Geodetic Network Research Articles

Thirty years of ground deformation monitoring at Stromboli volcano

Since 1992, INGV has collected tilt, GNSS (Global Navigation Satellite System) and strainmeter data, for the monitoring of effusive and explosive activity of Stromboli volcano. In this timespan, ground deformations related to eruptive activity, paroxystic explosions, cycles of inflation/deflation and many other phenomena of volcanological and geophysical interest have occurred. The dataset from the permanent geodetic networks spans the period 1992/2022 with a variable sampling rate, depending on the individual instrument: from the daily 3D coordinates of GNSS stations to the 1 Hz data of the strainmeter. The time series of GNSS, tilt and strainmeters data cover the entire spectrum of the volcanic and tectonic events observed at Stromboli. A GNSS-derived velocity field is also provided.

Ground-based InSAR and GNSS integration for enhanced dam monitoring

Abstract The monitoring of dams is essential to ensure their safe operation for the production of renewable energy. Common tools to monitor dams are permanently installed plumblines and surveying by means of total station and leveling within a geodetic network. The main drawback of these methods is their limited spatial and temporal resolution. Recent studies have shown promising results using Ground-Based InSAR for geodetic dam monitoring. The fast acquisition speed combined with the surface monitoring capabilities enable to monitor several hundreds to thousands of points on the dam every day or several times a day. However, GB-SAR is a relative phase-measurement technique, and any interruption in the data acquisition leads to difficulties to unwrap differential phase observations and join the disjunct time series. The combination with other absolute measurement tools is promising to create an absolute deformation map of the dam. GNSS is a very efficient and reliable method providing point-wise absolute displacement time series and mm-accuracy. This paper proposes a combination of GNSS and GB-SAR observations to enhance the consistency of the surface-based dam displacement maps obtained by solely GB-SAR measurements. A method to detect unwrapping errors over long time series is proposed. The corrected GB-SAR time displacement maps are compared to a numerical model and confirm the correctness of the applied corrections.

Enhanced geoid modelling in local geodetic networks: Comparative analysis of Least Squares Collocation techniques

The geoid is an equipotential surface of the Earth’s gravity field that closely approximates mean sea level in a least-squares sense. Meanwhile, this study aims to enhance local geoid modeling by comparing the Stationary (SLSC) and Non-Stationary Least Squares Collocation (NSLSC) techniques in Akure South and Gombe, Nigeria. Performance evaluation of the techniques, including comparison of SLSC and NSLSC approaches using three (Gaussian, Exponential, and Matern) covariance models and statistical (MANOVA) analysis, was carried out. In the Akure study area, Matern covariance model, though requiring longer processing time, has proved to be the best-fit (optimum) model for the application of SLSC and NSLSC techniques with standard deviations of 1.711825 m and 1.711782 m respectively. Also, using the GGM dataset for both approaches, the standard deviations for both approaches yielded 1.538476 m and 1.538454 m respectively. Furthermore, using the DEM dataset for both approaches, the standard deviations for both approaches yielded 0.943200 m and 0.943198 m respectively. However, in the Gombe study area, using terrestrial datasets, the Gaussian function proved to be the best-fit (optimum) model yielding the standard deviations of 0.352219 m and 0.352564 m for SLSC and NSLSC techniques, respectively. The results obtained from the GGM datasets yielded standard deviations of 0.340943 m and 0.338443 m for the SLSC and NSLSC techniques, respectively, while the DEM datasets produced standard deviations of 0.352285 m and 0.352496 m for the two techniques, respectively. The findings suggest that NSLSC is better suited for geoid determination in mountainous terrains like Akure South due to its flexibility, while SLSC is computationally more efficient for gently rolling terrains such as Gombe.

