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15 September 2026, Volume 46 Issue 9
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1039-1045. https://doi.org/10.14075/j.jgg.2026.02.043To address the limitations of the algebraic expansion of the meridian arc length, this study is based on the principles of equivalent transformation and order-increment invariance. Using the first eccentricity or the third flattening, this study reconstructs polynomial function models for the meridian arc length and the meridian radius of curvature, respectively. Additionally, a constrained least squares method is derived for the direct estimation of the model constant coefficients. The results indicate that, regardless of whether the first eccentricity or the third flattening is used, the polynomial function models facilitate the high-order expansion and correctness verification of the algebraic expansion of the meridian arc length. Furthermore, their estimation accuracy can meet the requirements of practical applications such as high-precision geodesy and map projection.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1046-1053. https://doi.org/10.14075/j.jgg.2025.11.366Aiming at the critical influence of universal time 1 (UT1) prediction accuracy on satellite precise orbit determination, this paper quantitatively analyzes the prediction performance of 116 batches of Bulletin A released by the international Earth rotation and reference systems service (IERS). Taking multi-orbit targets including the TianQin-3 satellite, space station and Beidou satellites as examples, the magnitude estimation formula for the influence of UT1 prediction error on orbit determination accuracy is verified. A rapid evaluation of the three-dimensional orbital deviation of satellites is realized only based on orbital radius and universal time error. The analysis results show that the UT1 prediction error of Bulletin A exhibits obvious uncertainty and increases significantly with the growth of time scale. Its 30-day mean prediction error (3.399 ms) causes orbital deviations ranging from 1.673 m to 24.79 m for satellites from low Earth orbit to deep space exploration represented by the TianQin-3 satellite. The quantitative results reveal that the accuracy of existing prediction products has a non-negligible impact on future high-precision aerospace missions, and demonstrate the necessity of developing China’s independent and high-precision universal time measurement and prediction system.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1054-1061. https://doi.org/10.14075/j.jgg.2025.12.438Currently, there is still a lack of long-term systematic monitoring of broadcast ephemeris orbit frames for multi-GNSS systems. We systematically investigate the long-term performance of the spatial reference frame for broadcast ephemeris orbits of the four GNSS satellite navigation systems (BDS-3, GPS, GLONASS, and Galileo) based on Helmert seven-parameter transformations between broadcast ephemeris and precise orbits, and the derived root sum squares (RSS) comprehensive index, as well as BDS-3/GLONASS analysis results from the data exchanged with the TsNIIMash, Russia, covering the period from August 2020 to December 2024. The results show that Galileo orbit demonstrates the best overall stability in realizing the spatial frame, with a RSS 7-parameter value of approximately 4.7-5.2 cm, following by GPS and BDS-3 (7.7-9.0/7.5-13.8 cm), while GLONASS has an uncertainty of 19.9-23.3 cm. Among the four systems, the Z-component of Helmert translation parameters for GPS, Galileo, and BDS-3 all exhibit significant annual periodic variations, which are likely related to deficiencies in the solar radiation pressure models used during orbit determination. Since the optimization of the Earth orientation parameters (EOP) update strategy in 2023, the BDS-3 system has shown a significant improvement in orbit frame maintenance accuracy, with the fluctuations of rotation parameters RX/RY/RZ components reduced from ±6/±8/±8 mas to ±2/±4/±3 mas, and the overall frame accuracy clearly improved, as RMS of RSS7 decreased from 12.2 cm to 7.5 cm. This finding is consistent with the analysis results from TsNIIMash.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1062-1069. https://doi.org/10.14075/j.jgg.2025.12.422We analyze the prediction effectiveness of seismic gaps before MS≥5 earthquakes in Gansu region from 1984 to 2023. The results show that seismic gaps in Gansu and its adjacent regions have an accuracy rate of 0.75, a false rate of 0.25, and a missing rate of 0.38 for forecasting moderate-strong earthquakes in Gansu. The R-value is 0.5, which exceeds the R0 value of 0.23 at the 97.5% confidence level. This demonstrates that seismic gaps have relatively good forecasting capability for moderate-strong earthquakes in Gansu. The mainshocks generally occurred inside the seismic gaps or near their edges，and the duration of these seismic gaps does not exceed 8 years. The number of broken and unbroken seismic gaps before mainshocks are comparable. The probability of the mainshock occurring within 1 year after the broken gap is about 89%, and about 67% within 4 months. There is no obvious correlation existed between the duration of seismic gap and the mainshock magnitude. However, there is a linear relationship between the minimum magnitude of seismic gap with initial magnitude of ML3.0~4.0, and the long axis of seismic gap has a good correlation with the mainshock magnitude. The seismic gap can be used as one of the important indicators for predicting moderate-strong earthquakes in western Qilian mountains, the southeastern part of eastern Qilian mountains and Minxian-Diebu section. It is also a significant indicator for predicting MS≥6 earthquakes in Gansu. The probability of two seismic gaps appearing before mainshock is very high, and the mainshock is most likely to occur within 4 months after the broken gap, located inside or near the overlapping region of the two seismic gaps.