Geodesy and Geodynamics最新文献

We used the geological map and published rock density measurements to compile the digital rock density model for the Hong Kong territories. We then estimated the average density for the whole territory. According to our result, the rock density values in Hong Kong vary from 2101 to 2681 kg·m⁻³. These density values are typically smaller than the average density of 2670 kg·m⁻³, often adopted to represent the average density of the upper continental crust in physical geodesy and gravimetric geophysics applications. This finding reflects that the geological configuration in Hong Kong is mainly formed by light volcanic formations and lava flows with overlying sedimentary deposits at many locations, while the percentage of heavier metamorphic rocks is very low (less than 1%). This product will improve the accuracy of a detailed geoid model and orthometric heights.

The availability of many high-degree Global Geopotential Models (GGMs), namely EGM2008, EIGEN-6C4, GECO, SGG-UGM-1, SGG-UGM-2, XGM2019e_2159, and GGMPlus, challenges users regarding which model is best for Vietnam. This study, therefore, evaluates their performance by comparing them with GNSS/leveling data over Vietnam. Results show that their absolute and relative performances are largely independent of topographic conditions and geographical location and can be ranked into three classes: (1) XGM2019e_2159 has the highest accuracy, (2) the models EIGEN-6C4, GECO, SGG-UGM-1, SGG-UGM-2, and GGMPlus, have a very similar level of medium accuracy, while (3) EGM2008 is found to be the least accurate. In an absolute sense, the differences between GNSS/leveling and EGM2008-based height anomalies have a standard deviation (STD) of 0.290 ± 0.010 m, whereas, for XGM2019e_2159, this is 0.156 ± 0.006 m. All other models have STDs of (0.18–0.19) ± 0.007 m. Regarding relative performance without fitting, all GGMs have comparable accuracies for baseline length of 5–20 km, while for baselines longer than 20 km, the STD of XGM2019e_2159 is 1.5 ppm–0.5 ppm (approximately 19%–40%) lower compared with EGM2008, and 0.5 ppm–0.25 ppm (approximately 7%–36%) lower compared with EIGEN6C4, GECO, SGG-UGM-1, SGG-UGM-2, and GGMPlus. In addition, the STDs decrease significantly from 20 to 12 ppm in the range of 5–10 km, slightly from 12 to 6 ppm for 10–35 km, very slightly from 6 to 2.5 ppm for 35–200 km, and then remain almost unchanged for longer baselines. After fitting, the relative accuracies of all GGMs are at the same level with negligible STD/RMSE values. Furthermore, only EGM2008 experiences significant regional differences, while other GGMs show more homogeneous spatial variation of absolute accuracy over Vietnam. These findings can contribute to the development of local quasigeoid models in Vietnam and may be helpful with the improvement of GGMs in the future.

Sentinel-1A/B data are crucial for retrieving numerical information about surface phenomena and processes. Coregistration of terrain observation by progressive scans (TOPS) data is a critical step in its application. TOPS data must be fundamentally co-registered with an accuracy of 0.001 pixels. However, various decorrelation factors due to natural vegetation and seasonal effects affect the coregistration accuracy of TOPS data. This paper proposed an enhanced spectral diversity coregistration method for dual-polarimetric (PolESD) Sentinel-1A/B TOPS data. The PolESD method suppresses speckle noise based on a unified non-local framework in dual-pol Synthetic Aperture Radar (SAR), and extracts the phase of the optimal polarization channel from the denoised polarimetric interferometric coherency matrix. Compared with the traditional ESD method developed for single-polarization data, the PolESD method can obtain more accurate coherence and phase and get more pixels for azimuth-offset estimation. In bare areas covered with low vegetation, the number of pixels selected by PolESD is more than the Boxcar method. It can also correct misregistration more effectively and eliminate phase jumps in the burst edge. Therefore, PolESD will help improve the application of TOPS data in low-coherence scenarios.