Utilizing Artificial Neural Networks for 2D Coordinate Transformation: A Case Study on the Reference System of Iraq

The study seeks to assess the efficacy of utilizing a Back Propagation Artificial Neural Network (BPANN) as an alternative to conventional methodologies for 2D coordinate transformation. Converting the previously used reference system in Iraq to the global system is one of the main requirements that play a main role in various applications requiring the standardization of geographic referencing for different data, including geospatial applications, remote sensing, image processing, and more. This necessitates researching and finding the most suitable methods to ensure high accuracy in the results. The Karbala 1979 (Clark 1880) of the Iraqi national geodetic network and the Iraqi Geospatial Reference System (IGRS) were currently used as geodetic reference frames in Iraq. In the context of transitioning between the local system (Karbala 1979) and the global system, specifically IGRS (ITRF2000 at epoch 1997.0), a crucial procedure involves the conversion of two-dimensional (2D) coordinate data. This conversion employed the BPANN method and conventional techniques such as affine and polynomial. The outcomes derived from the BPANN methodology are juxtaposed against those from the affine and polynomial methodologies. The findings reveal that the effective implementation of each approach within this study is contingent upon the spatial arrangement of the control points leveraged to develop the transformation model. Additionally, the root mean square error (RMSE) of BPANN ranging from 3 to 5 cm closely aligns with the outcomes achieved through affine and polynomial methods.

Fast and Slow Subduction Earthquakes in Latin America

Fast and Slow Subduction Earthquakes in Latin America

Design of Geodetic Monitoring Networks by Minimal Detectable Displacement Evaluation under Confidence and Sensitivity Analysis

Design of Geodetic Monitoring Networks by Minimal Detectable Displacement Evaluation under Confidence and Sensitivity Analysis

Comparison between a Two-Wavelength Absolute Distance Meter and a GNSS-Based Distance Meter at CERN Geodetic Network

Comparison between a Two-Wavelength Absolute Distance Meter and a GNSS-Based Distance Meter at CERN Geodetic Network

Оценка чувствительности к вертикальным перемещениям сети геодезического мониторинга при использовании малобюджетной навигационной аппаратуры потребителя ГНСС

The authors present a study of a geodetic monitoring-ringing observation system based on lowcost phased-array GNSS hardware, the open-source MonCenterLib software and the proprietary MonCenter GNSS Reveiver. The subject of the research was to evaluate the sensitivity of the mentioned system consisting of multiple stations to vertical impulse motions. As a result of the study it was found out that the developed device is sensitive to impulse vertical displacements of 10 mm and higher. At the same time, its efficiency in determining the motion according to the F1 measure is estimated at 67 %. The models of point movements obtained by processing the measurements in the “static” mode and analyzing the movements of the stations in the geodetic network are able to determine the displacements more accurately, compared to the models built based on processing GNSS measurements in the kinematic mode. Thus, the geodetic network based on the said GNSS receivers and open-source software, in general, allows increasing the observability of geodetic monitoring systems

Direct Position Estimation (DPE): A Potential Application in Geodetic Networks

Direct Position Estimation (DPE) is a relatively new technique in the Global Navigation Satellite System (GNSS) that is used to estimate the user’s position, velocity, and time directly from the correlation values of the received GNSS signal with the internal replica signals of the receiver. Unlike the conventional two-step approach, DPE infers the position directly from the sampled data without intermediate steps by joining signal tracking, and the navigation technique directly compares the expected signal reception of multiple potential navigation candidates against the actual received signal. The theoretical results indicate that DPE-based GNSS receivers can achieve more robust localization than conventional two-step receivers. DPE localization algorithms that compute the navigation solution directly in the navigation domain have been proposed, providing ways to address the challenges of conventional two-step receivers at the expense of additional computational load. Despite its high computational load, DPE is a more robust positioning algorithm than conventional two-step receivers in terms of multipath mitigation. The resilience of DPE against multipath and non-line-of-sight can even potentially offer applications in geodetic networks, where robust estimators are traditionally employed to counteract outliers.

