy is 84.9%, and by adjusting the threshold, the diagnostic accuracy can be increased to 99.8%.

    Consistency analysis of GNSS precise orbit and clock products based on globally unified coordinate frame
    Xuexi LIU, Shouqing ZHU, Guo CHEN, Kefei ZHANG, Nanshan ZHENG, Jingxuan LIU
    2025, 54(3):  432-447.  doi:10.11947/j.AGCS.2025.20240248
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    Precise satellite orbit and clock offset are the key to fast fixing undifferenced ambiguity and achieving high-precision positioning services. The combination of orbit and clock offset product requires the unification of the spatial and temporal references between products from different analysis centers. This paper first solved for the Bursa coordinate transformation parameters to analysis the difference of similar transformation parameters between the precise satellite orbit products provided by different analysis centers, and statistically calculated the correlation coefficient between the similar transformation parameters of each system of analysis centers. Secondly, the benchmark differences of the precise clock products are analyzed and it is found that there is a significant constant bias in the linear transformation by estimating a set of linear transformation parameters using the clock data of all the satellites. The GPS and Galileo have a constant deviation of up to 200 ps, while the constant deviation of the GLONASS and BDS can reach 1000 ps and 2400 ps respectively. In this paper, we propose a method to eliminate this constant bias by estimating a set of linear transformation parameters for each satellite clock. Thirdly, this paper analyses the benchmark consistency between the orbital and station coordinates and the Earth's rotation parameter products. The correlation coefficients of most of the rotational components are more than 0.5, which indicates that the orientation benchmark differences are more consistent among the analysis centers. Finally, the consistency of orbit and clock is analyzed by making the double difference of orbit and clock. After removing the constant deviation of clock, most of the correlation coefficients of the double difference of orbit and clock of GPS and Galileo are more than 0.9, and the correlation coefficients of GLONASS and BDS are a little bit worse but the correlation coefficients also exceed 0.6. This indicates that the nonlinear parts of the second difference between the precision satellite orbits and the clock products are more consistent, showing a high degree of conformity between orbital changes and clock variations.

    A thermal-inertial odometry with point and line fusion for the weak textured dark scenes
    Luguang LAI, Dongqing ZHAO, Linyang LI, Wenzhe FAN, Xiongqing LI, Pengfei LI
    2025, 54(3):  448-460.  doi:10.11947/j.AGCS.2025.20240251
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    Traditional visual SLAM performs poorly or even fails to work in challenging environments such as significant changes in light conditions, darkness, smoke, and fog. In contrast, infrared cameras possess greater anti-interference capabilities. Nevertheless, the performance of infrared SLAM is severely affected by the poor imaging quality and noise of infrared cameras. In this paper, a point and line fusion infrared inertial odometry method is proposed, which is based on the thermal radiation imaging characteristics of infrared cameras and considers the weak texture characteristics in structured scenes. In the front-end, a point tracking algorithm based on the optical flow method is employed with a filtering process to eliminate unstable point features. The LSD algorithm is enhanced to extract stable line features, and line feature tracking is conducted using the LBD descriptor. A sliding window in the back-end is used to construct a tightly coupled graph optimization model that includes point, line, and IMU information. Finally, validation is conducted using open-source datasets and measured data from underground garages, respectively. The results demonstrate that the accuracy and robustness of the point-line combined thermal inertial odometer are significantly improved compared to traditional visual SLAM algorithms, which helps unmanned systems achieve robust localization in dark and weakly textured scenes.

    A regional geomagnetic field model for China based on Swarm satellite data and 3D Legendre polynomials
    Bo ZHU, Houpu LI, Libo ZHU, Shaofeng BIAN, Cheng CHEN
    2025, 54(3):  461-472.  doi:10.11947/j.AGCS.2025.20240379
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    Regional geomagnetic field models can provide detailed information about the geomagnetic field, with significant applications in precise navigation and target detection. To establish a high-precision regional geomagnetic field model for China, this study integrates Swarm satellite data to investigate the 3D Legendre polynomial model and proposes an enhanced solution method based on singular value decomposition to improve accuracy at higher degrees. Concurrently, the optimal truncation degree of the Legendre polynomial model for each geomagnetic component is determined using K-fold cross-validation. Comparative experiments with Taylor polynomial models, Laguerre polynomial models, and Chebyshev polynomial models validate the advantages of the Legendre polynomial model in terms of truncation degree, computational speed, modeling accuracy, and boundary effects; with overall fitting errors for each component as low as 0.055 nT and boundary errors reaching a minimum of 0.074 nT. Further comparisons with other regional geomagnetic field models and WMM2020 calculation results confirm both the effectiveness and precision advantages of the proposed method along with its corresponding regional geomagnetic field model.

