15 October 2025, Volume 45 Issue 10
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Journal of Geodesy and Geodynamics. 2025, 45(10): 991-996, 1070. https://doi.org/10.14075/j.jgg.2025.02.026
By collecting achievements in the medium- to long-term prediction of strong earthquakes, an in-depth analysis of the commonalities and differences between vertical deformations observed by the Global Navigation Satellite System(GNSS) and leveling measurements was conducted. The related issues of abnormal uplifts before major earthquakes were explored, including the abnormal fluctuations of leveling and their differences from GNSS observation results. Through the analysis of years of precise leveling data, the abnormal phenomenon of ground uplift before major earthquakes was revealed. Combining this with research findings on gravity anomalies before major earthquakes, a theoretical deduction and analysis of the relationship between the two was conducted. The vertical deformation data obtained from leveling measurements not only includes the effects of point-wise vertical geometric deformation but also contains information about the dynamic bending of the local gravity level surface, with magnitudes reaching 2 mm or more. Based on this, the concepts of physical deformation and geometric deformation were proposed. The research in this paper is of significant theoretical and practical importance for correctly understanding the differences in deformation mechanisms, the medium- to long-term prediction of strong earthquakes, and the formulation of deformation anomaly monitoring plans and decision-making.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 997-1005. https://doi.org/10.14075/j.jgg.2024.09.443
By dividing the seismic cycles of MS≥7.8 earthquakes in China's mainland and adjacent regions and studying the migration of main active zones, combined with the acceleration-deceleration changes of Earth's rotation speed, this study explores the spatiotemporal patterns and driving mechanisms of M8.0 seismic activity in the study area. The main conclusions are as follows: 1) Since 1879, the study area has experienced 6 active periods of M8.0 earthquakes. The second active period mainly occurred in the Pamir-Baikal seismic belt, the third in the northeastern margin of the Qinghai-Xizang plateau, the fourth in the southeastern margin, the fifth in Yunnan and north China, and the sixth around the Bayan Har block within the Qinghai-Xizang plateau. The region may currently be in the initial stage of a new active period. 2) Since 1867, Earth's length of day(LOD) variation curve shows 4 acceleration-deceleration cycles and 16 acceleration-deceleration phases. The superposition of S tectonic stress fields with deceleration changes favors M8.0 earthquakes in the Pamir-Baikal belt, while NE-oriented stress fields combined with acceleration changes facilitate M8.0 earthquakes along the Qinghai-Xizang plateau margins and interior. The transition from acceleration to deceleration phases causes the tectonic stress field around the Qinghai-Xizang plateau to shift from NE-dominated to locally restored NS orientation, serving as the main driver for the third, fourth, and sixth active periods. 3) The tectonic stress field in China's mainland and adjacent regions has experienced clockwise rotation from NS to NE and then to NEE orientations over the past century, potentially related to Earth's rotation changes involving significant deceleration before 1913 followed by overall acceleration. This process remains ongoing, with no current signs of concentrated M8.0 earthquakes similar to the second active period. However, vigilance is needed regarding possible continued NEE rotation of the Qinghai-Xizang plateau's stress field, and future emergence of new main active zones cannot be ruled out.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1006-1012. https://doi.org/10.14075/j.jgg.2024.09.447
Based on continuous GNSS observation data, a relatively comprehensive three-dimensional GNSS velocity field for the northeastern margin of the Qinghai-Xizang plateau was established by fully considering random noise and regional environmental loading. This study characterizes crustal strain and vertical motion patterns in the research area. Results show that the region is dominated by compressive strain, with significant differences in principal strain rates between its southwestern and northeastern sectors. Notable distributions of maximum shear strain and principal strain are observed along the east Kunlun fault and Xianshuihe fault. Vertical uplift predominates across the northeastern Qinghai-Xizang plateau, suggesting that vertical tectonic forces may originate from intra-block compressional shortening or obstruction of deep lithospheric material flow. However, significant surface subsidence near the Lanzhou area is likely attributed to collapsible loess and soil erosion. Finally, estimates based on an incompressible Earth model indicate minimal vertical deformation caused by horizontal compression, implying that large-scale uplift in the northeastern Qinghai-Xizang plateau may primarily result from vertical tectonic factors such as lower crustal flow and lithospheric convective thinning, rather than horizontal crustal shortening.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1013-1019. https://doi.org/10.14075/j.jgg.2024.09.458
