Journal of Surveying Engineering

The study and understanding of the geodynamic aspects on the planet require global geodetic references with an order of accuracy better than the magnitude of the effects and with consistency and reliability. In this sense, this paper aims to present the new gravimetric infrastructure in the Brazilian southeast. A set of 22 absolute gravity stations were measured and materialized in the region. Additionally, gravity densification was carried out throughout the region aiming at a quasigeoid model. In the last decade, almost 3,000 points were collected. The model was computed by the least-squares collocation methodology using a recent geopotential model in the long- wavelength component and recent digital terrain model to compute the terrain correction. The quasigeoid model was validated with 136 global navigation satellite system (GNSS)/leveling stations and the RMS is 0.25 m. Furthermore, GNSS/leveling stations were compared with five recent geopotential models and the mean RMS difference was 0.28 m. Absolute and relative gravity stations will improve the national geodetic infrastructure, especially concerning the International Height Reference Frame and the International Gravity Reference Frame.

In this study, the relationships between possible ionospheric total electron content (TEC) anomalies and earthquake focal depths and fault types were investigated using 3,099 global earthquakes with $\mathrm{Mw}\ge 6.0$ between 2000 and 2020. The relationship between the ionospheric TEC changes and earthquakes has been previously discussed in the literature. However, very few studies have examined the relationship between the focal depths and the fault types of these earthquakes. In general, three indices, namely the disturbance storm-time index (Dst), the planetary geomagnetic activity index (Kp), and the solar flux (F10.7), are used to characterize the space weather conditions (SWC) that affect TEC anomalies and to identify the active/quiet days for future earthquakes. In this study, 13 different indices were used: indices that measured solar activity included proton flux (Pf) at six different energy levels, F10.7, and extreme ultraviolet (${\mathrm{EUV}}_{0.1-50\mathrm{nm}}$ and ${\mathrm{EUV}}_{26-34\mathrm{nm}}$). Meanwhile, geomagnetic storm indices included Dst, Kp, the $z\text{-}\text{component}$ of the magnetic field index (Bz), and proton density ($P_d$). By using the ionospheric TEC values derived from global ionosphere maps (GIM-TEC), both negative and positive ionospheric TEC anomalies were observed for 15 days before and 4 days after the earthquakes using a statistical analysis technique that involved a 15-day moving median. The earthquakes were grouped according to their fault types (normal, thrust, and strike-slip) and focal depths (shallow, intermediate, and deep). Their relationships with the negative and positive TEC anomalies in the quiet days before the earthquake were examined. Negative and positive anomalies were observed approximately 3–12 days before earthquakes that occurred on normal faults, approximately 5–8 days before earthquakes that occurred on thrust faults, and approximately 1–12 days before earthquakes that occurred on strike-slip faults. The average TEC anomaly changes were calculated to be 43.4% total electron content unit (TECU) for normal faults, 44.8% TECU for thrust faults, and 41.3% TECU for strike-slip faults. Positive anomaly values were exhibited by larger earthquakes on normal and thrust faults, whereas negative anomaly values tended to occur on strike-slip faults. Negative and positive TEC anomalies were detected around 3–12 days before shallow earthquakes, around 1–13 days before intermediate-depth earthquakes, and around 1–12 days before deep earthquakes. The average TEC anomaly changes were calculated to be 44.4% TECU for shallow earthquakes, 43.3% TECU for intermediate-depth earthquakes, and 42.6% TECU for deep earthquakes. Positive anomaly values were also found to be higher than the negative anomaly values in each group. We propose that there is a relationship between the ionospheric TEC anomalies that occur before large earthquakes and their fault types and focal depths.

Ocean tide loading (OTL) correction is becoming more and more crucial in high precision geodetic data processing. The published global ocean tide models show good agreement in deep oceans and exhibit differences in complex coastal areas, along with subsequent OTL displacement modeling differences. In order to select a suitable high precision ocean tide model for China’s coastline, both the tide gauge stations and multifrequency Global Navigation Satellite System (multi-GNSS) observations are used for validating eight global ocean tide models and a regional ocean tide model. First, 18.6 year’s tide gauge data were employed to generate the harmonic parameters to evaluate the accuracy of 9 ocean tide models. The DTU10 model shows better agreement with tide gauge stations. Second, combining the Global Positioning System (GPS) and global navigation satellite system (GLONASS) kinematic precise point positioning (PPP) was improved based on the algorithm of GPS kinematic PPP to estimate the effects of three-dimensional (3D) OTL displacements. Then, continuous observations of 23 coastal sites from the Crustal Movement Observation Network of China from January 1, 2016 to December 31, 2019 were collected to generate 3D OTL displacement amplitudes and phase lags of 8 constituents using GPS/GLONASS solutions and harmonic analysis. By comparison with DTU10 model predictions, the results present that the combined GPS/GLONASS-derived OTL displacement model showed good consistency with the model predictions in all three components. Third, the GPS/GLONASS-derived OTL displacement estimates were taken as reference to calculate the root mean square (RMS) misfit with model values from 9 ocean tide models. The results show the DTU10 model agreed with the multi-GNSS-derived OTL displacement estimates best in all three components. The RMS misfits of all constituents are less than 1.8, 1.3, and 1.8 mm in the vertical, east, and north directions, respectively. Finally, through comparing the correction effects from different model predictions on the coordinate time series of the GNSS stations, the results also show that the DTU10 model correction effect in the GNSS position time series was better than that of other global or regional ocean tide models. That DTU10 model had good adaptability in the China coast areas was proven, so that it can be recommended for more data processing, such as leveling, gravity, and other geodetic data processing.

