Permanent Global Navigation Satellite System Research Articles

Temporal gravimetry, campaign and permanent GNSS, and interferometric radar techniques: A comparative approach to quantifying land deformation rates in coastal Texas

Land subsidence and local sea-level rise are well-known on-going hazards that negatively impacting coastal regions, exacerbating coastal flooding, threatening infrastructure stability, accelerating erosion, and amplifying the risks of inundation and property damage. This study used four techniques to quantify land deformation rates in the Texas Coastal Bend region and to investigate the controlling factors on two different spatiotemporal scales: (1) local scale, where biweekly temporal gravity and campaign Global Navigation Satellite System (GNSS) measurements were acquired at six locations over 2 years (October 2020–September 2022); and (2) regional scale, where vertical displacement time series were extracted from the Interferometric Synthetic Aperture Radar (InSAR) and 15 permanent GNSS stations over 5 years (January 2017–November 2021). The observed inconsistency between land deformation rates derived from gravity (range: −33.32 ± 149.30 to +338.68 ± 107.93 mm/yr) and campaign GNSS (range: −17.91 ± 14.90 to +5.69 ± 9.93 mm/yr) surveys could be attributed to the short campaign period and the infrequency of data acquisition. The InSAR-derived deformation rates (range: −12.16 ± 0.12 to +11.70 ± 0.00 mm/yr) were consistent with the permanent GNSS-derived rates (range: −14.0 ± 0.6 to +9.0 ± 3.0 mm/yr); both indicated spatiotemporal variability in land deformation rates across the Texas Coastal Bend. A total of 4 coastal towns (−2.3 ± 3.3 mm/yr), 3 cities (−1.4 ± 2.6 mm/yr), 3 inland towns (−3.6 ± 4.2 mm/yr), and 7 industrial plants (−3.8 ± 5.8 mm/yr) were found to have significant land subsidence rates due to sediment compaction, growth faulting, oil/gas extraction, and groundwater extraction. Results of this study emphasize the advantages and limitations of four different techniques in quantifying land deformation rates; can enhance estimates of local sea-level rise; and offer valuable insights to support coastal communities in mitigating the impacts of land subsidence and improving their resilience.

Local Gravity and Geoid Improvements around the Gavdos Satellite Altimetry Cal/Val Site

The isle of Gavdos, and its wider area, is one of the few places worldwide where the calibration and validation of altimetric satellites has been carried out during the last, more than, two decades using dedicated techniques at sea and on land. The sea-surface calibration employed for the determination of the bias in the satellite altimeter’s sea-surface height relies on the use of a gravimetric geoid in collocation with data from tide gauges, permanent global navigation satellite system (GNSS) receivers, as well as meteorological and oceanographic sensors. Hence, a high-accuracy and high-resolution gravimetric geoid model in the vicinity of Gavdos and its surrounding area is of vital importance. The existence of such a geoid model resides in the availability of reliable, in terms of accuracy, and dense, in terms of spatial resolution, gravity data. The isle of Gavdos presents varying topographic characteristics with heights larger than 400 m within small spatial distances of ~7 km. The small size of the island and the significant bathymetric variations in its surrounding marine regions make the determination of the gravity field and the geoid a challenging task. Given the above, the objective of the present work was two-fold. First, to collect new land gravity data over the isle of Gavdos in order to complete the existing database and cover parts of the island where voids existed. Relative gravity campaigns have been designed to cover as homogenously as possible the entire island of Gavdos and especially areas where the topographic gradient is large. The second focus was on the determination of a high-resolution, 1′×1′, and high-accuracy gravimetric geoid for the wider Gavdos area, which will support activities on the determination of the absolute altimetric bias. The relative gravity campaigns have been designed and carried out employing a CG5 relative gravity meter along with geodetic grade GNSS receivers to determine the geodetic position of the acquired observations. Geoid determination has been based on the newly acquired and historical gravity data, GNSS/Leveling observations, and topography and bathymetry databases for the region. The modeling was based on the well-known remove–compute–restore (RCR) method, employing least-squares collocation (LSC) and fast Fourier transform (FFT) methods for the evaluation of the Stokes’ integral. Modeling of the long wavelength contribution has been based on EIGEN6c4 and XGM2019e global geopotential models (GGMs), while for the contribution of the topography, the residual terrain model correction has been employed using both the classical, space domain, and spectral approaches. From the results achieved, the final geoid model accuracy reached the ±1–3 cm level, while in terms of the absolute differences to the GNSS/Leveling data per baseline length, 28.4% of the differences were below the 1cmSij [km] level and 55.2% below the 2cmSij [km]. The latter improved drastically to 52.8% and 81.1%, respectively, after deterministic fit to GNSS/Leveling data, while in terms of the relative differences, the final geoid reaches relative uncertainties of 11.58 ppm (±1.2 cm) for baselines as short as 0–10 km, which improves to 10.63 ppm (±1.1 cm) after the fit.

