Both observation stations of the National Space Science Center, CAS, which are in Baodi district of Tianjin city and Yongqing county of Langfang city, observed atmospheric electric field anomalies before the Luanzhou MS4.3 earthquake on April 16, 2021. The Baodi station monitored a mixed electric field anomaly signal of transit clouds and geological activities. The Yongqing station monitored a bay-like continuous electric field anomaly signal, showing a typical hour-scale precursor signal before the earthquake, and its amplitude and duration are significantly higher than the anomalous electric field signal at the Baodi station. Comparing the meteorological activities and space weather activities of the two stations during the electric field anomaly, we infer that although the electric field anomaly signals of the two stations behave differently; the background changes imply the signals of large-scale geological activities. The analysis shows that in the future, it is possible to form an effective identification method by analyzing the evolutionary process of space static electricity caused by multi-source activities. Within a certain range of meteorological activities, it is possible to extract the precursor information of earthquakes of medium intensity or more from the atmospheric static electricity monitoring data.
To analyze the characteristics of geomagnetic induction vector and its structural implications in Shandong province, we calculate the transfer function and induction vector of 15 stations. The frequency domain curves show that the transfer function and induction vector of most stations change smoothly with period. The relative difference in electrical structure is not obvious with depth, and the underground electrical structure is stable based on the comparative analysis of each frequency band. The result suggests that the basic tectonic framework does not change with the depth. The current aggregation direction in 40 to 80 min band of Ji’ning in Luxi uplift takes a new turn of 180°, indicating that there is a large-scale high conductivity zone in this depth range. The study establishes the optimal window length (N=60 d) of daily sliding. Time series analysis shows that the transfer function has obvious 1 a cyclical characteristics, with obvious seasonal changes. Furthermore, the stability of the transfer function A is better than that of B, which is more suitable for time-lapse analysis. The induction vector results reveal that Yishu fault is an obvious electrical interface, and the electrical properties of Jiaodong uplift and Luxi uplift are quite different. The lateral electrical structure in the Luxi uplift area is not obvious. The internal structure of the Yishu fault is complex, and the transfer function has no significant change characteristics.
To analyze the influence of the time-varying gravity factors on mobile gravimetry data processing, we use static and dynamic adjustment methods to process gravimetry data in the area of southern segment of the north-south seismic belt, comparing the results of the two methods. The results show that: 1) The time-varying gravity factors cause errors in the gravity changes by the static adjustment method, which have a relatively obvious impact on gravity variations of the 0.5 a and 1 a time scales, but less impact on the gravity variations of more than 2 a time scale. Therefore, it is appropriate to use the dynamic adjustment method to calculate the 0.5 a and 1 a time scales gravity variations. 2) The locations of the Jiuzhaigou M7.0, Changning M6.0 and Yangbi M6.4 earthquakes have a good corresponding relationship with the zero-value of gravity variations. The gravity variations image reflects the seismogenic background of the 3 earthquakes.
Using ocean tide loading(OTL) corrections computed in the center of mass of the whole earth system(CM) frame and in the center of mass of the solid earth(CE) frame, we compute PPP position time series of 132 global stations to investigate the effect of geocenter motion induced by OTL on periodic signals of GPS position time series. The result shows that: 1) The average position differences induced by OTL geocenter motion are 0.7 mm and 1.3 mm for the horizontal and vertical components, respectively, and the effect of OTL-induced geocenter motion on GPS position time series is very similar for adjacent stations. 2) In CM-OTL and CE-OTL, the periodic signal caused by the tidal load effect is significantly reduced, and the inconsistency between the frame to which the tidal load correction belongs and the frame to which the GPS track belongs will introduce the GPS nodal year signal, 14 d and 9 d signals. 3) When performing PPP using precise satellite products provided by IGS, the OTL in the CE frame should be employed.