Taking the hilly open-pit mining area in central Shandong as the study region, this research analyzes the impacts of different DEMs(SRTM-1, SRTM-3, ALOS-DEM, ASTER-GDEM, and LiDAR-DEM) and their elevation accuracy/spatial resolution on SBAS-InSAR deformation monitoring performance and geometric distortion identification. Results demonstrate that compared to spatial resolution, DEM elevation accuracy plays a more critical role in deformation monitoring and significantly affects measurement precision. Both DEM elevation accuracy and spatial resolution substantially influence the identification of shadow and layover areas. These findings provide guidance for DEM data selection in subsequent time-series deformation monitoring in complex terrains.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1020-1025. https://doi.org/10.14075/j.jgg.2024.10.482
Based on observation data from 77 GNSS stations worldwide, this study systematically evaluates the global applicability of four tropospheric delay mapping function models(GMF, NMF, VMF1, VMF3) and their impact on the accuracy of precise point positioning(PPP). The zenith tropospheric delay(ZTD) for each station was obtained using the PRIDE PPP-AR software. With the ZTD products released by the Center for Orbit Determination in Europe(CODE) as a reference, a comparative analysis of model performance was conducted across geographical zones(low/medium/high latitudes, land/ocean, and altitude gradients). The results indicate that the existing tropospheric delay mapping function models exhibit poorer accuracy in low-latitude, low-altitude, and oceanic regions. The VMF series mapping function models perform better in addressing differences arising from changes in altitude and latitude, and both the GMF and VMF series models show significant correction effects for oceanic stations. In terms of positioning accuracy in the U direction, the GMF, VMF3, and NMF mapping function models perform best in low-latitude, medium-latitude, and high-latitude regions, respectively. Overall, the GMF and VMF series mapping function models demonstrate superior performance in global PPP data processing.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1026-1032, 1100. https://doi.org/10.14075/j.jgg.2024.10.485
A wideband signal extraction method based on normal time-frequency transform(NTFT-WSE) is proposed based on standard time-frequency theory. First, the standard time-frequency transform is used to extract and model the periodic signals of sea level. Then, the NTFT-WSE method is employed to extract, model, and predict the components at different time scales, achieving accurate prediction of the periodic low-frequency signals of sea level changes. Compared with the standard Morlet wavelet transform, the NTFT-WSE method reduces the root mean square error(RMSE) and mean absolute error(MAE) in periodic signal extraction by 26.03% and 22.24%, respectively, significantly improving the extraction accuracy of mid- and low-frequency signals. Finally, based on satellite altimetry sea level anomaly data from June 1993 to May 2008, the NTFT-WSE method was used to predict the sea level changes in the South China Sea from June 2008 to May 2023. The prediction results are consistent with the overall trend of actual observations.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1033-1036. https://doi.org/10.14075/j.jgg.2024.11.504
This paper utilizes the ERA5 multi-element dataset to predict ERA5 water vapor by integrating the fast Fourier transform(FFT) and convolutional long short-term memory(ConvLSTM) methods. Firstly, the common periods of various meteorological elements are extracted using FFT. Subsequently, multiple meteorological elements with different common periods and individual water vapor data are selected as model inputs, and the ConvLSTM method is employed to train the ERA5 water vapor and construct the prediction model. Finally, the prediction performance of the model for point and spatial water vapor is evaluated using GNSS water vapor and actual ERA5 water vapor. The results indicate that the ERA5 water vapor prediction method based on FFT and ConvLSTM can effectively predict water vapor for the next 120 hours, with high accuracy in both single-point and spatial areas, providing a data foundation for short-term precipitation warnings.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1037-1042. https://doi.org/10.14075/j.jgg.2024.10.493
Based on nearly one year of GNSS-R data from the GNSS occultation sounder Ⅱ(GNOS-Ⅱ) onboard the Fengyun-3E(FY-3E) satellite, this study conducted global soil moisture inversion modeling and evaluated the inversion results from different satellite systems and their combined observations. The results indicate that there are systematic biases in the reflectivity distributions calibrated by the reflected signals of BDS, GPS, and Galileo. However, the inversion results based on different systems have similar accuracy. The predicted soil moisture values show good consistency with the level 3 soil moisture products provided by the SMAP satellite, with a correlation coefficient of 0.855 and an unbiased root mean square error of 0.063 cm3/cm3. When combining different systems for inversion, the cumulative distribution function matching method was used to recalibrate the effective reflectivity of each satellite system's observations, which further improved the accuracy of surface soil moisture inversion.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1043-1048. https://doi.org/10.14075/j.jgg.2024.11.528