Multi-Criteria Optimization of Special-Purpose Geodetic Network Using the Vikor Method

This paper discusses and applies an approach for the design of a geodetic network intended to serve as an adequate basis for analyzing the verticality of buildings in Podgorica, Montenegro. The method analyzed in this paper is the Multi-Criteria Compromise Ranking/Solution (VIKOR), a technique used in multi-criteria optimization for different systems. During the research preparation, six competitive alternatives were established. The ranking of these alternatives was carried out based on four different preference approaches. The primary difference between these approaches lies in the varying weights assigned to certain criteria. Specifically, the weight ratios for individual criteria were adjusted. For the analysis of the building's verticality, a geodetic network design, selected as the optimal compromise solution, was utilized. The network measurements were conducted using appropriate geodetic instrument and supporting equipment. After completing the measurements in the optimized network, the network was adjusted, and the accuracy of the positional coordinates was assessed.

Assessing the reliability of a surveying and geodetic network based on a Markov model

Purpose. To build a graph of states and transitions of the surveying-geodetic network (SGN), which includes 16 points. To study the functioning of constructed discrete-continuous stochastic Markov models of the surveying-geodetic network with full and current recovery. To perform a numerical calculation of reliability, safety and efficiency indicators: readiness ratio, limit probability states, mean time to failure, mean time between failures. Methodology. A model of SGN functioning is built in the form of a graph of states and transitions with current and full recovery. Based on the model in the Mathcad software, the availability factor, mean time to failure, mean time between failures are calculated. The following graphs are built: readiness functions, probabilities of operation until the first failure, and frequency of getting into an emergency situation. Findings. Constructed discrete-continuous stochastic Markov reliability models of the boundary probability states, mean time between failures, mean time to the first failure have been analyzed. The probability of fault-free operation is presented graphically in the form of a transition graph, which describes the logic of the operation of the SGN. Based on the graph of states and transitions (graphical model) according to the Kolmogorov-Chapman algorithm, an analytical model of the reliability behavior of the surveying-geodetic network was built. A system of linear Kolmogorov-Chapman differential equations was compiled and solved. The distribution of probabilities of being in each state of the surveying-geodetic network has been obtained. Originality. For the first time in surveying practice, a reasonable choice of a discrete-continuous stochastic model of the functioning of a surveying-geodetic network based on the application of the state space method has been made. This model most fully describes the process of functioning (behavior) of the dynamic system. Dependencies between reliability indicators and safety indicators are established. It is recommended to use a model with ongoing network recovery, which allows you to maintain a given level of reliability through timely maintenance (recovery). Practical value. The most expedient time for restoration of geodetic points with certain failure intensity parameters has been determined. It has been done in order to maintain the SGN in an operational state with a given level of reliability. Current network recovery makes it possible to maintain reliability at the desired level. In the case of complete restoration of the SGN, the readiness factor will be lower, but such a system will be significantly cheaper.

Geodetic Support for the Use of Natural Resources of Chernivtsi Region Using GIS

Maps and plans are necessary to obtain accurate spatial information about the location of any geo-objects. High-quality and accurate creation of cartographic materials will improve the assessment of natural resources, cadastral work, etc. to solve the problem, cadastral maps and plans of a given scale are necessary. Their creation without violating regulatory documents requires certain State Geodetic Network (SGN) points. The purpose of the study is to analyse the spatial location of SGN points on the territory of the Chernivtsi region in Ukraine and to assess geodetic support for the use of natural resources using geographic information systems (GIS). We used QGIS version 3.28, to create maps and models based on the thematic layers, and evaluated the existing geodetic support in the section of the newly created administrative and territorial units of the region. An assessment of the spatial placement of SGN points for the territory of the Chernivtsi region by the administrative-territorial division was carried out. We identified 198 geodetic points of different classes. The boundaries of Chernivtsi district had the largest number of geodetic points (109 units, which is 55% of the total region). This was followed by Dnistrovsky District (54 points - 27% of the region), and Vyzhnytsky District (35 objects - 18% of the region).

