For the empirical mode decomposition (EMD) noise reduction process, there is signal and noise mode aliasing, and the intrinsic mode function (IMF) component is directly classified into high frequency noiseto generate real signals. The real signal is “submerged,” among other issues. This paper proposes an improved method of EMD noise reduction. The improved EMD denoising method mainly reconstructs the second IMF to demarcate the IMF component obtained by EMD decomposition, performs the next EMD decomposition on the reconstructed signal, obtains the “real” signal therein, and repeats this operation multiple times. Finally, all the obtained low frequency signals are accumulated to achieve the purpose of noise reduction. Experiments are carried out using three kinds of simulation data and one kind of GPS measured elevation data. The simulation data and the measured data are evaluated by different evaluation indexes. The results show that the improved EMD method has better noise reduction effects than the traditional EMD method, and the reliability of the method is verified.

We are concerned with the characteristics of the triple-frequency signal broadcast by the full constellation of the Beidou navigation satellite system. One carrier pseudorange combination (1,4,-5) and two triple-frequency geometric-free phase combinations (1,1,-2) and (1,-2,1) perform the cycle slip detection. We combine the minimum 2-norm to the integer cycle-slip search strategy to determine the cycle-slip value. The measured data show that the proposed method can detect and repair the normal cycle-slip, insensitive cycle-slip and continuous random cycle-slip.

Based on the radiosonde records at 81 sounding stations from integrated global radiosonde archive (IGRA) throughout 2017, we conduct a comprehensive evaluation and analysis of the precision of four tropospheric delay models over China. Results show that GPT2w model outperforms the other models, including the Saastamoinen model that is dependent on meteorological elements, GZTD, as well as UNB3m with the format of spherical harmonic function. Mean bias (MB) and root mean square error (RMSE) of GPT2w model are －0.8 cm and 4.1 cm, respectively, and they range from －2 to 2 cm, and from 1.3 to 7.9 cm at all sites, respectively. The UNB3m model has the largest MB and RMSE among the four models, with the maximal RMSE reaching 10.2 cm. In addition, the four models have consistent sensitivity to the latitude of the stations, presenting as decreasing accuracy with increasing latitudes. The precision of the models has a prominent seasonal variability, presenting as different seasonal sensitivities among the four models. The low precision in modeling of tropospheric wet delay causes the lower accuracy of the models in summer (RMSE: 6~9 cm), in contrast with that in winter (RMSE: 2~2.5 cm).

Using the data of Beidou GEO satellites in the Asia-Pacific region, we study the geomagnetic storm phenomenon that occurred in the middle and low latitude regions in May 2017. The accuracy of the global ionospheric map (GIM) is evaluated using the measured TEC data obtained by Beidou GEO satellites, and the global response of the ionospheric TEC of this geomagnetic storm is further analyzed. It is found that the response of the ionospheric TEC to the geomagnetic storm occurs 1 to 4 hours after the start of the main phase of the geomagnetic storm and the maximal disturbance value could reach 20 TECu.

We discuss the distribution characteristics of precipitable water vapor(PWV) and the relationship between PWV and actual precipitation during two typical precipitation processes in 2018 to analyze the application of PWV in rainfall prediction. The results show that during the precipitation process, PWV distribution is consistent with actual precipitation. PWV presents indications about rainfall prediction; PWV starts to increase within 6 to 12 hours before rainfall occurs, and rises rapidly within 1 to 2 hours before precipitation occurs. When PWV increases significantly and maintains a high value, it indicates that heavy precipitation will occur. Moreover, the faster PWV changes, the greater precipitation probability and amount of precipitation. Through the sliding average treatment, the phenomenon of rapid accumulation and release of PWV before and after heavy rainfall occurrence is further proven. PWV can be used as sequence data for research and application of short-term nowcasting and weather analysis. It also provides a powerful supplement for traditional meteorological methods.

Aiming at the problem that the weighted average atmospheric temperature (T_m) is affected by time and space in GNSS meteorology, this paper uses the data of seven sounding stations in the Yangtze river delta from 2015 to 2017. The linear relationships between T_m and the ground temperature (T_s), water vapor pressure (e_s) and air pressure (P_s) are analyzed. The multifactor linear fitting localized T_m model for Yangtze river delta is established based on the least square method. Experiments show that the one-factor T_m model are better compared to Bevis model. However, the effects of the two-factor and multi-factor models are comparable to the single-factor model. The seasonal multi-factor T_m model is better than the yearly model and improved prominently in autumn and winter. GNSS PWV calculated by the multi-factor T_m model is also better than the Bevis model. The results show that the seasonal multi-factor localized T_m model is more suitable for the Yangtze river delta and it can obtain more accurate T_m and PWV.