To enhance the filtering performance of the maximum correntropy Kalman filter(MCKF) method in complex environments, an adaptive maximum correntropy Kalman filter algorithm(AMCKF) for GNSS/SINS integrated navigation systems is proposed. Firstly, based on the relationship between the filtering fault detection function values at the current and the past (l-1) time steps and the detection threshold, two mapping relationships of 0 and 1 are formed. Then, a window of length l is constructed using the mapped values, and a kernel width adaptive adjustment algorithm is proposed. Finally, this kernel width adaptive adjustment algorithm is applied to MCKF to form the AMCKF algorithm for the integrated navigation system. Experiments are conducted on a GNSS/SINS integrated navigation system under measurement environments with Gaussian white noise and heavy-tailed impulsive noise. The results indicate that AMCKF can adaptively adjust the kernel width value according to different measurement noise environments, thereby improving the filtering accuracy of the integrated navigation system. Compared with KF and MCKF, AMCKF can improve position accuracy by approximately 26.5% and 16.4%, respectively, and improve velocity accuracy by approximately 15.5% and 6.4%, respectively.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1049-1056. https://doi.org/10.14075/j.jgg.2024.09.442
To address the limitations of traditional RAIM algorithms, including abnormal fault detection and insensitivity to small faults, we introduce the concept of variance inflation from robust estimation into receiver autonomous integrity monitoring(RAIM). A RAIM algorithm combing variance inflation model is proposed, with an improved fault handling process. Integrity determination is performed using the user's protection level based on positioning uncertainty, and multi-constellation simulations and real-world tests in complex environments are conducted. The simulation results show that the proposed method can accurately detect a significant fault of 30 meters and effectively mitigate the impact of a small 5-meter fault on positioning results, successfully restoring the positioning error level to the state before the fault is introduced. The real-world test results show that the proposed method achieves horizontal and vertical availability rates of 95.38% and 98.74%, respectively, which are 11.63% and 5.06% higher than traditional RAIM algorithms. In terms of positioning accuracy, compared to traditional RAIM algorithms, the proposed method improves precision in E, N, U directions by 23.03%, 11.68%, and 26.79%, respectively.
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Estimation of Grid Search Algorithm of Seamount Morphology Using Vertical Gravity Gradient AnomaliesJournal of Geodesy and Geodynamics. 2025, 45(10): 1057-1064. https://doi.org/10.14075/j.jgg.2024.11.533
Seamounts are previously approximated as an axisymmetric Gaussian shape, and the vertical gravity gradient(VGG) anomalies combined with ship-track bathymetry data are used to evaluate seamount morphology. However, there are significant challenges in describing the complex morphology of seamounts. Therefore, we classify seamounts into two distinct types: conical and elliptical conical shapes, which can be determined by three and five parameters, respectively. We perform a grid search on seamount parameters, obtaining VGG anomalies corresponding to each parameter through forward calculation. The forward VGG anomalies are compared with the observed VGG anomalies, and the minimal root mean square(RMS) error between them is used as a search criterion for estimating. We validate the effectiveness of grid search algorithm through numerical simulations, and apply it to practical examples. The estimation results are compared with multi-beam bathymetry data, the RMS errors ranging from 150 m to 640 m, and the fitting of VGG anomalies is within 8 Eötvös.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1065-1070. https://doi.org/10.14075/j.jgg.2024.09.421
We propose a bathymetric prediction method based on a dual-channel BP neural network, integrate gravity anomaly data(including long-wave, short-wave, and residual gravity anomalies) and shipborne bathymetry data to predict seafloor topography in the gulf of Guinea. The prediction results are compared with those obtained from gravity geology methods and the GEBCO_2023 and Topo_25.1 models. The results show that dual-channel BP neural network-based inversion achieves superior accuracy compared to other models. This study can provide new insights into applying deep learning in marine geodesy and enhances the accuracy of seafloor topography inversion.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1071-1078. https://doi.org/10.14075/j.jgg.2024.10.470