    Inspection capacity index (ICI)—a sampling scheme measure of quality inspection of surveying and mapping products
    Yanhui CAI, Pengfei CHENG, Li ZHANG
    2025, 54(3):  473-480.  doi:10.11947/j.AGCS.2025.20230443
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    Based on the theory of the acceptance probability of cumulative hyper-geometric distribution, the paper analyzes the essence of the consistency problem of sampling plan series and proposes the concept of inspection capacity (IC) for sampling inspection by defining inspection capacity index (ICI) function with acceptance probability and logarithm of lot size, which provides a method to evaluate quantity indicators of sampling plan. Based on the actual application of quality inspection of surveying and mapping products and operating characteristic (OC) curves method, an approach, called inspection characteristic (ICC) curve, was developed to analyze the differences between two sampling plans. The numerical results of 7 typical sampling plans show that the ICI value can better reflect overall characteristics of sampling plan. The ICC analyzing results indicate the consistency prior AQL interval of the 7 typical sampling plans should be 0.3%~1.0%, and the optimal AQL value is 0.6%. It is not only significant for the theoretical analysis of the prior quality level that the surveying and mapping products needed, but also for the management of smart surveying and the multi-sourced geo-information data's quality and reliability analyzing.

    Comprehensive analysis of multiple monitoring methods in main subsidence areas
    Zhaofeng DU, Guopeng LI, Zhanke LIU, Xiaming SHANG, Shengjun KANG, Xiaoqiang WANG
    2025, 54(3):  481-492.  doi:10.11947/j.AGCS.2025.20230141
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    The land subsidence accumulated over years in the North China Plain has become an increasingly serious geological environment problem. Based on the monitoring results of InSAR vertical deformation field, multi-source data was fused to build a unified datum vertical deformation field from the information extraction results of surface vertical changes of continuously operation reference stations (CORS) and geodetic control points in the North China Plain, and the elevation change data of leveling points were used for comparative verification. In response to the issues of poor current status and low accuracy of national elevation datum caused by land subsidence, the characteristics and impact of changes in national elevation datum point was analyzed in main subsidence areas. Furthermore, a regional remeasurement scheme was developed to achieve dynamic updates and maintenance of the national elevation datum in a regional way. The regional remeasurement of the national elevation datum point can not only save the investment in remeasurement the entire control network of the national elevation datum, avoid the cost of repetitive construction, but also meet the construction needs of major national strategic projects.

    Photogrammetry and Remote Sensing
    Digital orthophoto map encryption based on QR code and GS phase retrieval
    Jun WU, Yiren SHEN, Gang XU, Xuemei ZHAO
    2025, 54(3):  493-509.  doi:10.11947/j.AGCS.2025.20230053
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    To address the protection and secure transmission of digital orthophoto map (DOM) information in network environments, this study proposes a novel DOM encryption method that combines QR code and GS phase retrieval in two stages: ① The image data (RGB channels) of the DOM is encoded using the GS algorithm to generate three phase-only holograms. These holograms are scrambled and diffused using pseudorandom sequences generated by the Lorenz hyperchaotic system, enhancing the sensitivity of the optical keys and the ciphertext's sensitivity to plaintext changes through chaotic system properties and diffusion mechanisms. ② The geographic information of the DOM, along with partial keys and user authorization information, are encoded into a QR code and embedded into the three phase-only holograms. The three holograms with embedded QR codes are then synthesized into a meaningless white noise color image, serving as the final ciphertext. Experimental results for DOM in different scenes demonstrate that this method achieves unified encryption of both the DOM image data and geographic information. The decrypted images are highly consistent with the original plaintext images, achieving a peak signal-to-noise ratio of over 39 dB. Evaluation metrics including the correlation coefficient, structural similarity index measure, change rate of pixel number, and normalized change intensity, are close to their ideal values, outperforming existing methods. In addition to traditional chaos parameters, the GS parameters, such as diffraction distance and reference light wavelength, serve as the key, ensuring the method has a large key space (approximately 10141). Minor changes to the plaintext completely alter the ciphertext, and pixel values are statistically independent. The method exhibits strong robustness against ciphertext-only attacks, known-plaintext attacks, chosen-plaintext attacks, chosen-ciphertext attacks, and noise attacks, making it highly valuable for the protection and secure transmission of raster geographic data, including DOM.