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1070-1079. https://doi.org/10.14075/j.jgg.2025.09.305Taking the 2021 Horqin MS4.7 earthquake as a case study, this paper uses the Biot-Savart law and the Monte-Carlo method, and employs the abnormal amplitude of the anti-phase geomagnetic vertical component at observation stations to invert and locate the information of these earthquake-induced currents. It reveals the temporal and spatial evolution characteristics of the induced currents related to the pre-earthquake geomagnetic anti-phase anomalies, as well as their correlations and influences with seismogenic structures and nearby/far-field earthquakes in the surrounding areas. Spatial distribution of induced currents: 1)The distribution trend of the peak value of induced currents is similar to the nature of the seismogenic fault. 2)Conjugate-shaped induced currents appear before the earthquake. Temporal sequence analysis of induced current depth: 1)The depth of induced currents during the earthquake occurrence period is very close to the focal depth. 2)As the earthquake approaches in time, the first-order difference of the shallowest depth of induced currents shows a convergent trend. 3)Surrounding earthquake events can cause the phenomenon of “shrinking before the earthquake and increasing after the earthquake” in the maximum depth of induced currents.This study represents a new attempt in the application of the electromagnetic discipline to the location of earthquake precursor anomalies, and provides new ideas for the short-term and imminent earthquake prediction methods based on electromagnetic anomalies.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1080-1087. https://doi.org/10.14075/j.jgg.2025.12.445This paper proposes a novel in-situ stress inversion method. Combined with Michael’s linear stress inversion and Vavryčuk’s fault plane identification technology, a complete inversion workflow for in-situ stress parameters is established by adopting multi-constrained moment tensor inversion to determine focal mechanisms. Taking the carbonate hot dry rock (HDR) reservoir in the Subei basin as a case study, 90 high-quality microseismic events are selected for in-situ stress inversion. The relative magnitude of the three principal stresses follows the order of SV>SHmax>SHmin. The orientation of the maximum horizontal principal stress SHmax is approximately NW44°, and the stress shape factor R is 0.74. The inverted results are in good agreement with the in-situ stress data measured by the anelastic strain recovery (ASR) method from core samples of the same well, in terms of stress regime and principal stress orientation. This confirms the reliability and applicability of the microseismic-based stress inversion method in the study area. The proposed method can efficiently calculate in-situ stress parameters during fracturing and quantitatively characterize dynamic stress field evolution, which provides solid technical support for deep reservoir stimulation.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1088-1094. https://doi.org/10.14075/j.jgg.2025.10.351We propose an outlier detection method for dam deformation based on ensemble empirical mode decomposition (EEMD) high-frequency differential conversion and gated recurrent unit (GRU) analysis. First, the EEMD technology is employed to decompose the original deformation monitoring data, yielding deformation components at different frequencies. Then, high-frequency components containing abnormal deformation information can be extracted for differential sequence conversion, and identification criteria for abnormal single-jump points are proposed. Finally, a high-frequency component time series model is established by GRU neural networks, which is then combined with the abnormal single-jump point identification pattern to recognize outliers. The results show that EEMD technology and high-frequency sequence differential conversion can effectively isolate deformation anomaly information. The proposed single-jump point detection model aligns with the characteristics of dam deformation anomalies. Combining GRU and the 3σ criterion for time series modeling analysis of differential sequences, all deformation anomalies can be accurately identified, and achieve higher accuracy than traditional methods.