Possible impact of construction activities around a permanent GNSS station – A time series analysis

Abstract In this article, we address the potential effects of construction activities around a permanent Global Navigation Satellite System (GNSS) station. The study is based on a consistent time series of GNSS observations collected over a span of almost 13 years and comprises an analysis in both observation and coordinate domains. The analysis in the observation domain revealed a significant increase of the code multipath for the C1C signal of GPS and GLONASS. In terms of standard deviations the values increased by 37 and 31%, respectively. No significant increase was observed for other signals. Interestingly, the analysis showed that the Galileo E5 AltBOC signal outperformed the other signals in distinguishing direct from indirect signals. In the coordinate domain, the relative GNSS solution results demonstrated an increase in root mean square error for the eastern component during the same period. Noteworthy, the observed increase in both domains coincided with the period of the highest level of construction activity around the GNSS station. These findings suggest that the construction activity near the station impacted the quality of GNSS observations and that the Galileo E5 AltBOC signal was better at compensating for local changes than other signals.

The analysis of crustal deformation patterns in the Tashkent region, Uzbekistan, derived from GNSS data over the period 2018–2023

The Tashkent region is one of the most tectonically and seismically active areas in Uzbekistan. Although it is highly significant, the understanding and quantification of current deformation processes are still incomplete, especially concerning space-based geodetic techniques like the Global Navigation Satellite System (GNSS). Using velocity field data from 16 permanent GNSS sites during 2018–2023, this paper analyzes the strain rate field and its spatial characteristics using an improved least squares collocation method. The results indicate a northeastward motion consistent with India-Eurasian convergence, with velocities ranging from 24.7 to 30.1 mm/yr and increasing from northwest to southeast. The region displays substantial positive dilation at a rate of 14.7 nanostrain/yr, while the neighboring areas demonstrate negative dilation ranging from −10 to −30 nanostrain/yr. The second strain rate invariant with an average value of 20 nanostrain/yr primarily occurs along the Karzhantau fault. The spatial features of strain rate fields delineate the extensional and compressional strain zones, bounded in the west by the Tien Shan orogenic belt. Therefore, these zones warrant increased attention due to their relatively higher seismic risk in the Tashkent region.

Analysis of Multipath Changes in the Polish Permanent GNSS Stations Network

This study examines the influence of multipath errors on Global Navigation Satellite System (GNSS) measurements collected at ASG-EUPOS reference stations between 2010 and 2021. Multipath occurs when GNSS signals reflect off surrounding objects before reaching the receiver antenna, leading to positioning errors. In the case of reference stations, all available mitigation techniques were used to minimize the impact of multipath. However, it is still detectable and affects the measurement results. For carrier phase differential positioning, it increases the ambiguous search space, which results in a decrease in determining rover—reference station vector accuracy. The study employs two linear combinations (Code-Minus-Carrier and Multipath Pseudorange Observable) to quantify the multipath effect on both pseudorange and carrier phase measurements. Based on the research, it was found that the multipath values changed depending on the change of the receiver and the terrain around the reference stations. The study observed a gradual decrease in multipath errors from 2010 to 2021, likely due to technological advancements in receiver design. No significant increase in multipath errors was observed due to environmental changes around the stations, suggesting a minimal influence from new reflecting objects nearby. Based on the analyses conducted, it is also recommended to perform periodic tests to detect incorrect receiver configuration or operation.