Precise Point Positioning (PPP) technology has developed into a potent instrument for geodetic positioning, ionospheric modeling, tropospheric atmospheric parameter detection, and seismic monitoring. As atmospheric reanalysis data products' accuracy and spatiotemporal resolution have improved recently, it has become important to apply these products to obtain high-accuracy tropospheric delay parameters, like zenith tropospheric delay (ZTD) and tropospheric horizontal gradient. These tropospheric delay parameters can be applied to PPP to reduce the convergence time and to increase the accuracy in the vertical direction of the position. The European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) atmospheric reanalysis data is the latest product with a high spatiotemporal resolution released by the European Center for Medium-Range Weather Forecasts (ECMWF). Only a few researches have evaluated the application of ERA5 data to Global Navigation Satellite System (GNSS) PPP. Therefore, this study compared and validated the ZTD products derived from ERA5 data using ZTD values provided by 290 global International GNSS Service (IGS) stations for 2016–2017. The results indicated a stable performance for ZTD, with annual average bias and RMS values of 0.23 cm and 1.09 cm, respectively. Further, GNSS observations for one week in each of the four seasons (spring: DOY 92–98; summer: DOY 199–205; autumn: DOY 275–281; and winter: DOY 22–28) from 34 multi-GNSS experiments (MGEX) stations distributed globally in 2016 were considered to evaluate the performance of ERA5-derived tropospheric delay products in GNSS PPP. The performance of ERA5-enhanced PPP was compared with that of the two standard GNSS PPP schemes (without estimated tropospheric horizontal gradient and with estimated tropospheric horizontal gradient). The results demonstrated that ERA5-enhanced GNSS PPP showed no significant improvement in the convergence times in both the Eastern (E) and Northern (N) directions, while the average convergence time over four weeks in the vertical (U) direction improved by 53.3% and 52.7%, respectively (in the case of pngm station). The average convergence times for each week in the U direction of the northern and southern hemisphere stations indicated a decrease of 16.3%, 12.6%, 9.6%, and 9.1%, and 16.9%, 9.6%, 8.9%, and 14.5%, respectively. Regarding positioning accuracy, ERA5-enhanced PPP showed an improvement of 13.3% and 16.2% over the two standard PPP schemes in the U direction, respectively. No significant improvement in the positioning performance was observed in both the E and N directions. Thus, this study demonstrated the potential application of the ERA5 tropospheric parameters-augmented approach to Beidou navigation and positioning.

Stochastic models play an important role in achieving high accuracy in positioning, the ideal estimator in the least-squares (LS) can be obtained only by using the suitable stochastic model. This study investigates the role of variance component estimation (VCE) in the LS method for Precise Point Positioning (PPP). This estimation is performed by considering the ionospheric-free (IF) functional model for code and the phase observation of Global Positioning System (GPS). The strategy for estimating the accuracy of these observations was evaluated to check the effect of the stochastic model in four modes: a) antenna type, b) receiver type, c) the tropospheric effect, and d) the ionosphere effect. The results show that using empirical variance for code and phase observations in some cases caused erroneous estimation of unknown components in the PPP model. This is because a constant empirical variance may not be suitable for various receivers and antennas under different conditions. Coordinates were compared in two cases using the stochastic model of nominal weight and weight estimated by LS-VCE. The position error difference for the east-west, north-south, and height components was 1.5 cm, 4 mm, and 1.8 cm, respectively. Therefore, weight estimation with LS-VCE can provide more appropriate results. Eventually, the convergence time based on four elevation-dependent models was evaluated using nominal weight and LS-VCE weight. According to the results, the LS-VCE has a higher convergence rate than the nominal weight. The weight estimation using LS-VCE improves the convergence time in four elevation-dependent models by 11, 13, 12, and 9 min, respectively.