Based on the spherical harmonic coefficient products of the GRACE gravity satellite by CSR, we retrieve the changes of terrestrial water storage in China's seven major river basins from 2002 to 2018. Terrestrial water storage changes are obviously dependent on geographical distributions. The water storage of the Liaohe, Haihe, Huanghe and Huaihe river basins generally show decreasing trends, with average annual rates of -0.54±0.9 mm/a, -5.96±0.6 mm/a, -2.65±0.8 mm/a, -1.94±1.2 mm/a, respectively. The most significant decrease in water storage occurred in Haihe river basin, resulting plausibly from the overexploitation of groundwater for industrial and agricultural activities. In the Songhua river, Yangtze river, and Pearl river basins, the water storages show significant positive trends, with average annual rates of 4.52±1.1 mm/a, 3.84±0.7 mm/a, and 4.87±1.1 mm/a, respectively. The time of water storage peak of the basin generally lags behind that of the peak monthly precipitation, because it takes some time to convert rainfall into land water storage.
Based on data from 11 cross-fault sites in Yunnan province, applying the cross-fault data analysis method, this paper systematically summarizes and extracts the comprehensive seismic prediction indexes in Yunnan province. By analyzing and summarizing the response ability of these indexes before the Yangbi M6.4 earthquake, the preliminary conclusion is that there is a significant mid-term anomaly in the cross-fault data before the Yangbi M6.4 earthquake, and that the occurrence of the earthquake may be related to the increase in activity of the western boundary of the Sichuan-Yunnan diamond block. The cross-fault mid-term prediction index makes a good estimate for the Yangbi M6.4 earthquake. Short-term indicators also pass the effectiveness criterion, but forecast effectiveness is slightly worse. Therefore, in the subsequent analysis of cross-fault data, more attention should be paid to the extraction and application of medium-term anomalies and medium-term prediction indexes. The comprehensive indexes summarized in this paper can be applied to follow-up earthquake situation tracking in Yunnan area.
Based on D-InSAR technique, the coseismic deformation fields of the May 21, 2021 MW6.1 earthquake in Yangbi County, Dali Prefecture, Yunnan Province are successfully extracted by collecting Sentinel-1 satellite ascending and descending orbit data and precision orbit data, combined with external DEM data.The results show that the maximum line-of-sight deformation of the ascending is about 6.0 cm while the descending about 7.9 cm. Based on InSAR observations, we obtain the fault geometry parameters and slip distribution of the Yangbi earthquake. We find that the fault of the earthquake has an optimal strike angle of 136.6° and dip angle of 83.1°. The fault rupture is mainly concentrated in the depth of 2 to 12 km underground. The maximum slip is about 0.45 m, located at a depth of about 7 km underground. There is no large area significant slip near the surface of the fault, indicating that the earthquake did not rupture to the surface.
Using SBAS-InSAR technology to process the 43-view Sentinel-1A images to obtain the surface deformation of Yan’an New Area(north zone), we decompose the monitoring results with empirical orthogonal function analysis to obtain the time coefficients and spatial distribution of the study area. The results show that the maximum settlement rate of Yan’an New Area(north zone) is -56 mm/a and the maximum uplift rate is 32 mm/a. From the mode 1, the excavation and filling are the main causes of surface uplift and settlement. The mode 2 reflects that different periods of construction correspond to different states of surface deformation, i.e., three stages of acceleration, slowdown, and smoothness.
We use the D-InSAR technique to process the 2-view descending track Sentinel-1A data covering the period before and after the eruption of 2020 Sakurajima volcano in Kagoshima city, Japan. We obtain the surface deformation field caused by the volcanic eruption event, and on this basis, we carry out the inversion analysis of the magma source during the eruption of Sakurajima volcano by combining the point source Mogi model. The results show that subsidence during 2020-07-28~08-09 is mainly concentrated in the central area of the volcano, and the maximum subsidence area is the central area of the volcano, with maximum and average subsidence amounts of 5.5 cm and 2.85 cm, respectively. The uplift mainly occurs in the rim area of the volcano, with maximum and average uplift amounts of 5 cm and 2.24 cm, respectively. The uplift may be related to the magmatic activity below the crater of Ayla. The inversion of the point-source Mogi model yields a magma source depth and volume change of 1.016 km and -0.139×106 m3, respectively, and the magma source is located below Minami-dake, which is related to the eruptive activity of Minami-dake.