GNSS and Sentinel-1 InSAR Integrated Long-Term Subsidence Monitoring in Quetta and Mastung Districts, Balochistan, Pakistan

Land subsidence (LS) is a global phenomenon that has affected several urban centres around the world such as Jakarta (Indonesia), Mexico City (Mexico), Xi’an (China), and Iron County (US). It has mainly been attributed to anthropogenic activities such as groundwater exploitation, especially in unconsolidated aquifer systems rich in highly compressible clay and silt. The platy clay minerals rearrange into horizontal stacks after dewatering, leading to a volume change due to overburden. In this study, land subsidence is investigated in the Quetta and Mastung districts, Balochistan, Pakistan, by employing Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and groundwater level (GWL) variations. This study represents the first attempt in Pakistan to measure the long-term land subsidence by fusing GNSS and InSAR data for improved validity. InSAR data from the Sentinel-1 satellite in the Ascending (195 scenes) and Descending (183 scenes) tracks were used to analyse LS from December 2015 to December 2022. High-accuracy Trimble NetRS GNSS receivers were used in five locations from October 2006 to December 2022. An average subsidence ranging from 3.2 cm/y to 16 cm/y was recorded in the valley mainly due to the GWL decline and clay-rich sediments, which are prone to compaction due to dewatering. An accumulative LS of 2 m was recorded by the permanent GNSS station in central Quetta from October 2008 to January 2023 (14.2 years). An acceleration in the subsidence from 12 cm/y to 16.6 cm/y after 2016 was recorded by the continuous GNSS. Additionally, the InSAR and GNSS values were compared for validation, resulting in a good correlation between both techniques. A GWL decline ranging from 1.7 m to 6 m was recorded by the piezometers in Quetta during the period 1987–2022. Large- and small-scale fissures were observed in the study area during the surveys. These fissures are responsible for damage to the city’s infrastructure and aquifer contamination. The subsidence profile also agrees with the subsurface lithology. Our assessment concludes that Quetta may be the fastest-sinking metropolitan city in Pakistan. The overexploitation of groundwater and the population explosion may be the main contributing factors for the land subsidence.

Rapid Assessment of Landslide Dynamics by UAV-RTK Repeated Surveys Using Ground Targets: The Ca’ Lita Landslide (Northern Apennines, Italy)

The combined use of Uncrewed Aerial Vehicles (UAVs) with an integrated Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) module and an external GNSS base station allows photogrammetric surveys with centimeter accuracy to be obtained without the use of ground control points. This greatly reduces acquisition and processing time, making it possible to perform rapid monitoring of landslides by installing permanent and clearly recognizable optical targets on the ground. In this contribution, we show the results obtained in the Ca’ Lita landslide (Northern Apennines, Italy) by performing multi-temporal RTK-aided UAV surveys. The landslide is a large-scale roto-translational rockslide evolving downslope into an earthslide–earthflow. The test area extends 60 × 103 m2 in the upper track zone, which has recently experienced two major reactivations in May 2022 and March 2023. A catastrophic event took place in May 2023, but it goes beyond the purpose of the present study. A total of eight UAV surveys were carried out from October 2020 to March 2023. A total of eight targets were installed transversally to the movement direction. The results, in the active portion of the landslide, show that between October 2020 and March 2023, the planimetric displacement of targets ranged from 0.09 m (in the lateral zone) to 71.61 m (in the central zone). The vertical displacement values ranged from −2.05 to 5.94 m, respectively. The estimated positioning errors are 0.01 (planimetric) and 0.03 m (vertical). The validation, performed by using data from a permanent GNSS receiver, shows maximum differences of 0.18 m (planimetric) and 0.21 m (vertical). These results, together with the rapidity of image acquisition and data processing, highlight the advantages of using this rapid method to follow the evolution of relatively rapid landslides such as the Ca’ Lita landslide.

