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Journal of Applied Geodesy

Editors-in-Chief: Hans-Berndt Neuner and Chris Rizos

Language: English

First published: March 22, 2007

Publication Frequency: 4 issues per year

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Objective
The Journal of Applied Geodesy (JAG) is a forum for peer-reviewed research articles in the area of application of geodesy to engineering and other natural sciences. It publishes innovative contributions on sensor developments, multi-sensor systems and sensor data fusion focusing on the capture of georeferenced data. Hence topics related to navigation and mobile mapping will also be covered by JAG. The scope includes optical and microwave 3-D measurement techniques and other sensors for geotechnical measurements. Furthermore, applied geodesy articles from all areas of satellite-based geodetic networks, deformation measurements, deformation analysis, modelling of local geodynamic processes and the development of intelligent alert systems, measurement techniques for large construction sites and mechanical engineering will be presented. With increased use of the tools of Artificial Intelligence for sensor control, sensor fusion and data analysis, manuscripts on these topics with a strong emphasis on applied geodesy will also be published.

Topics

Navigation and mobile mapping
Optical and microwave 3-D measurement techniques
Satellite-based geodetic networks
Deformation measurements
Deformation analysis
Modelling of local geodynamic processes
Intelligent alert systems
Measurement techniques for large construction sites
Mechanical engineering
Sensor control
Sensor fusion

Article formats
Research articles

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Novel fields of application of geodesy to engineering and other natural sciences
Rapid developments that have influenced both sensors / instrumentation and methodology
Cutting-edge surveying and mapping techniques, processing algorithms and analytical tools
Rigorous peer-review

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As of 2026, all De Gruyter journal subscriptions include access to every issue, from Volume 1, Issue 1 through to today, meaning subscribers can access even more research at no additional cost.

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AI-driven versus traditional ionospheric modeling approaches for GNSS positioning in Egypt

November 4, 2025

Ahmed Abdelmaaboud, Tamer Fathallah, Ahmed Ragheb, Ahmed Gomaa, Tarek Hassan

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The ionosphere significantly impacts Global Navigation Satellite Systems (GNSS) positioning accuracy, particularly in regions with pronounced ionospheric irregularities and high solar activity, such as Egypt. These regions face more challenges in ionospheric modeling compared to the higher-latitude areas. This study provides a detailed assessment of different approaches to Total Electron Content (TEC) estimation in Egypt and their impact on GNSS positioning accuracy using single-frequency receivers. The approaches include the traditional Klobuchar model, Global Ionospheric Maps (GIMs), and the Artificial Neural Network (ANNTEC) model. This ANN model was developed to predict the TEC over Egypt using 10 years of GNSS observations and ionospheric data. The assessment process is performed in two scenarios: static and kinematic positioning. The positioning accuracy employing each approach is evaluated relative to reference coordinates tied to the International Terrestrial Reference Frame 2020 (ITRF-2020) through the nearest International GNSS Service (IGS) stations. The results indicate that the ANNTEC model outperforms the other approaches in both kinematic and static scenarios. In the static mode, the Root Mean Square Error (RMSE) value of the horizontal positions can be improved by 46.6 % and 24.5 % compared to using the Klobuchar model and the GIMs, respectively. In addition, in the kinematic mode, the RMSE value was reduced by 54.7 % and 25.8 % compared to using the Klobuchar model and the GIMs, respectively. These results demonstrate the potential of employing the ANNTEC model to enhance single-frequency GNSS positioning accuracy in Egypt.
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Construction of models of temperature dependent variations in the position of EPN/IGS stations located on buildings and other structures. Case Wettzell, Germany