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1095-1106. https://doi.org/10.14075/j.jgg.2025.12.420Based on 228 Sentinel-1 images acquired from January 2018 to August 2022, we use the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique to derive surface deformation time series in Baotou. Multi-source datasets, including precipitation records, optical imagery, and mineral resource distribution data, were integrated to analyze deformation characteristics and their driving factors in different functional zones. The results indicate that the study area is generally stable, with approximately 98.85% of permanent scatterers (PS) exhibiting annual average deformation rates between -10 and 10 mm/a, while significant local variations are observed. In local built-up areas of the urban plain, evident subsidence occurs due to building loads and ash compaction, with a maximum rate of -73 mm/a. Open-pit mining activities in Donghe district induce pronounced deformation, with a maximum subsidence rate of -77 mm/a, and a stage-wise adjustment of deformation is observed after mining cessation. Time-series analysis results show that deformation in urban built-up areas exhibits weak sensitivity to precipitation, whereas deformation in mining areas presents a lagged response to precipitation at the monthly scale. Comparison with GNSS observations indicate that there is a good consistency between InSAR and the measured deformation trends. The results suggest that mining activities and urban construction are the primary controlling factors of regional surface deformation, while natural conditions play a modulating role in deformation evolution across different functional zones. The study highlights the application potential of SBAS-InSAR for surface deformation monitoring in resource-based cities.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1107-1113. https://doi.org/10.14075/j.jgg.2025.12.441SBAS-InSAR technology was employed to obtain the land surface deformation distribution in Xining city from October 2020 to November 2024. By integrating static features such as the spatial location of deformation points with dynamic climatic characteristics, a multi-feature-based BiLSTM prediction model was constructed to forecast deformation in areas with typical deformation characteristics. The main conclusions are as follows: 1) The average annual deformation rate in the study area ranges from -48 mm/a to 30.2 mm/a, with a maximum cumulative deformation value reaching -187.2 mm. 2) Compared with the LSTM model, the prediction accuracy of the multi-feature BiLSTM model in three typical deformation areas is improved by up to approximately 32.3%, and it can more accurately identify local details and abrupt change points. At last, the optimal model was used to predict the deformation trends in each typical deformation area for the next six months, providing a reasonable reference for surface deformation monitoring.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1114-1123. https://doi.org/10.14075/j.jgg.2025.12.437This study takes Jinyang county as the research area and integrates 332 Sentinel-1 SAR images from the past six years with multi-temporal optical imagery. Based on the SBAS-InSAR technique, regional landslide hazards were systematically identified and monitored. The results indicate that: 1) Combining InSAR-derived deformation with optical interpretation, and verified by field surveys, 14 landslide hazards were identified. They are mainly distributed along the right bank of the Jinsha river and both banks of the Jinyang river, with slope aspects predominantly facing due east and southeast. 2) In-depth analysis of a typical landslide shows a high consistency between the deformation area detected by InSAR （2018-01-02 to 2023-10-27） and the results from optical interpretation. Deformation is primarily concentrated in the middle part of the slope. Based on deformation rates, the area can be classified into zones of extremely strong, strong, weak, and stable deformation. The cumulative deformation in the extremely strong deformation zone exceeds -490 mm and shows ongoing activity. 3) Landslide deformation exhibits a lagged response to rainfall, and terrain slope is a key factor controlling its deformation pattern. This study can provide direct support for regional landslide risk management and scientific monitoring.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1124-1133. https://doi.org/10.14075/j.jgg.2025.12.435This study takes the agricultural irrigation district of Changji, Xinjiang as the research object. By integrating time-series InSAR, geographically weighted regression (GWR), and wavelet analysis methods, and based on Sentinel-1A data from 2017 to 2020, the surface deformation field was obtained. Multi-source data were fused to quantify the spatial heterogeneity of driving factors, and periodic characteristics of the deformation time series were extracted. The results show that: 1)The deformation in the study area exhibits a spatial pattern of stable in the south, subsiding in the center,and uplifting in the north. The maximum subsidence rate in the central subsidence funnel reached -90.1 mm/a, while the uplift rate in the northern area reached 21.7 mm/a. Temporally, the deformation showed continuous accumulation superimposed with seasonal fluctuations, with the maximum cumulative subsidence reaching -407.3 mm in August 2020. 2)The GWR model revealed significant spatial heterogeneity in the driving mechanisms: stability in the south is controlled by abundant rainfall and coarse-grained aquifers; subsidence in the central area is closely related to groundwater over-extraction and fine-grained, easily compressible strata; uplift in the north is mainly driven by human-regulated water level recovery. 3)Wavelet analysis identified two main periodicities of 372 days and 348 days in the subsidence areas, whose spatial distribution is highly consistent with the intensity of agricultural irrigation. This indicates that agricultural extraction activities are the primary factor controlling the spatial differentiation of these periodic characteristics. This study provides a basis for differentiated prevention and control of land subsidence and adaptive water resource management in arid regions.