THE EFFECT OF SEASONAL VARIATION ON GNSS ZENITH TROPOSPHERIC DELAY

Abstract. The Global Navigation Satellite System (GNSS) signal experiences delays caused by the atmosphere, leading to the lengthening of the geometric path of the ray, commonly referred to as tropospheric delay. This delay is a significant source of error in GNSS positioning, contributing to a bias in the height component of several centimeters, even when meteorological data are simultaneously recorded and used in tropospheric models. In this study, considering seasonal variations, we investigated the impact of tropospheric delay on the GNSS height component. GNSS stations, part of the Turkish RTK CORS Network known as TUSAGA-Active (Turkish National Permanent GNSS Network Active), covered different heights over the 2014–2019 period. Daily coordinates of GNSS stations and tropospheric zenith delay were obtained through the GAMIT/GLOBK software solution.In the study, temperature, pressure, and relative humidity data of meteorological stations at different heights were converted to mean sea level. By using these values, interpolation estimates were made for the continuous GNSS stations in the same region with the IDW method. The most significant delay in GNSS signals occurs in July and August. This effect, which causes periodic changes in the zenith delay, varies inversely with the station's height. With the increase in the amount of water vapor in the atmosphere in parallel with the rise in the temperature in the summer months, it is seen that the stations at a low height are more exposed to the tropospheric effect than the stations at higher heights. In addition, GNSS stations' reduced meteorological values (temperature, pressure and relative humidity) show that the zenith delay values changed directly proportional to the temperature and inversely proportional to the pressure and relative humidity.

A Multi-Input Convolutional Neural Networks Model for Earthquake Precursor Detection Based on Ionospheric Total Electron Content

Earthquakes occur all around the world, causing varying degrees of damage and destruction. Earthquakes are by their very nature a sudden phenomenon and predicting them with a precise time range is difficult. Some phenomena may be indicators of physical conditions favorable for large earthquakes (e.g., the ionospheric Total Electron Content (TEC)). The TEC is an important parameter used to detect pre-earthquake changes by measuring ionospheric disturbances and space weather indices, such as the global geomagnetic index (Kp), the storm duration distribution (Dst), the sunspot number (R), the geomagnetic storm index (Ap-index), the solar wind speed (Vsw), and the solar activity index (F10.7), have also been used to detect pre-earthquake ionospheric changes. In this study, the feasibility of the 6th-day earthquake prediction by the deep neural network technique using the previous five consecutive days is investigated. For this purpose, a two-staged approach is developed. In the first stage, various preprocessing steps, namely TEC signal improvement and time-frequency representation-based TEC image construction, are performed. In the second stage, a multi-input convolutional neural network (CNN) model is designed and trained in an end-to-end fashion. This multi-input CNN model has a total of six inputs, and five of the inputs are designed as 2D and the sixth is a 1D vector. The 2D inputs to the multi-input CNN model are TEC images and the vector input is concatenated space weather indices. The network branches with the 2D inputs contain convolution, batch normalization, and Rectified Linear Unit (ReLU) activation layers, and the branch with the 1D input contains a ReLU activation layer. The ReLU activation outputs of all the branches are flattened and then concatenated. And the classification is performed via fully connected, softmax, and classification layers, respectively. In the experimental work, earthquakes with a magnitude of Mw5.0 and above that occurred in Turkey between 2012 and 2019 are used as the dataset. The TEC data were recorded by the Turkey National Permanent GNSS Network-Active (TNPGN-Active) Global Navigation Satellite System (GNSS) stations. The TEC data five days before the earthquake were marked as “precursor days” and the TEC data five days after the earthquake were marked as “normal days”. In total, 75% of the dataset is used to train the proposed method and 25% of the dataset is used for testing. The classification accuracy, sensitivity, specificity, and F1-score values are obtained for performance evaluations. The results are promising, and an 89.31% classification accuracy is obtained.