In order to fill in the gaps of the traditional GM(1,1) power model with equal-weight construction for background values, a non-equidistance linear time-varying parametric GM(1,1) power model with weighted optimization of background values is constructed for the non-equidistance spaced oscillation characteristics of the original deformation sequences. In addition, we use the particle swarm optimization(PSO) algorithm with fast convergence and high precision to solve the power exponent and background value weight. Taking the cumulative settlement observation data of monitoring points in two mining areas as examples, we use the constructed model for settlement analysis and prediction. The results show that average absolute percentage fitting errors of the model in this paper are 2.33% and 4.70% respectively, and the prediction errors are 2.10% and 6.38% respectively, which are better than other three GM(1,1) power models. The engineering application shows that the proposed optimization model has applicability and superiority to deal the small-sample non-equidistant oscillation sequences, and that it is suitable for short-term prediction and time-varying analysis in coal mining deformation monitoring engineering.
We obtain the 10-40 s phase velocity structure of the study area based on the ambient noise tomography method and records from 70 stations in Liaoning and adjacent areas in 2012. The 3D S-wave velocity structure of 10 - 40 km below the study area is inferred by Markov Chain Monte Carlo(MCMC) method using the obtained base-order surface wave phase velocity dispersion curves. The results show that the S-wave velocity distribution in the shallow, middle and upper crust of the study area corresponds well with the topography, and the transition zone between high and low velocities is more likely to be the seismogenic zone. The S-wave velocity structure in the middle and lower crust to the top of the upper mantle is more controlled by the undulating state of the Moho surface and the deep major fractures. At 30 - 40 km depth in the area from Haicheng to Dalian and finally to Liaodong bay, there is an “arc-shaped” low velocity anomaly, and we infer that there is thermal material upwelling in this area. An elliptical low-velocity body occurs 15 km below the Liaoyang to Yitong section of longitudinal profile C-C′.
Based on the regional geological structure survey, geophysical data and remote sensing interpretation, using drilling, trenching and 14C chronology, we discuss and study the age, character and tectonic significance of the NE trending buried fault in Siping section of Yitong-Shulan fault zone. The results show that: 1) Siping section is mainly developed in the upper pleistocene felsic(including breccia) sand layer, and belongs to thrust nappe fault; 2) AMS14C dating results of arable soil layer, clay layer, argillaceous sandstone layer and felsic(including breccia) sandstone layer exposed by trenching and drilling are -70~6 270 BP、60~7 780 BP、110~21 780 BP、11 740~26 100 BP, respectively. The age of fault activity should belong to pre Quaternary (>26 100 BP); 3) Combined with regional magmatic tectonic and seismic events, the NE trending concealed fault zone exposed in this study may have been formed in the late Pleistocene.
We propose a simplified model for differential code bias estimation, which simplifies the VTEC of each puncture point in the direction of the station into a parametric sub-period for direct estimation. To verify the validity of the method, a comparative analysis is performed using the spherical harmonic function modeling and the GIM estimation-based method. GPS+GLONASS data from nearly 200 IGS stations in January 2016 were selected for the experiments and validated with the products provided by CODE. The results show that for GPS(GLONASS) satellite DCB, the method is relatively close to the results estimated by the other two methods, and the mean deviation and standard deviation compared with the products of CODE are -0.3-0.5 ns (GPS)、-1.3-0.7 ns(GLONASS) and 0.05-0.20 ns (GPS)、0.14-1.10 ns(GLONASS), respectively. For receiver DCB, the mean deviation of the three methods compared with the products of CODE are -0.6-0.7 ns (GPS) and -1.5-1.5 ns (GLONASS), respectively. The experimental results verified the validity of the simplified model of DCB.
In order to verify the positioning performance of the new triple-frequency PPP model of the BDS-3 system, we derive the new triple-frequency PPP model based on the original observation equation and derive the pseudorange deviation correction again in the model. Using BDS-3 data observed by 14 MGEX stations, we compare and analyze the static and dynamic positioning performances of three triple-frequency PPP models and two traditional dual-frequency uncombined models. Experimental results show that the new triple-frequency PPP model can improve convergence time and positioning accuracy, and the TDF model has the greatest improvement effect.