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1134-1146. https://doi.org/10.14075/j.jgg.2025.12.440This study proposes an improved DeepLabV3 model for the identification of retrogressive thaw slumps in frozen ground regions. The method integrates the Sobel operator with a boundary-enhanced dual attention (BEDA) module to accurately extract retrogressive thaw slump boundaries; a deformable context pyramid (DCP) module is employed to adapt to retrogressive thaw slumps of varying scales and morphological characteristics. Weighted residual connections are introduced to preserve the original semantic information and enhance detail representation. The dataset of retrogressive thaw slumps was constructed through visual interpretation using SBAS-InSAR surface deformation results, mountain shadow information, and Google Earth imagery. Experimental results show that the overall outputs of the model are closer to the ground truth labels, and the Recall and MIoU of the improved model are increased by 1.59% and 2.09%, respectively, compared with the baseline model.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1147-1155. https://doi.org/10.14075/j.jgg.2025.11.403Based on Sentinel-1A ascending and descending SAR data, the co-seismic InSAR deformation field and range-direction pixel offset of the January 7, 2025, MW7.1 Dingri earthquake were obtained. Combined with elastic half-space dislocation theory, the particle swarm optimization (PSO) algorithm and the Akaike-Bayesian information criterion (ABIC) were used to invert single- and double-fault slip distribution models. Static Coulomb stress changes at depths of 5 km, 10 km, and 15 km were also calculated. The results show that although the double-fault model, constrained by surface rupture traces identified via the pixel offset tracking (POT) method, exhibits higher roughness, it more accurately reproduces the surface rupture trajectory at fault strike variations. The double-fault model achieved fitting accuracies of 97.2% and 96.5% for ascending and descending InSAR data, respectively, outperforming the single-fault model (96.8%/95.9%). The inverted seismogenic fault has a strike of 186° and a dip angle of 55°, with co-seismic slip mainly concentrated in the northern section and a secondary slip core between the two fault strands. The total seismic moment released was 6.12×1019 Nm (MW7.1). Coulomb stress perturbations generally decreased on both sides of the fault, while stress increased at a depth of 15 km in the southern segment, showing strong spatial correlation with aftershock distribution, indicating that stress in this region is prone to release through aftershocks. Local stress increases were also observed at different depths near the northern and southern ends of the fault, which should be key areas for future research.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1156-1161. https://doi.org/10.14075/j.jgg.2025.12.406Aiming at the problem that the static relative positioning technology has a long calculation cycle and cannot timely reflect abrupt deformations when using Beidou/GNSS technology for infrastructure deformation monitoring currently, this paper proposes a real-time fusion method for monitoring results of static and RTK with different time scales and positioning accuracies, based on wavelet decomposition and dynamic weighted fusion of sliding time windows. Through experimental tests in the ultra-short baseline field, it is verified that this method can provide millimeter-level monitoring accuracy results when the monitored object is stable or deforms slowly, and can timely output the actual displacement when abrupt deformation occurs, with accuracy superior to that of RTK monitoring results. The method can be implemented based on general-purpose GNSS data processing software available on the market, and has a good prospect of engineering application.
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Journal of Geodesy and Geodynamics. 2026, 46(9): 1162-1170. https://doi.org/10.14075/j.jgg.2025.11.380To address the limited positioning accuracy of global geomagnetic field models in localized regions, this paper proposes a geomagnetic positioning method based on a genetic algorithm-optimized extreme learning machine (GGA-ELM). By introducing an elite backpropagation strategy, the initial weights and thresholds of the ELM network are optimized, thereby improving training efficiency and reducing the risk of getting stuck in local optima. Based on actual aeromagnetic data from the Yuyao and Weishui regions in China, and in combination with the EMM2017, WMM2020, and IGRF13 geomagnetic field models, this study analyzes the differences in positioning accuracy between model data and observed data. Experiments demonstrate that the EMM2017 model achieves the best overall positioning accuracy at both sites (Yuyao: 6.29 m in longitude and 5.92 m in latitude; Weishui: 6.81 m in longitude and 5.89 m in latitude), significantly outperforming the WMM2020 and IGRF13 models. In the measured aeromagnetic data, the error in the latitudinal direction was slightly greater than that in the longitudinal direction (with a difference in root mean square error of approximately 0.5 m), whereas the geomagnetic field model data exhibited a characteristic where the longitudinal error was greater than the latitudinal error. The GGA-ELM method performed consistently at both locations, with positioning accuracy differences of less than 5%, verifying the robustness of the GGA-ELM method. This study provides a theoretical basis for model selection and algorithm optimization in geomagnetic navigation.