Kinematic Rupture Model of the 6 February 2023 Mw 7.8 Türkiye Earthquake from a Large Set of Near-Source Strong-Motion Records Combined with GNSS Offsets Reveals Intermittent Supershear Rupture

ABSTRACT The 2023 Mw 7.8 southeast Türkiye earthquake was recorded by an unprecedentedly large set of strong-motion stations very close to its rupture, opening the opportunity to observe the rupture process of a large earthquake with fine resolution. Here, the kinematics of the earthquake source are inferred by finite-source inversion based on strong-motion records and coseismic offsets from permanent Global Navigation Satellite Systems stations. The strong-motion records at stations NAR and 4615, which are the closest to the splay fault (SPF) where the rupture initiated and which were previously interpreted to contain the signature of supershear rupture speeds, are successfully modeled here by a subshear rupture propagating unilaterally to the northeast. Once the rupture on the SPF reaches the east Anatolian fault (EAF), it propagates on the EAF bilaterally, extending about 120 km northeast and 180 km southwest. To the south, the depth extent of the rupture decreases, as it passes a bend of the EAF. Although the rupture velocity remains globally subshear along the EAF, we identify three portions of the fault where the rupture is transiently supershear. The transitions to supershear speed coincide with regions of reduced fault slip, which suggests supershear bursts generated by the failure of local rupture barriers. Toward the southwest termination, the rupture encircles an asperity before its failure, which is a feature that has been observed only on rare occasions. This unprecedented detail of the inversion was facilitated by the proximity to the fault and the exceptional density of the accelerometric network in the area.

GPS data analysis and geodetic velocity field investigation in Greece, 2001–2016

In this study, an updated crustal velocity field for the Greece area was estimated using a time series analysis that covers a duration of 16 years (2001–2016) from 227 Global Navigation Satellite System (GNSS) permanent stations. The GPS processing was carried out using GNSS Analysis software at MIT (GAMIT) and the velocity field expressed with respect to Eurasian plate. For the time series analysis, we applied a robust Median Interannual Difference Adjusted for Skewness trend estimator to mitigate the effects of discontinuities due to geophysical phenomena on the estimation of geodetic velocities and their uncertainties. The main earthquake events that occurred in the GPS time series analysis in the study area are analyzed, providing the co-seismic displacements in the permanent GNSS stations. We also compare our geodetic velocities with five previous publications, where we found consistency at the mm/year level, leading to reliable results for the geodynamic behavior of the Greek area, providing a dense velocity field.

Characterization of the co-seismic pattern and slip distribution of the February 06, 2023, Kahramanmaraş (Turkey) earthquakes (Mw 7.7 and Mw 7.6) with a dense GNSS network

Two consecutive earthquakes with the magnitudes of Mw 7.7 and 7.6 (February 06, 2023) occurred on the East Anatolian Fault Zone (EAFZ) segments and unfortunately resulted in significant devastation to human life and cities in Turkey and Syria. In this study, we aimed to analyse the co-seismic displacements and fault slip distributions of these seismic events. Our unique high-spatial-resolution Global Navigation Satellite System (GNSS) network (comprising 73 permanent GNSS stations and 40 campaign observation sites), providing the recent geodetic dataset for the region, allows better constraint of the co-seismic surface displacements and slip distributions of both earthquakes. The three largest total displacements were identified as 466 cm, 362 cm, and 360 cm. The Fault interactions along the EAFZ were obvious during the consecutive earthquakes. The ruptures mainly occurred in the left-lateral components of the fault segments, with the maximum slips of 7.25 m and 9.43 m for the first event along the EAFZ and the second event on the Çardak Fault, respectively.