Classifying continuous GNSS stations using integrated machine learning

The development of Global Navigation Satellite Systems (GNSS) results in large spatial geodetic networks with a distinct range of accuracy. Thus, classification of the GNSS stations is needed to determine which stations are appropriate for geodetic applications. Additionally, advanced Machine Learning (ML) techniques have been proposed. However, ML algorithms may sometimes be less sensitive due to a lack of samples or anomalies in input data. Therefore, this study introduces an approach in which human-based supervision is integrated into ML processes to improve the ML model’s performance in classifying the continuous GNSS stations. The human factor influences the ML processes through two sampling strategies: “suggest-decide” and “correct-retrain”, where the accuracy of ML models will be improved via human-based corrections. The idea is that the unsupervised ML-based clustering techniques are driven by human-based supervision to create samples for training the supervised ML-based classification models. In this study, we develop a MATLAB app to automate the clustering and labeling processes. Our finding demonstrates that applying these sampling strategies can enhance the accuracy of the ML-based classification models from under 50 % up to ∼99 % after re-training. Also, this study categorizes almost 9000 continuous monitoring stations in the Nevada database, of which 1900 stations in Europe serve as samples for training the ML-based classification models. Furthermore, the methodologies developed in this study can be applied to warning systems, which utilize internal and external human resources to correct errors, address unusual situations, and provide timely feedback for better performance of ML-based forecasts.

Long-distance SLAM scanning of mine tunnel - testing of precision and accuracy of Emesent Hovermap ST-X

This paper presents a detailed analysis of the Emesent Hovermap ST-X LiDAR scanner's precision in long-distance scanning of underground environments, specifically within the Josef mine's main gallery. The experiment aimed to evaluate the simultaneous localization and mapping (SLAM) capabilities of the Hovermap ST-X over a 750-meter straight tunnel section where conventional geodetic reference points are unavailable. To validate the scanner's accuracy, reference measurements were obtained using a Leica ScanStation P40 terrestrial laser scanner and a Leica MS60 total station, establishing a millimeter-level geodetic network with spherical control targets. The SLAM-based Hovermap ST-X scanner captured point clouds in both single (1P) and double (2P) pass modes, which were then analyzed for systematic errors in transverse (X), longitudinal (Y), and vertical (Z) directions using RMSE metrics. The study finds that while the Hovermap ST-X provides high-precision point clouds within shorter sections, cumulative errors arise over the entire 750-meter distance, particularly in the longitudinal axis, leading to slight compressions that necessitate scale corrections. In the transverse direction, the deviations reach up to tens of centimetres. The study also highlights that double-pass scans effectively reduce transverse deviation errors compared to single-pass measurements, yet significant systematic errors persist in both vertical and horizontal planes. These findings suggest that while SLAM scanning offers rapid data acquisition and adequate accuracy for various applications, its precision for geodetic surveys over extended distances could be improved by integrating scaling transformations and optimized pathing strategies. This work demonstrates the SLAM scanner's utility in challenging underground conditions and provides a framework for future precision assessments in mine surveying. The results suggest practical considerations for enhancing SLAM-based mapping accuracy in geodetic applications, emphasizing the need for periodic control points to minimize cumulative drift errors.

Precision and accuracy determination of horizontal geodetic networks using least squares technique

The determination of precision and accuracy in horizontal geodetic networks using a least squares adjustment is a complex process that has a range of available software applications. However, it is commonly observed that users may not possess a complete understanding of the underlying theories and equations that inform the development of such software. This paper presents a set of step-by-step procedures for determining the precision and accuracy of horizontal geodetic networks using the observation equation method of the least squares technique. In the sample calculation, the a posteriori variance and standard error were computed to obtain the precision and accuracy of the network, respectively. The inverse of the normal matrix was multiplied with the a posteriori variance to obtain the precision of the adjusted parameter. The square root of the precision was evaluated to obtain the accuracy of the adjusted parameter. The enumerated procedures are presented in a sequential order to ensure ease of comprehension for users. Additionally, a numerical example is provided to illustrate the procedures and to enhance understanding of the concepts presented. The computed adjusted network's precision and accuracy are 0.723m 2 and 0.850m respectively. Our objective is to provide users with the necessary tools and knowledge required to confidently perform this task.