This paper uses GNSS signal-to-noise ratio (SNR) data to obtain the dam water level changes. Based on the multi-path signal characteristics of water surface reflection, this paper analyzes the influence of signal frequency, altitude angle range and arc length on the water level inversion results of power station dams. We compare the water level inversion results with the measured water level data of the dam. The experimental results show that the two results have good consistency; the correlation coefficient is above 0.9; the water level retrieval accuracy of the GPS system is 0.1-0.15 m; the water level retrieval accuracy of the BDS system is 0.35-0.45 m; and the combined inversion accuracy of the GPS and BDS systems is 0.1-0.13 m, which is better than the single system retrieval precision.

In this paper, an adjustment model with uncertainty and inequality constraints is established by combining the bounded uncertainty of parameters with the adjustment model with uncertainty. Then, the corresponding iterative algorithm with uncertainty and inequality constraints is put forward, starting from the equality constraints, using the idea of infinite weight and zero weight, and combining the uncertainty adjustment algorithm with the penalty function in the inequality constraints. Finally, an example further verifies the feasibility and effectiveness of the algorithm.

The regularized smoothing factor method is adopted to process and analyze continuous gravity data and to attempt separate coseismic signals. The results show that this method can effectively separate and obtain the coseismic gravity change and seismic wave and that the estimated co-seismic gravity change has good consistency with the theoretical simulation results, providing more constraint conditions for fast inversion of seismic parameters and early warning.

Based on flow gravity observation data from 2011 to 2013 in southern Liaoning province, in-depth analysis is carried out on the evolution characteristics and the mechanism of gravity space before the M5.1 Dengta earthquake in 2013. The study shows that: 1) There is a good correspondence in time and space between the anomaly of the gravity field and the M5.1 Dengta earthquake in middle south Liaoning province. 2) One year before the earthquake, the characteristics of the four quadrants are apparent, half a year before the earthquake, 50 μGal reverse change appeared, accompanied by high gradient zone of gravity change; the rising and falling trend of the gravity point value sequence are obvious, and the gravity profile fluctuates intensely. 3) Combining the background field of gravity change and the regional geological structure in 2011 to 2012, we infer that this earthquake may be a result of the density variation of the deep material and tectonic movement in the southern region of Liaoning.

In order to investigate the relationship between the temporal and spatial distribution characteristics of gravity tide parameters and earthquake gestation, this paper takes the 2013 Lushan M7.0 earthquake as an example. The continuous gravity observation data of 17 stations in the vicinity of the Lushan earthquake area are collected and analyzed. The parameters of the daily and half-day wave tidal parameters are analyzed by VAV harmonic analysis method. The tidal factors of the half-day M₂ wave are studied with time trend and spatial distribution. The results show that the spatial distribution of the trend of the trend of the M₂ wave tidal factor before the Lushan earthquake generally shows a four-quadrant distribution of rising and falling trends. The Lushan earthquake is at the center of the four quadrants, which may be caused by the “locking shear force” existing before the earthquake deformation or density disturbance.

This paper uses the Jiuzhaigou MS7.0 earthquake as an example to discuss the precision of the earthquake monitoring system. The result shows that a change of 70 μGal on earth surface declines to 18 μGal in near space (20 km high) to earth.

Based on the EGM2008 global gravity field model, the horizontal and vertical distributions of gravitational field at different scales in the Cangwu earthquake region and south China block are studied. The density variation of deep material and its possible dynamic implication is discussed, providing a deep basis for studying the environment of earthquake inoculation in this region. The lateral variation of gravity anomaly in the Yangtze craton is relatively small, suggesting relatively stable characteristics of craton structure. The upper mantle of the Huaxia block has a gravity positive anomaly, consistent with the subduction angle of the western Pacific plate and the negative gravity anomaly in interphase distribution. Also, the distribution of the high and low density body may be related to lithosphere disintegration and the upwelling of the asthenosphere under the subduction of the western Pacific plate since the Mesozoic. The transition zone between the Yangtze craton and the Huaxia block shows a significant gravity anomaly with high gradient and east-west difference, revealing the complexity of tectonic deformation and transitional zone in deep regions. The lateral complexity and heterogeneity of the multi-scale lattice gravity anomalies, as well as the gravity anomaly in different depths of the crust and upper mantle, reflect the dynamic process of the difference movement between the shallow material structure and the dynamic imbalance in the study area, which may be the deep dynamic environment of the strong earthquake occurring in the study area. The Cangwu earthquake and most strong earthquakes in the study area are located in the transitional zone of gravitational positive and negative anomaly, which is closely related to the perturbation and inhomogeneity density of the deep material distribution.