Introducing the Idea of Classifying Sets of Permanent GNSS Stations as Benchmarks for Hydrogeodesy

AbstractWe propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed.

Estimation of Height Changes of Continuous GNSS Stations in the Eastern Anatolia Region during the Seasonal Variation

Estimating the height component of Global Navigation Satellite System (GNSS) stations is widely known to be more challenging than estimating the horizontal position. In this study, we utilized height time series data from 37 continuous GNSS stations that were part of the Turkish RTK CORS Network called TUSAGA-Active (Turkish National Permanent GNSS Network Active). The data covered the period from 2014 to 2019, and the selection of stations focused on the Eastern Anatolia region of Turkey due to its topographic characteristics and the pronounced influence of seasonal changes, which facilitated the interpretation of the effects on the height component. The daily coordinates of the GNSS stations were derived using the GAMIT/GLOBK software solution. We identified statistically significant trends, periodic variations, and stochastic components associated with the stations by applying time series analysis to these daily coordinate values. As a result, the vertical velocities of the GNSS stations were determined, along with their corresponding standard deviations. Furthermore, examining the height components of the continuous GNSS stations revealed seasonal effects. We aimed to investigate the potential relationship between these height components and meteorological parameters. The study provides evidence of the interconnectedness between the height components of continuous GNSS stations and various meteorological parameters. Simple linear regression analysis and ARMA time series modeling were utilized to establish this relationship.

GPS + Galileo + BDS-3 medium to long-range single-baseline RTK: an alternative for network-based RTK?

AbstractThanks to the development of the real-time kinematic (RTK) algorithm and the emerging Global Navigation Satellite System (GNSS), especially for Galileo and BeiDou-3, reliable positioning accuracy for medium and long-baseline RTK became possible globally. Moreover, with the development of the GNSS receiver hardware, baseline length limitations due to radio-based communications are removed thanks to internet-based communication. In this work, single-baseline RTK, incorporated partial ambiguity resolution with troposphere and ionosphere weighting, using GPS (G), Galileo (E), BeiDou-3 (C3) and multi-GNSS (GE and GEC3), is conducted with real GNSS data of EUREF Permanent GNSS network under three different cutoff angles (10°, 20°, and 30°) for six different lengths of baselines (~50, ~150, ~250, ~350, ~450, and ~550 km). The results show that the multi-GNSS RTK solution significantly contributed to the positioning accuracy and convergence time of the single-system RTK solutions. Based on the results, non-available epoch-wise solutions for the high-degree cutoff angles are more obvious for the single-system RTK, whereas multi-GNSS solutions provide 100% solutions for each cutoff angle and baseline. The results indicate that instantaneous and a few epochs single-epoch ambiguity resolution is feasible for 50, 150, 250 and 350 km baseline lengths for multi-GNSS RTK. Based on the positioning results, horizontal–vertical positioning improvements of multi-GNSS RTK (GEC3) compared with the single-system GPS RTK are found as 50%–37%, 40%–35%, 55%–47%, 53%–54%, 57%–49% and 57%–49% for 50, 150, 250, 350, 450 and 550 km, respectively, under a 10° cutoff angle. For 20° and 30° cutoff angles, the accuracy improvements are much higher. The convergence time improvements (n/e/u) of multi-GNSS RTK (GEC3) compared with the single-system GPS RTK are found as 86/92/75%, 77/67/72%, 75/77/83%, 53/56/52%, 69/49/62%, and 52/45/39% for 50, 150, 250, 350, 450 and 550 km, respectively, under a 10° cutoff angle.