Development of a high-resolution ionospheric VTEC model over Nigeria using spherical harmonics with orthogonal transformation solution

Abstract One important ionosphere element that impacts radio signal transmission is the Vertical Total Electron Content (VTEC). Accurate estimation of VTEC is important for diverse applications such as satellite positioning, space weather forecasting, satellite communication. In regions with a sparse network of receivers, especially Nigeria, the spatial and temporal resolutions of the Global Ionospheric Maps (GIM) regularly provided by the International GNSS Service (IGS), Center for Orbit Determination in Europe (CODE), and the International Reference Ionosphere (IRI) are limited. This limits their potential to uncover local ionospheric phenomena in such areas. To address this limitation, we have developed a VTEC model for estimating high temporal-resolution VTEC and Differential Code Bias (DCB) over Nigeria using spherical harmonic expansions with an orthogonal transformation solution. Our novel method makes use of GNSS measurements from the Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) to precisely estimate VTEC and DCB. GNSS datasets in Receiver Independent EXchange (RINEX), satellite orbit (SP3) and Ionospheric Exchange (IONEX) formats from 2011 across 9 GNSS receivers in the Nigerian Geodetic Network sampled at 30-second intervals were used for this study. For this investigation, code pseudo-range observations were also smoothed using carrier phase observations. To assure data quality, we also carried out several preprocessing procedures utilizing the Melbourne-Wubbena linear and geometry-free linear combinations using an internal ITB-GNSSTEC FORTRAN application based on batch processing and least squares approaches. To validate our model, we compared the estimates with the IGS, CODE, and IRI-2020 models. Results demonstrated strong agreement with the other models with a standard deviation between 2.80 and 6.50 TECU and a correlation coefficient of not less than 0.92 at the evaluation stations. Notably, the new model aligned more closely with CODE and IGS than the IRI model. Also, the new model enabled the detection of local ionospheric VTEC post-sunset enhancement missed by GIM models. Our model also showed a strong positive correlation with the other models for quiet and disturbed days of geomagnetic activity. In Conclusively, this research has developed a high-resolution VTEC method for areas with sparse distribution of GNSS receivers, achieving a temporal resolution of 10 minutes. The ionospheric modeling in areas like Nigeria with sparse GNSS networks has greatly benefited from this research. The approach improves the precision of GNSS-based applications, such as location and navigation, by precisely calculating VTEC and DCBs. It also addresses the issue of sparse observational data in equatorial regions, offering insightful information for atmospheric and geodetic research.

Accurate Underwater Acoustic Positioning Considering Geometric Configuration

The accuracy of underwater acoustic positioning is significantly influenced by observing geometry configuration and sound speed variation. The geometric configuration includes the sailing track of the surface vessel as well as the geometry of the seafloor array, all of which are relevant to data processing and error analysis. In this paper, we study how to reduce the influence of sound speed error on underwater positioning based on geometric configuration. For the single point positioning model, an integrated sound speed compensation approach considering the vessel track is proposed to improve positioning accuracy. For the seafloor geodetic network, a network positioning model with virtual seafloor baseline constraints is proposed to improve positioning accuracy. Acoustic positioning experiments conducted in the South China Sea and Japanese open data verify the effectiveness of presented methods. The results show that there is significant diurnal sound speed variation in the South China Sea. The discrepancies between positioning results of different data sets are reduced by sound speed compensation, and the standard deviations of horizontal components are better than 10 cm. The positioning accuracy of repeated surveys in Japanese geodetic network is improved with virtual baseline constraints. Compared with solutions with no virtual baseline constraints, the standard deviation of array center coordinate series is reduced by 8.7%, 21.3%, and 57.1% for the east, north, and up components when dealing with long-term GNSS-A data.