November 6, 2025

Nikolay A. Bovshin

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In this work, a study of a specific network of five permanently operating GNSS stations was carried out. It based on the previously obtained results of studies of the effect of thermal compression-expansion of buildings as foundations of geodetic stations, conditions for the manifestation of this effect in variations of geodetic stations positions and properties of these variations. The study examined seasonal variations in relative positions of stations in this network. Relative GPS positioning on very short baselines that has very high sensitivity was used for the study. Based on the analysis of the properties of the time series obtained for all possible baselines in this network, it is shown that the seasonal variations observed in these time series reflect the influence of changes in ambient temperature. From point of view of the problem being solved, this network has an important property: all stations are installed along perimeter of the same building – a concrete survey tower. Using this property, models of variations of these stations positions under influence of this effect were constructed without the use of external reference stations. The constructed high-precision models are suitable for practical use – predicting actual positions of these stations in arbitrary observation epochs.
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Quality analysis of reference GPS stations in Ecuador

June 30, 2025

Richard Serrano-Agila, Rosendo Romero-Andrade, Daniel Hernández-Andrade, Wilman Gonzalo Merino-Vivianco

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Since 2008, Ecuador has established a Permanent Geodetic Network (REGME), to support geodetic research in the country. The REGME network plays a critical role in monitoring tectonic activity and crustal deformation throughout Ecuador. However, no comprehensive quality analysis has been conducted for REGME stations. The network has provided data from 70 continuous GPS stations across Ecuador, covering a period of 16 years. Shell scripts were developed on UNIX to manage and process REGME raw data. The data were converted from HATANAKA to RINEX format using CRX2RNX, and the sampling rate was standardized to 30 s using TEQC software. Only GPS signals were selected due to variations in the stations’ capabilities to track different signals. This study establishes a crucial foundation for future research on crustal deformation and geophysical phenomena in the region, offering valuable insights that will enhance both local and global geodetic efforts.
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Mitigation of chirp interference in NavIC signals using NWPR and SNV estimator

September 23, 2025

Divyasree Uddandapu, Surya Narayana Murthy Tummala

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Radio Frequency Interference (RFI) makes it very difficult for Global Navigation Satellite Systems (GNSS) signals to work properly and remains safe. This makes positioning less accurate and reliable. This study looks at the current methods for finding and reducing RFI, with a focus on the IRNSS S-band and L5-band, because it covers the whole world. In this, how the chirp interference affects signal tracking by measuring the Carrier-to-Noise Ratio ( C / N 0 ) using in-phase and quadrature-phase correlator outputs under both statistical and estimated settings. The narrowband-wideband power ratio (NWPR) approach boosts effective C / N 0 by 11.37 dB-Hz for the S-band signal and 12.48 dB-Hz for the L5-band signal, and compares it to the statistical C / N 0 value and the Signal to Noise variance estimator C / N 0 .
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Investigation the impact of active fault-induced vertical displacement on land subsidence rates using GNSS CORS data in northern coastal cities of Central Java, Indonesia

August 27, 2025

Muhammad Arif Mumtaz, Cecep Pratama, Leni Sophia Heliani, Dwi Lestari, Krishna Duta Wibisono, Zulviana Rahmadina, Nur Intan Komala Dewi, Nicholas Genta Setiawan Gunawan, Sidik Tri Wibowo

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Land subsidence is commonly observed along the coastal regions of Java Island, particularly in the northern part of Central Java. This phenomenon often contributes to the intensification of coastal flooding. Subsidence rates are influenced by multiple factors, which might also relate to tectonic movements associated with active fault structures. In this study, we investigate the contribution of active fault-induced deformation to land subsidence in northern coastal cities of Central Java. We modeled the surface displacements resulting from active faults using the elastic half-space approach. We analyzed geodetic data from Continuously Operating Reference Stations (CORS) situated along the northern coast, covering the period from 2015 to 2019. The analysis revealed notable land subsidence at Pekalongan and Tegal, with annual rates of −122.54 mm/year and −11.04 mm/year, respectively. Statistical testing of annual displacement rates indicated that fault-induced surface movement was significant only at Semarang City. Conversely, the displacement observed at CORS with pronounced subsidence was not statistically significant. These findings suggest that active fault-related displacements do not play a dominant role in driving land subsidence in the study area. Instead, the magnitude of their influence appears to depend on the proximity of the faults to observation sites and the relative level of earthquake potential of the fault.
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Optimizing GNSS-IR for sea level monitoring: a case study along the Eastern Black Sea coast of Türkiye