In this paper, we use a novel approach, the multi-scale gravity analysis method, to extract the gravity anomaly signals originated from the Moho undulations and to determine the Moho topography beneath the whole of Iran. The inverted Moho topography for the Iran is consistent with that derived from the previous works. In addition, the Moho depth in the west is deeper than that in the east, demonstrating an earlier collision between the Arabian block and Eurasian plate in the west relative to that in the east.

In this paper, we introduce the geographically weighted regression (GWR) into the spatial scale segmentation method of the study area, the particle swarm optimization (PSO) algorithm to optimize the parameters of support vector machine (SVM) model, and finally construct the GWR-PSO-SVM coupling model. In addition, the traditional PSO-SVM coupling model is constructed to compare with the new method. The results show that in the specific category accuracy analysis, the overall prediction accuracy analysis and the area under the curve analysis, the evaluation results of this method are better than the traditional methods.

We establish a numerical model for the research area using basic information such as terrain, geological structure, etc. Then, we calculate and analyze the observation point’s subsidence, which is caused by the change of the load weight. We calculate the numerical model, which includes the across-fault site Xichang and the tailings nearby, using FLAC^3D software. The results show that the tailings accumulation is not the cause of the unusual change of the level observation data in the across-fault site Xichang.

This paper uses the Sentinel-1A SAR data from March 2017 to March 2018 to obtain the ground deformation of Chengdu's main urban area by using PSI and SBAS technologies. The distribution information, combined with ground level data, is used to evaluate the accuracy of the InSAR results. The reasons for the ground subsidence are analyzed. The results show that most areas of Chengdu are stable, and the deformation interval is mainly concentrated at －5~5 mm/a; the ground subsidence is mainly located outside the first ring line, and the uneven settlement of the main stations and surrounding areas of metro lines 5 and 6 is obvious. The sedimentation rate reached 20 mm/a, and the land subsidence in different urban areas such as Chenghua district and Jinjiang district differs. The annual average rate is in the range of 5~15 mm/a, and the correlation between PSI and SBAS is higher.

In order to identify potential seismogenic faults in the central part of Taiyuan basin, we carry out shallow seismic exploration of Tianzhuang fault. The results show that: 1) Tianzhuang fault can be divided into three sections, in which the north branch faults are the main faults. 2) Except for the western end of the fault and the turning section of the middle-eastern segment, the other sections are similar to the “Y” structure. 3) The fracture bandwidth of the eastern segment is the largest and the smallest. The active ages and slip rates of the faults are determined by borehole profiles and chronological methods. The active ages of the middle part of the fault are late Late Pleistocene, the minimum buried depth of the upper fault point is 39.3 m, the maximum fault distance since late Pleistocene is 2.9 m, and the maximum slip rate is 0.041 5 mm/a. The active ages of the western and eastern segments are middle Pleistocene, and the minimum buried depth of the upper fault point at the turning point of the middle-eastern segment is 37.4 m. Since the late Pleistocene, the maximum fault distance is 2.7 m and the maximum slip rate is 0.046 1 mm/a. Based on the fracture length of bedrock revealed by shallow earthquake, seismic moment method is used to analyze the seismic risk probability of Tianzhuang fault, and the maximum potential magnitude and seismogenic probability of the fault are determined.

In this paper, we obtain waveforms from an M_W5.7 deep-source earthquake with a depth of 554.9 km that occurred at the junction of Heilongjiang province and Jilin province (131.09°E, 43.32°N) on May 10, 2011. We analyze high-frequency (0.5 to 2 Hz) radial and vertical data from 22 NECESSArray stations, which are located in the Songliao basin. Using the effect layer on travel-time delays, and amplitudes of the P wave and Ps converted waves, we obtain the shear velocities on the top and bottom of the sediment layer using a grid-search method. The results show that the shear velocity on the top of the sediments below 22 stations is 0.1 to 1.0 km/s. The thickness of the basin is 0 to 6.5 km. Our results obtained in this paper generally agree with other studies, with some discrepancies at the edge, indicating that velocity structures of the sedimentary basin can be obtained through high-frequency Ps converted wave from local deep-source waveform data.