Assessment of GNSS zenith tropospheric delay responses to atmospheric variables derived from ERA5 data over Nigeria

Tropospheric delay is a major error caused by atmospheric refraction in Global Navigation Satellite System (GNSS) positioning. The study evaluates the potential of the European Centre for Medium-range Weather Forecast (ECMWF) Reanalysis 5 (ERA5) atmospheric variables in estimating the Zenith Tropospheric Delay (ZTD). Linear regression models (LRM) are applied to estimate ZTD with the ERA5 atmospheric variables. The ZTD are also estimated using standard ZTD models based on ERA5 and Global Pressure and Temperature 3 (GPT3) atmospheric variables. These ZTD estimates are evaluated using the data collected from the permanent GNSS continuously operating reference stations in the Nigerian region. The results reveal that the Zenith Hydrostatic Delay (ZHD) from the LRM and the Saastamoinien model using ERA5 surface pressure are of identical accuracy, having a Root Mean Square (RMS) error of 2.3 mm while the GPT3-ZHD has an RMS of 3.4 mm. For the Zenith Wet Delay (ZWD) component, the best estimates are derived using ERA5 Precipitable Water Vapour (PWV). These include the ZWD derived by the LRM having an average RMS of 20.9 mm and Bevis equation having RMS of 21.1 mm and 21.0 mm for global and local weighted mean temperatures, respectively. The evaluation of GPT3-ZWD estimates gives RMS of 45.8 mm. This study has provided a valuable insight into the application of ERA5 data for ZTD estimation. In line with the findings of the study, the ERA5 atmospheric variables are recommended for improving the accuracy in ZTD estimation, required for GNSS positioning.

Sequential Generation of Multi-GNSS Multi-Frequency PPP-RTK Products and Their Performance Using the EUREF Permanent GNSS Network

In the classic Precise Point Positioning (PPP) approach, observations of Global Navigation Satellite Systems (GNSS) are processed at the network level to generate satellite clocks and positions. This information can be used to enable accurate point positioning for a single GNSS receiver. In the PPP Real-Time Kinematic (PPP-RTK) approach, satellite phase biases are considered as well, enabling ambiguity resolution at the network and user levels. In this research, 30 s multi-frequency raw GPS, Galileo, and BDS-2/3 observations are processed at the network and user levels in a sequential Kalman filter. PPP-RTK enabling products are generated for up to five frequencies, and ambiguity resolution is performed at the network and user levels using a flexible ambiguity reparameterization approach, comparable to wide- and narrow-laning, which has shown to yield a significantly improved single epoch coordinate solution when multi-frequency observations are available. Different assumptions regarding the time stability of receiver and satellite phase biases have been made and compared. The availability of a precise user coordinate solution when multi-frequency and dual-frequency observations are processed is assessed and compared. A precise ambiguity-fixed solution is available in three epochs or fewer in 77% of all cases with an average of 24 visible satellites for static and kinematic receivers when multi-frequency observations are processed. When only dual-frequency observations are considered, a fixed solution is available in seven epochs or fewer in 71% of all cases. The fastest fixed solution was found in two epochs with multi-frequency observations and in six epochs with dual-frequency observations. Estimating a reference phase clock did not lead to an improvement in the coordinate solution. The findings indicate that a fixed solution can potentially be found faster than often suggested, with potential for further improvement when more satellites or regional atmospheric corrections are considered.

Elucidating the magma plumbing system of Ol Doinyo Lengai (Natron Rift, Tanzania) Using satellite geodesy and numerical modeling