January 19, 2026

Cansu Beşel Hatipoğlu

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Determining the optimal parameter conditions based on satellite elevation angle and azimuth ranges allows the examination of the reflection surface at the GNSS site locations. This study aims to assess whether the GNSS site locations along the Trabzon coast in the Eastern Black Sea region of Türkiye meet the optimal parameter conditions for monitoring of sea level changes using GNSS-IR. Additionally, the impact of different topographical features and sea conditions was assessed for parameter selection. For this purpose, an experimental area was selected along the coast, and GNSS receivers were installed at four experimental points (NOK1, NOK2, NOK3, NOK4) with different topographic characteristics. A 3-day measurement campaign was conducted to determine the optimal parameter conditions. Signal-to-noise ratio (SNR) data from these four experimental points were used in the study. Satisfactory results could not be obtained at NOK1 and NOK2. Only the NOK4 could be compared with the nearby tide gauge. A relatively high root mean square error of 20 cm was obtained between the two datasets. The results indicate that the data collected from the experimental points were affected by the optimal parameter conditions. Moreover, the GNSS-IR-derived sea level was influenced by the environmental circumstances in locations with optimum parameters.
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Preliminary investigation on digital signal processing techniques for echo signal analysis in geodetic and wildlife monitoring

December 2, 2025

Sony Devalapally, Sridher Tunguturi, Lakshmanna Kuruva

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In large-scale remote monitoring of animals/mammals, echo signals localization with Internet of Things (IoT) modules has proved significant progress. Accurate information of echo signal extraction is difficult due to the frequent overlapping of signals in field recordings. The Digitization of these echo signals is essential to reconstruct interpretation of accurate signal in various geodetic fields, bird’s/mammal’s vocalization, seismic data collection, and GNSS signal processing. As a preliminary examination, this research examines on digital signal processing operations on four sampling rates namely 16 kHz, 32 kHz, 48 khz, and 96 kHz and their influences on the clarity, noise impact by employing GNU Radio Companion (GRC). It is observed that the lower rates 16 kHz and 32 kHz results in pronounced aliasing effects and the loss of higher-frequency signal components, hindering accurate interpretation. In contrast, the higher sampling rates 48 kHz and 96 kHz preserved signal details and demonstrated stronger resistance to noise. In this study, to measure aliasing and signal reconstruction quality, this study proposed the Fidelity Score (FS), a normalised quality metric that ranges from ‘0 to 10’ i.e. poor fidelity to perfect fidelity, and the Aliasing Severity metric (ASI), which is the ratio of aliased to original signal power. For instance, at 96 kHz, the aliasing severity was 0.5, and the fidelity score reached 9 out of 10, indicating near-perfect reconstruction. Further the work is validated using real-time bird vocalizations, including a 48 kHz recording of the White-throated Laughingthrush and a 15 kHz dominant frequency call of the Common Babbler, confirming its applicability to real-world data. These preliminary findings help in appropriately choosing sampling rates to achieve reliable signal acquisition in geodetic, automatic bird/animal sound separation applications that require high precision and signal clarity.
Open Access
Exploring LSTM neural networks for sea level forecasting based on two-decadal tidal and meteorological data