    Analysis of the spatio-temporal evolution and driving factors of urban ecological quality based on long-term Landsat image time series
    Yonggang GAO, Yuting LIU, Hanqiu XU
    2025, 54(3):  510-522.  doi:10.11947/j.AGCS.2025.20240147
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    Analyzing the spatio-temporal evolution of urban ecological quality and its driving factors is crucial for regional environmental protection and sustainable development. This paper presents a robust analytical framework for urban ecological quality evaluation based on multi-temporal Landsat satellite remote sensing imagery and auxiliary data. The framework integrates the remote sensing ecological index (RSEI) with Theil-Sen estimation, Mann-Kendall trend test, Hurst index, optimal parameters-based geographical detectors (OPGD), and multi-scale geographically weighted regression (MGWR). To verify its applicability and effectiveness in the context of rapid urbanization, this framework was used to investigate ecological quality changes and influencing factors in Dongguan city over the past 20 years. The results show that Dongguan's ecological environment has undergone a complex dynamic process of deterioration-improvement-re-deterioration during the 20-year period. Furthermore, forward-looking predictive analysis identified key areas of future ecological change and regions facing severe ecological risks as well as those with significant improvement potential. This comprehensive analysis provides scientific support for ecological management in Dongguan and offers valuable insights for similar regions undergoing rapid urbanization.

    A dynamic weighted fusion SLAM method using multi-source sensor data in complex underground spaces
    Xiaohu LIN, Xin YANG, Wanqiang YAO, Hongwei MA, Bolin MA, Xiongwei MA
    2025, 54(3):  523-535.  doi:10.11947/j.AGCS.2025.20230586
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    Simultaneous localization and mapping (SLAM) is pivotal for autonomous detection, automatic inspection, and emergency rescue in underground spaces. However, the challenges of narrow and long tunnels, complex terrain, and uneven illumination in underground spaces make LiDAR point cloud and visual image matching highly susceptible to degradation. This, in turn, results in insufficient accuracy or even failure of SLAM when fusing multi-sensor data. To address this challenge, we propose a dynamic weighted fusion SLAM method for multi-source sensor data with enhanced robustness. First, during the visual image preprocessing stage, an image enhancement technique based on the hue, saturation, and value (HSV) color space is employed. This method combines single-parameter homomorphic filtering with contrast limited adaptive histogram equalization (CLAHE) to effectively enhance the brightness and contrast of the image. This improvement strengthens the robustness of visual odometry. Next, the data quality of each sensor is evaluated using a Mahalanobis distance consistency test, which analyzes potential data degradation and adaptively selects the most suitable sensor data for fusion based on the current scene. Finally, considering the key parameters of each sensor, we construct the multi-source sensor factor graph model. The dynamic combination of multi-source sensor data weights is then formed according to the data quality model, allowing for the dynamic adjustment of the weight of each sensor data fusion factor. To verify the effectiveness of the proposed method, experiments were conducted in typical underground spaces such as underground corridors, excavated subway tunnels, and coal mine tunnels using self-designed and integrated mobile robots. Qualitative and quantitative comparative analyses were performed against various state-of-the-art methods. The results demonstrate that the maximum root mean square error (RMSE) of the proposed method is only 0.19 m. The average cloud to cloud (C2C) distance is less than 0.13 m, referencing the point cloud acquired by high-precision terrestrial 3D laser scanning. Additionally, the constructed point cloud maps exhibit superior global consistency and geometric structure authenticity. These findings confirm that the proposed method offers higher accuracy and robustness in complex underground spaces.

    Cartography and Geoinformation
    Method for discovering spatial causality in geological hazards guided by spatial association patterns
    Bingrong CHEN, Kaiqi CHEN, Min DENG, Cheng HUANG, Qinghao LIU
    2025, 54(3):  536-551.  doi:10.11947/j.AGCS.2025.20240279
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    Spatial causality is a core approach for understanding the patterns of geographic phenomena, as it can reveal the driving factors and causal mechanisms behind geological hazards like landslides and debris flows. This insight provides essential technical support for hazard tracing and emergency management. Existing causal discovery methods, not originally developed for geographic research, often overlook spatial location constraints, making them inadequate for effectively detecting spatial causal relationships in geographic phenomena. To address this gap, this paper introduces a Spatial-PC causal discovery method from a spatial association perspective, incorporating models for causality and direction determination using spatial conditional mutual information and spatial partial correlation tests. This method enables effective detection of spatial causality under location constraints. Specifically, we applied the approach to geological hazards in Yunnan province, China, utilizing the Apriori algorithm to identify spatial association patterns, then applying spatial conditional mutual information to filter out spatial causality, and spatial partial correlation tests to determine causal directions, ultimately constructing a spatial causality graph. The study's findings effectively elucidate the mechanisms driving geological hazards in Yunnan province, supporting precise hazard prevention and control.