Ol Doinyo Lengai, located in the southern Eastern Branch of the East African Rift had several eruptive episodes with ash falls and lava flows (VEI 3) that caused damage to the nearby communities between 2007 and 2010. The volcano is remote and access is difficult. Although this volcano has been studied for decades, its plumbing system is still poorly understood, in part, because of the lack of precise observations of surface deformation during periods of quiet and unrest. This study investigates the volcanic plumbing system of Ol Doinyo Lengai and its surroundings using data from the network of permanent Global Navigation Satellite System (GNSS) sites monitoring the volcano (the TZVOLCANO network) around the flanks of the volcano and Interferometric Synthetic Aperture Radar (InSAR) observations. We constrain surface motions using 6 GNSS sites distributed around Ol Doinyo Lengai, operating between 2016 and 2021, and InSAR data covering nearly the same time period. Because of the complex local tectonics, the interpretation of the deformation pattern is not straightforward. We first invert the GNSS deformation and InSAR observations independently to infer potential deformation sources. Then we perform a joint inversion of both GNSS and InSAR datasets to verify our findings. We compare the results from the joint inversion with the results from inverting each dataset independently. The GNSS, InSAR, and joint inversion results point to a deflating source, located east of Ol Doinyo Lengai and southwest of the dormant volcano Gelai at a depth of 3.49 ± 0.03 km (GNSS inversion), 5.2 ± 1.2 km (InSAR inversion) and 3.49 ± 0.06 km (joint inversion) relative to the summit (vent) and with a volume change ∆V of −0.04 ± 0.05 × 106 m3 (GNSS inversion), −0.39 ± 0.29 × 106 m3 (InSAR inversion), and − 0.04 ± 0.01 × 106 m3 (joint inversion). Although this is non-unique modeling of geodetic datasets with small signals, the inversion results suggest that Ol Doinyo Lengai could be fed by an offset multi-reservoir system that includes a shallow magma reservoir (<5 km) east of Ol Doinyo Lengai, possibly connected to a deeper magma reservoir.

Integrated Analysis of Lithosphere-Atmosphere-Ionospheric Coupling Associated with the 2021 Mw 7.2 Haiti Earthquake

The search for Earthquake (EQ) precursors in the ionosphere and atmosphere from satellite data has provided significant information about the upcoming main shock. This study presents the abnormal atmospheric and ionospheric perturbations associated with the Mw 7.2 Haiti EQ on 14 August 2021 at geographical coordinates (18° N, 73° W) and shallow hypocentral depth of 10 km from the data of permanent Global Navigation Satellite System (GNSS) stations near the epicenter, followed by Swarm satellites data. The total vertical electron (VTEC) anomalies occur within a 5-day window before the main shock in the analysis of nearby operation stations, followed by Swarm (A and C satellites) ionospheric anomalies in the same 5-day window before the main shock. Moreover, the geomagnetic activities are completely quiet within 10 days before and 10 days after the main shock. Similarly, the atmospheric parameters endorse the EQ anomalies within 5 days before the main shock day. The evolution of gases from the lithosphere at the epicentral region possessed significant atmospheric and ionospheric perturbations within the EQ preparation period of 5-day before the main shock under the hypothesis of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC).

Monitoring nonlinear and fast deformation caused by underground mining exploitation using multi-temporal Sentinel-1 radar interferometry and corner reflectors: application, validation and processing obstacles

ABSTRACT In this study, Differential Interferometric Synthetic Aperture Radar Interferometry (DInSAR) of artificial Corner Reflectors (CRs) were validated in the area of fast and nonlinear deformation gradient caused by active coal longwall exploitation. Three Sentinel-1 datasets were processed using conventional DInSAR, Persistent Scatterer Interferometry (PSI), and Small BAseline Subset methods implemented in ENVI SARscape™. For evaluation, leveling and Global Navigation Satellite System (GNSS) measurements were used. Considering the challenge of snow cover, the removal of all winter images was not a successful strategy due to the long temporal baseline and strong movement, which cause phase unwrapping problems and underestimate the real deformation. The results indicate that only conventional DInSAR and SBAS with low network redundancy allow us to capture maximal deformation gradient and the root mean square error calculated between the CRs and the ground truth is on the level of 2–3 cm for the vertical and easting deformation component, respectively. For the small deformation gradient represented by the permanent GNSS station (4 cm/year), all SBAS techniques appeared to be more accurate than DInSAR, which corresponds to higher redundancy and better removal of the atmospheric signal. In contrast, DInSAR results allowed to capture information about two subsidence basins, which was not possible with SBAS and PSI approaches.