September 22, 2025

Nestoras Papadopoulos, Vassilis Gikas

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The analysis of long-term sea level signal fluctuations and their systematic forecasting showcase the value and implications not only for oceanographic, climate monitoring and related studies but also, on socio-economic aspects of life. Such changes affect significantly the stability in natural processes functioning as well as the usage of nearshore infrastructures; and therefore, interrelate to human activities in coastal areas. This study contributes to the forecasting of sea level variation employing emerging Deep Learning techniques in the form of Recurrent Neural Networks, particularly Long Short-Term Memory (LSTM). Several combinations of data were tested exhaustively to identify the most suitable setup and examine the accuracy depending on available datasets. Univariate, multivariate and multivariate to univariate LSTMs were formed and hyperparameter tuning took place exhibiting RMSE values around 4–5 cm. Also, the effect of seasonality and trend to LSTM forecast was investigated thoroughly leading to performance improvement after eliminating it from the network. The combination of the above networks introduced the “fill-in and predict” technique leading to RMSE slightly over 1 cm for the multivariate to univariate LSTM network. The forecast results were validated against more than two years of historical data.
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A simplified PPP-RTK atmospheric delay correction model and its positioning performance

December 26, 2025

Siyao Wang, Miaomiao Wang, Rui Tu, Song Jia, Lihong Fan, Xianjian Xiao

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The atmospheric delay corrections including tropospheric delay corrections and ionospheric delay corrections are critical information in positioning solutions of PPP-RTK (Precise Point Positioning-Real-Time Kinematic) rapid positioning service, in order to achieve rapid convergence of fixed ambiguity and high-precision positioning solutions in a short time. With rapid development of GNSS (Global Navigation Satellite Systems), the availability of multi-frequency and multi-GNSS observations has led to a significantly increase of number of atmospheric delay corrections, which will surely put more pressure on data transmission and reception to PPP-RTK service and potentially improve the cost of operational economy of users. Therefore, we propose a simplified method to process the atmospheric delay corrections, which sacrifices a certain degree of mathematical rigorousness in positioning equations, but significantly reduces the number of corrections while ensuring that the degradation in positioning performance remains in a controllable way. The traditionally used slant tropospheric delay corrections are simplified to zenith tropospheric delay corrections, and the usually used pseudo-range slant ionospheric delay corrections are no longer transmitted and are simply calculated as the opposite of phase slant ionospheric delay corrections at the user station. The experiments results show that the number of atmospheric delay corrections reduced about 60 %, and the differences between the atmospheric delay corrections processed by the proposed simplified method and the typically traditional method are acceptable to a certain extent for users located in networks with small/medium scale and under relatively stable atmospheric conditions. Although the employment of atmospheric corrections processed by the proposed method introduces the longer TTFF (Time To First Fix) and the lower success fixing rate of ambiguity, the positioning solutions with the proposed simplified method is still basically adequately to meet the positioning requirement of user stations. The proposed simplified model is beneficial to some users who prefer to put more emphasis on equipment portability and data transmission economy.
Open Access
Sensitivity quantification of spatially averaged displacement estimates in TLS-based geomonitoring

July 31, 2025

Lorenz Schmid, Tomislav Medic, Nicholas Meyer, Andreas Wieser

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Terrestrial Laser Scanning (TLS) is increasingly used in geomonitoring for 3D displacement analysis. However, assessing the sensitivity of the implemented monitoring strategy, which is crucial for correctly interpreting observations and detecting deformations, is challenging due to the impact of complex spatial correlations and other influencing factors. Traditional methods for sensitivity analysis often assume uncorrelated measurements, leading to biased and overestimated sensitivity. This can lead to suboptimal choices of monitoring strategy, false expectations, and errors in displacement detection. This study introduces a new method for quantifying the uncertainty of spatially aggregated (averaged) TLS-based displacement estimates in geomonitoring by empirically locally sampling such aggregated values (ELSA). The method implicitly accounts for the mentioned spatial correlations and their local variations, therefore, providing a more realistic sensitivity quantification. Validation using real-world datasets and simulated displacements demonstrates the method’s ability to provide a realistic uncertainty estimate and, subsequently, a good sensitivity estimate, realized herein by means of the Minimal Detectable Bias (MDB). Finally, we investigated several data preprocessing steps and demonstrated their effectiveness in enhancing both sensitivity and the quality of uncertainty estimates.
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Unificative methodology for determining recent dynamic parameters of tectonic plates based on GNSS data