Based on the three indicators of altitude angle, signal-to-noise ratio and pseudorange residual, this paper adopts K-means(Kmeans++), iterative self-organizing data analysis method(ISODATA) and density-based spatial classification with noise(DBSCAN) to classify the GNSS data in complex urban observation environments. We evaluate the classification accuracy of different algorithms using pseudorange single point positioning(SPP). The results show that the Kmeans++ algorithm has the best classification accuracy. The accuracy of positioning in three directions of E,N and U is 2.56 m, 3.25 m, and 9.73 m respectively; compared with not using the Kmeans++ algorithm, the positioning accuracy is improved by 57.86%, 47.64%, and 60.98%. To further verify the performance of the algorithm, the accuracy of the Kmeans++ algorithm is compared with the signal-to-noise ratio and height angle threshold algorithm. The results show that the plane and three-dimensional positioning accuracy of the Kmeans++ algorithm is significantly improved by 24.87%, 39.07%(signal-to-noise ratio algorithm) and 41.36%, 59.91%(height angle threshold algorithm), respectively.
Based on the traditional algebraic reconstruction technique (ART), an variable weight algebraic reconstruction technique (VWART) of constraint equations is proposed, and the GNSS observation data of CORS network in Hong Kong area in August 2019 is used for experiments, and the sounding data of HKKP is selected for verification and analysis. The results show that, compared with the traditional ART, the accuracy, stability and reliability of the solution results of the VWART are improved. The RMSE is reduced by 20.334% using the sounding data as an example, and the vertical water vapor profile distribution of the VWART is better than that of the traditional ART under different levels of precipitation.
Aiming at the problem of bridge deck segmentation of bridge point cloud, we propose a bridge deck segmentation method based on the fusion of plane elements in adjacent regions. Firstly, the point cloud is voxelized to obtain the voxel point cloud, and the supervoxel space and normal constraint criteria are used to over-segment the bridge point cloud. Then, we use the direction of the patch normal and the model length to perform the patch filter to obtain the candidate patch containing the bridge deck. Finally, we perform the plane element fusion of the adjacent area on the candidate patch and use the statistical distribution method to filter the fusion area to obtain the bridge deck point cloud. Experiments show that the method in this paper can effectively segment the bridge deck of the bridge point cloud, has high stability, and retains the original data before voxelization. Compared with the region growing and the supervoxel region growing methods, the method in this paper integrates across regions. It has a better inhibitory effect and is more suitable for bridge deck segmentation of bridge point clouds.
We use a phasenet model for deep learning detection of seismic signals to detect the MS6.6 earthquake sequence in Minxian, Gansu province. According to the seismic correlation technology and absolute positioning hypoinverse method, we construct the AI detection directory. Compared with the manual analysis of seismic directory and seismic phase report, we analyze the error range of AI automatic processing of seismic events. The results show that AI technology realizes 85.5% manual work, and the positioning error is normally distributed within 20 km. AI method has played a significant role in the detection of low magnitude earthquake events. Compared with manual processing, the AI method has good stability, does not depend on personal experience level, and has fast analysis speed. It can play a key role in the rapid output of earthquake catalog after a large earthquake, quickly improve the ability of earthquake analysis and save human labor.
Before the Qinghai Maduo MS7.4 earthquake, the VP broadband tiltmeter of Anxi seismic station in Gansu province showed obvious abnormal changes and recorded co-seismic waveforms. Combined with the CTS-1 seismometer for fusion analysis, the phase of co-seismic waveforms changed in the same time, showing that the records of two sets of instruments are reliable and consistent, but the characteristics of seismic phase differ. The annual change is broken and tilts to the northwest on April 17, 2021, when analyzing the data of the VP broadband tiltmeter, and the original northwest tilt is restored to the southwest tilt on May 13. The azimuth of sharp increase of dip angle recorded before the earthquake is consistent with that from the epicenter to the station, and the change of tilt rotation is consistent with the direction of regional tectonic stress. The time-frequency spectrum of hour data show low-frequency signals from 1.085×10-6 to 4.340×10-6 Hz(period 64~128 h). There are significant differences in the dominant frequency and time-frequency variation characteristics of the two sets of instruments in the earthquake, which may be related to the different mechanical structures, frequency band widths, and sampling frequencies of the two sets of instruments.