RESEARCH OF THE RELIABILITY OF THE GEODETIC NETWORK IN PROVIDING GEODETIC SUPPORT OF CONSTRUCTION

The safety and reliability of buildings and structures as a complex technical system depends not only on the correct consideration of data on the structural features of the building, but also on the behavior of the soil base and on the geodetic support of the construction. Geodetic works are an integral part of the technological process of construction production and belong to the main types of work. Ensuring reliable and safe, long-term operation of buildings and structures of residential, civil, industrial and agricultural purpose, located both in ordinary and in difficult engineering-geological, earthquake-hazardous, mining-geological conditions is an urgent scientific task in our time. Buildings located on artificial territories, on subsiding soils, landslide-prone slopes or in conditions of dense urban development need to determine the development of deformation processes based on the results of periodic geomonitoring at the stage of their operation. The purpose of the work is to create a Markov discrete-continuous stochastic model of the operation of the local geodetic network (GN) to provide geodetic support for construction and perform numerical calculations of the reliability and safety of the GN depending on the features of its restoration. Analyze regulatory and legal documents on the reliability and safety of construction objects. Perform an analysis of methods for assessing the reliability and safety of technical systems. Perform a numerical calculation of reliability, safety and efficiency indicators: availability ratio, limit probability states, mean time between failures, average duration of fault-free operation of the geodetic network (GN). Methodology. Analysis of regulatory documents on the reliability and safety of construction objects. Review of methods for assessing the reliability and safety of technical systems. Application of the state space method, construction of graphs of states and transitions of a renewable geodesic network. Construction of graphs of the readiness function, the probability of operation before the first failure and the frequency of getting into an emergency situation in the Mathcad software tool. Scientific novelty. The state space method allows simulating the behavior of the designed GN in order to identify the time spent in various states of the technical system depending on the intensity of failures of geodetic points and the intensity of their recovery. On the graph of states and transitions, in contrast to the “fault tree” method, it is possible to simultaneously see all possible situations separated by masks of emergency situations. Practical value. Due to the use of stable geodetic points selected based on the results of the performed reliability assessment, there is an opportunity to improve the quality of geodetic construction support. The most expedient scheme of GN restoration has been substantiated. The results of the analysis of the functioning models of the designed GN were used and the calculated values of: availability coefficient, frequency of GN failures and the probability of operation before the first failure. Results. A graphic model of the reliability behavior of GM in the form of a graph of states and transitions has been built. Geodetic network includes 8 points. A system of Kolmogorov-Chapman linear differential equations was compiled and solved. The distribution of probabilities of being in each state of GN has been obtained. The reasonable periodicity of GN restoration depending on the intensity of failures has been substantiated. It has been proven that periodic restoration of geodetic points allows maintaining a given level of GM reliability. This increases the accuracy of geodetic monitoring of construction and ensures functional safety.

Unexpected far-field deformation of the 2023 Kahramanmaraş earthquakes revealed by space geodesy.

The spatiotemporal pattern of surface displacements from large earthquakes provides crucial insights about the deformation of Earth's crust at various scales and the interactions among tectonic plates. However, the lack of extensive and large-scale geodetic networks near such seismic events hinders our thorough understanding of the large-scale crustal deformation resulting from earthquakes. Using Türkiye's extensive and continuous global navigation satellite system (GNSS) network during the moment magnitude 7.8 and 7.6 Kahramanmaraş earthquakes on 6 February 2023, we show that large earthquakes can induce far-field crustal deformations (>700 kilometers), exceeding current predictions from elastic dislocation models. They can lead to the mobilization of tectonic plates and the triggering of far-field earthquakes, which carries profound implications for seismic hazard assessments and necessitates a new perspective on crustal deformation and earthquake mechanics.

Afterslip and Creep in the Rate‐Dependent Framework: Joint Inversion of Borehole Strain and GNSS Displacements for the Mw 7.1 Ridgecrest Earthquake

AbstractThe elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub‐nanostrain precision and sub‐second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best‐fitting models adhere to mechanical rate‐and‐state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.