    A bivariate spatio-temporal association analysis method for aggregated flows
    Qingyang FU, Mengjie ZHOU, Yige LI, Weitao CHEN
    2025, 54(3):  552-562.  doi:10.11947/j.AGCS.2025.20240011
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    Aggregated flows can reflect the spatio-temporal interactions between different spatial areas from the group perspective, and often contain non-spatial attributes that describe quantitative characteristics, such as the migratory intensity of population flows. Analyzing the spatio-temporal association between two non-spatial attributes of aggregated flows can reveal the interaction patterns between different flow attributes, which helps to understand the intrinsic occurrence mechanisms of dynamic interaction phenomena in geographic space. However, there is still a lack of spatio-temporal statistical indicators to evaluate the association degree between two flow attributes, and the understanding of the asymmetry and spatio-temporal heterogeneity of the association remains inadequate. Therefore, this paper proposes a bivariate spatio-temporal association analysis method for aggregated flows. It establishes spatio-temporal weights for aggregated flows to express their spatio-temporal adjacency relationships. Then, it constructs the global and local bivariate flow spatio-temporal Moran's I to assess the asymmetric spatio-temporal association degree between two flow attributes, and identify the local spatio-temporal association patterns and their dynamic variations. The synthetic test results verify that the method can effectively uncover the global and local spatio-temporal association patterns between two flow attributes, and the appropriate scale of spatio-temporal association analysis is also identified through parameter sensitivity tests. The practical application results reveal the spatio-temporal associations between intercity search behavior and travel activities in Shandong, which can provide a theoretical basis for in-depth analysis of urban attractiveness from virtual and real perspectives.

    A method for automatic buildings aggregation constrained by proximity edges
    Youneng SU, Qing XU, Qun SUN, Xinming ZHU, Fubing ZHANG, Bo LIU
    2025, 54(3):  563-576.  doi:10.11947/j.AGCS.2025.20240138
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    Aggregation of large scale buildings is a difficult problem in the field of map generalization. In order to maintain the characteristic consistency of the building's shape before and after the aggregation, a method for automatic buildings aggregation constrained by proximity edges was proposed in this paper. The method firstly used the Delaunay triangulation networks to determine the proximity relations between buildings, generated the proximity edges of buildings with the constraint of the minimum bounding rectangle of buildings, and divided the spatial structural relations of buildings into the alignment types and the dislocation types according to the projection proportions of the minimum external rectangles of buildings. Secondly, the proximity edges interactive projection method and the proximity edges angular bisector method were proposed for the combination of the aligned and the dislocated buildings, respectively. Finally, the validity of the proposed method was verified with the experimental data of Shanghai residential land. The results showed that the proposed method could effectively merge buildings under different structural relations and merging thresholds, and effectively expressed the spatial structural characteristics and the right-angle characteristics of residential lands under the control of a certain area increment.

    Summary of PhD Thesis
    The instability of polar ice shelf based on remote sensing observation and ISSM numerical modeling
    Daan LI
    2025, 54(3):  577-577.  doi:10.11947/j.AGCS.2025.20230466
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    Spatiotemporal modelling and risk assessment of regional land subsidence based on recurrent neural network
    Huijun LI
    2025, 54(3):  578-578.  doi:10.11947/j.AGCS.2025.20230470
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    Research on the determination of geopotential by multi-frequency and multi-mode GNSS carrier phase time and frequency signal
    Wei XU
    2025, 54(3):  579-579.  doi:10.11947/j.AGCS.2025.20230478
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    Geometry-vector-based model for terrain derivatives calculation
    Guanghui HU
    2025, 54(3):  580-580.  doi:10.11947/j.AGCS.2025.20230485
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    Remote sensing retrieval of suspended sediment concentration and particle size in turbid estuarine and nearshore waters and its application
    Wei LUO
    2025, 54(3):  581-581.  doi:10.11947/j.AGCS.2025.20230487
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    Research on man-made target detection of high-spatial resolution remote sensing imagery based on multi-scale morphological features
    Junjun LI
    2025, 54(3):  582-582.  doi:10.11947/j.AGCS.2025.20230495
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    Research on theory and method of on-orbit calibration of GRACE-type gravity satellite payloads
    Zhiyong HUANG
    2025, 54(3):  583-583.  doi:10.11947/j.AGCS.2025.20230499
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    Research and application of key technologies for deep-sea cold seep detection
    Sai MEI
    2025, 54(3):  584-584.  doi:10.11947/j.AGCS.2025.20230505
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