The space constellation of the BeiDou navigation satellite system (BDS) is a hybrid constellation containing medium earth orbit (MEO) satellites, geostationary earth orbit (GEO) satellites, and inclined geosynchronous orbit (IGSO) satellites. Due to the geosynchronous characteristics of GEO and IGSO, GEO satellites and IGSO satellites often need to perform orbital maneuvers, which can affect the signal-in-space (SIS) availability performance of BeiDou satellites. A two-step detection method for BeiDou satellite orbital maneuvers has been proposed in this paper. The first step is to identify orbital maneuvers based on time series analysis of broadcast ephemeris, and the second step is to verify orbital maneuvers based on bidirectional orbit prediction. The two-step detection method was used to detect the orbital maneuvers of BeiDou satellites in 2019. Through the double guarantees of identification and verification, the detection accuracy of BeiDou satellite orbital maneuvers has been effectively improved. And the orbital maneuver detection results are continued to be used to assess the SIS availability of BeiDou satellites. The results show that the availability loss of GEO satellite orbital maneuvers is about 0.45%–1.07%, and the availability loss of IGSO satellite orbital maneuvers is about 0.12%–0.19%.

Joint inversion is one of the most effective methods for reducing non-uniqueness for geophysical inversion. The current joint inversion methods can be divided into the structural consistency constraint and petrophysical consistency constraint methods, which are mutually independent. Currently, there is a need for joint inversion methods that can comprehensively consider the structural consistency constraints and petrophysical consistency constraints. This paper develops the structural similarity index (SSIM) as a new structural and petrophysical consistency constraint for the joint inversion of gravity and vertical gradient data. The SSIM constraint is in the form of a fraction, which may have analytical singularities. Therefore, converting the fractional form to the subtractive form can solve the problem of analytic singularity and finally form a modified structural consistency index of the joint inversion, which enhances the stability of the SSIM constraint applied to the joint inversion. Compared to the reconstructed results from the cross-gradient inversion, the proposed method presents good performance and stability. The SSIM algorithm is a new joint inversion method for petrophysical and structural constraints. It can promote the consistency of the recovered models from the distribution and the structure of the physical property values. Then, applications to synthetic data illustrate that the algorithm proposed in this paper can well process the synthetic data and acquire good reconstructed results.

In recent years, karst construction projects in the built-up area of Wuhan (capital of Hubei Province, China) are increasing, and the karst geological disasters have aroused social concerns. The actual engineering projects usually use shallow geophysical exploration methods to explore karst. This paper uses Spatial Auto-Correlation Method (SPAC) and electromagnetic Computerized Tomography (CT) to detect karst in urban built-up areas. Depending on the different physical properties of rock and soil, the SPAC method can better reveal the interface between soil and rock strata and the interface between soil layers. The electromagnetic CT method can identify strata according to the apparent absorption coefficient, which can better reveal the interface between soil and rock, the interface between the more intact and weathered rock. The SPAC method is mainly qualitative to measure the low-speed area, namely, the wrong geological body i.e., karst cave, but also can detect the fracture zone or filling mode of karst cave, and at the same time, cannot use exploration holes or logging observation. The electromagnetic CT method can accurately detect the location and scale of the karst caves and has a higher accuracy detecting karst bands. In addition, exploration holes or well logging observations are also expected to be conducted, and their detection effect is greatly affected by lithology.

Two-Line Element (TLE) datasets are the only orbital data source of Earth-orbiting space objects for many civil users for their research and applications. The datasets have uneven qualities that may affect the reliability of the propagated positions of space objects using a single TLE. The least squares approach to use multiple TLEs also suffers from the poor quality of some TLEs, and reliable error information cannot be available. This paper proposes a simplex algorithm to estimate an optimal TLE from multiple TLEs and obtain the uncertainty of each element. It is a derivative-free technique that can deal with various orbit types. Experiments have demonstrated that using the TLE estimated from the simplex method is more reliable, stable, and effective than those from the batch least squares method. As an application example, the optimal TLE and its uncertainty are used for predicting the fallen area, keeping the actual fallen site in the prediction areas.