When an electromagnetic wave passes through the atmosphere, due to variation of atmospheric parameters, its propagation path is usually altered and the propagation speed also changes. Therefore, errors will be induced in triangulation measurement with electronic surveying robots, delimiting the accuracy of trigonometric leveling. Targeting at improving the accuracy of trigonometric leveling, a correction model based on atmospheric refraction coefficients is proposed in this article. First, based on the meteorological parameters collected on-site and Rüeger equation, influence of the meteorological parameters (e.g., temperature, atmospheric pressure, humidity, and ${\mathrm{CO}}_2$) on the refractive index are analyzed. Furthermore, gradient models of temperature, humidity, and atmospheric pressure with reference to height are established. In order to build the atmospheric gradient models of the optical path, height difference between the optical path and the ground is estimated with a precise digital elevation model generated by laser scanning. On this basis, the vertical atmospheric refraction coefficient model is proposed and used to correct the trigonometric leveling data measured by surveying robots. By conducting experimental studies over two open-pit iron mines with large topographic relief and comparing with first-class leveling data, reliability of the proposed atmospheric refraction coefficient model is assessed. The outcome of this article has demonstrated that by adopting the proposed model, accuracy of trigonometric leveling can meet the requirements of second-class leveling.

The prediction of dam settlement data plays an important role in analyzing whether the dam is in a safe operation state. But in the field of surveying engineering, the original data measured by instruments will inevitably have random and unpredictable random errors, and the settlement of dams usually has a strong correlation with environmental parameters. In this study, the influence of random error and environmental parameters on dam settlement prediction is discussed, and a prediction model based on multi-input long short-term memory (LSTM) network and random error extraction is proposed. Through the settlement data of a concrete face rockfill dam, the analysis shows that removing random errors can significantly improve the short-term prediction performance and considering environmental parameters can significantly improve the long-term prediction performance. In addition, through comparison and generalization experiments, this method not only has higher prediction accuracy, but also can be applied to other surveying and mapping engineering fields.

This study investigated the accuracy improvement of the gravimetric geoid model in Turkey using densified grids of the gravity anomalies with the least-squares modification of the Stokes integral with additive corrections (LSMSA) method. In LSMSA computations of the geoid models, the surface gravity anomalies, which were derived from the complete Bouguer anomaly grid data set by forward modeling the topographic masses, were used. In the computations, in addition to the original 5′-resolution ($\sim 9\mathrm{km}$) Bouguer anomaly data set, its densified versions to 1′-resolution ($\sim 2\mathrm{km}$) also were used. The densification of the gravity grids was carried out using both planar- and spherical-type complete Bouguer anomalies. Thus, the effects of both gravity grid densification and the applied approximation for the Bouguer reduction process in gravity gridding on the geoid model accuracies were examined in order. The Bouguer gravity reductions were carried out using classical formulas for the planar approximation, whereas the gravimetric terrain corrections from the high-resolution SRTM2gravity global model were employed for the spherical approximation in numerical tests. The calculated geoid models were validated at 100 homogeneously distributed GPS/leveling (GPS means Global Positioning System) benchmarks over the country. In the tests, the geoid undulations derived from the models also were compared with the observations at six tide gauge stations along the coastlines. The latter provided an additional check for the assessment of the models’ compatibility at the coastal boundaries. In conclusion, the accuracy of the best geoid model solution (8.6 cm by means of the standard deviation of geoid undulation differences at GPS/leveling benchmarks) was achieved using 1′-resolution gravity anomalies restored from the spherical complete Bouguer anomalies in Turkey.

Due to the joint constraints of boundary conditions, including seabed topography, driven water level at open boundary (DWLOB), and bottom friction coefficient (BFC), the accuracy of tidal numerical modeling in coastal and offshore waters is still relatively low. A two-dimensional tide numerical model (2D-MIKE21) based on synchronously optimized boundary conditions was used to simulate a tidal model of the Haizhou Bay of the Yellow Sea in China. The water depth with higher resolution and accuracy than the charted depth was used as the seabed topography. The DWLOB was calculated from 13 tidal constituents (including the two long-period constituents, Sa and Ssa) of the regional tidal model of China’s seas, CST1. The calculation of the BFC takes into account the spatial variation of water depth. For validation, we compared the simulated water level heights in this article and the tidal forecasts from the CST1 model with the 1-month observations at three tide gauges in Haizhou Bay and six points altimetry data of Jason-1, Jason-2, and Jason-3 satellites at the same time in 2007, which passed the modeling domain, and the former had a smaller root-mean square (RMS) than the latter. We compared the 13 dominant tidal constituents, which were from the 1-year simulated water level heights in this article by using tidal harmonic analysis and the one from the CST1 models, with that from the altimetry data of Jason-1, Jason-2, and Jason-3 satellites between 2002 and 2019. The root sum square (RSS) of the former was 8.16 cm, and that of the latter was 8.94 cm.