This article utilizes observational data from seven geoelectric field stations in the Shandong region starting in 2021. It determines the dominant azimuth angle α of the geoelectric field using a geoelectric rock mass fracture model. The jumping range Δα did not meet the criteria for judgment and did not meet the abnormal indicators. According to the prediction rules of this method, it is analyzed that the probability of a moderate to strong earthquake occurring in Shandong region in the near future is not high. Based on the analysis of the development of rock fractures in the site reflected by the advantageous azimuth results, the results show that the rock fractures in Heze station located on the east side of the Liaokao fault zone and Zoucheng station located between the Cangshan-Nishan fault zone and Fushan fault zone are in the generation stage, which is a common background for the development of small and medium-sized earthquakes area. The rock fractures of Anqiu station and Lingyang station located in the northern section of the Yishu fault zone and Rushan station on the east side of the Muping-Jimo fault zone are in the stage of development or growth, which is in line with the background of nurturing moderate to strong earthquakes and deserves special attention.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1079-1084. https://doi.org/10.14075/j.jgg.2024.11.499
Aiming at the problems of wireless node seismometer can not be accurately located and may be lost in the field under complex exploration environment, the study of UHF RFID high-precision ranging and positioning is of great significance. Firstly, we use the received signal strength indicator(RSSI) approximation calculation formula to sieve out the sampling values with large errors. Then, two optimization objective functions of the third-generation non-dominated sorting genetic algorithm(NSGA-Ⅲ) are designed, whose independent variables are one-dimensional convolutional neural network(1D-CNN) hyper-parameters, such as learning rate decreasing factor, initial learning rate, and batch size, and whose dependent variables are determination coefficient(R2) and mean bias error(MBE) of network prediction and theoretical values. Finally, the best hyperparameter values are used to form a new model of NSGAⅢ-1D-CNN, which is designed to improve the stability and accuracy of RFID ranging model. The prediction experiments show that the new model has a small prediction error of node seismometer RFID ranging under 100 rounds of cyclic experiments, and its performance is excellent in several indexes, such as R2, root mean square error(RMSE), mean absolute error(MAE), MBE, with the mean values of 0.977 9, 0.058 6 m, 0.047 2 m, -0.001 3 m, respectively, which has higher ranging and positioning accuracy compared with other models. The new model has certain application value in field physical exploration.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1085-1092. https://doi.org/10.14075/j.jgg.2024.09.432
This study aims to examine the monitoring and early warning abilities of the Yunnan seismic station network using the 72 h continuous waveform recordings recorded at 2 060 stations. The evaluation index used was the maximum probability peak displacement(PGD) of background noise at each station. The findings revealed that the average monitoring capacity of the Yunnan seismic network raised to ML1.0, while the smallest earthquake that could be monitored was ML0.1, and the monitoring capacity was comparatively weak in the central and northwestern Yunnan area. Moreover, the average values of the minimum magnitude of earthquake early warning, the warning time after the triggering of the first station, and the warning time after the earthquake were ML2.2, 4.0 s, and 6.1 s, respectively. Furthermore, the planning layout of the Yunnan seismic station network fulfilled the criteria for the initial establishment of earthquake early warning.
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Journal of Geodesy and Geodynamics. 2025, 45(10): 1093-1100. https://doi.org/10.14075/j.jgg.2024.09.433
This study focuses on the classification problem of mining seismic and blasting signals in a mine in Gansu province. Common unsupervised classification methods such as support vector machine, K-means clustering, and principal component analysis were analyzed. These methods face significant challenges in terms of insufficient feature selection, low classification accuracy, and imbalanced samples. To attempt to address these issues, this paper employs a lightweight collaborative learning method(LCL-SSS) that combines MiniRocket feature extraction with improved K-means clustering, aiming to enhance the accuracy and efficiency of classification. Through time-frequency analysis, it was found that the initial P-wave frequency of blasting events is mainly concentrated between 80 to 200 Hz, while the P-wave frequency of mining seismic events is distributed between 20 to 120 Hz. After 30 training experiments, the classification accuracy of the LCL-SSS method reached 95.07%, effectively capturing key features in mining seismic waveforms.