November 17, 2025

Ihor Savchyn

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This study presents a unificative methodology for determining the latest dynamic parameters of tectonic plates, including moment of inertia, angular momentum, and kinetic energy, using data from continuous GNSS stations combined with information on crustal thickness and density from the CRUST1.0 model. The methodology treats the tectonic plate as a system of discrete volume cells, each with a defined mass and distance to the axis of rotation, which allows for accurate calculation of dynamic parameters. The approach has been tested on 7 large, 7 medium, and 3 microplates using data from 3169 GNSS stations for the period 2002–2021. The methodology provides an uncertainty of parameter estimation of less than 5.5 %, offering a new tool for detailed assessment of lithospheric dynamics and understanding the distribution of rotational energy in the Earth’s plates.
Open Access
Using robotic total station networks for 360° prism deviation reduction

November 6, 2025

Gereon Tombrink, Lasse Klingbeil, Heiner Kuhlmann

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The accurate generation of reference trajectories is essential for the empirical evaluation of navigation sensors. Systematic deviations of the reference trajectory should be avoided as much as possible, as they distort the result of the trajectory comparison. While robotic total stations (RTS) already have several advantages over commonly used GNSS/IMU reference trajectories, they are still not free of systematic deviations due to the use of 360° prisms. Depending on the angle of incidence of the RTS signal into the prism, these cause systematic deviations in the position in the range of several millimeters. In this paper, we therefore present a measurement concept that can be used to reduce these deviations. We use a network of multiple RTS that track the same 360° prism. Due to the different RTS-target geometry of each RTS, the resulting deviations also differ and can be reduced when averaged. We support this claim with experiments which show a reduction of horizontal position deviations of up to 38.5 % in a static measurement and up to 22.4 % in a kinematic measurement. However, the vertical deviations cannot be reduced by combining multiple RTS with our measurement setup. We publish the code for controlling and managing RTS networks here: https://github.com/Engineering-Geodesy-Bonn/rts-network.
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Hybrid algorithm for identification of stable reference points in a monitoring network

November 4, 2025

Waldemar Odziemczyk

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The results of deformation analysis are crucial for the safety of engineering infrastructure and people’s lives. A key element of this analysis is the identification of stable points of the monitoring network, which will constitute the reference for further calculated displacements. This paper proposes a new method of stability analysis aimed at identifying stable groups of reference points in a displacement monitoring network. It is based on coordinate transformation and involves searching for the optimal set of transformation parameters identified with the optimal point in the transformation parameters space. A hybrid algorithm, which combines two optimization algorithms – Hooke–Jeeves and Simulated Annealing – is used to search for the solution. Two variants of the objective function were tested as the elements of the algorithm. Multiple solutions (groups of congruent reference points) can be detected in case they exist. The simulated 2D network with two congruent point groups was used as an example to illustrate the performance of the proposed algorithm. The proposed hybrid algorithm appeared to overperform the individual Hooke–Jeeves and Simulated Annealing algorithms.
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Geopotential-number estimation based on regional and global geoid models towards vertical datum modernization in India

November 5, 2025

Ana Isela Vidal-Vega, Manuel E. Trejo-Soto, Karan Nayak, Manuel Trejo-Echeagaray, Aníbal I. Arana Medina, Tiojari D. Guzman Galindo

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This study focuses on the analysis of the dataset currently available over the Indian subcontinent for the calculation of geopotential numbers and orthometric heights, mainly the performance of regional and global geoid models across diverse topographic conditions. Using Global Navigation Satellite System (GNSS) observations from 17 Asia Pacific Regional Geodetic Project (APRGP) stations distributed across plains, plateaus, coastal areas, and complex mountainous regions, we compared six geoid models: three global (EIGEN-6C4, xGM2019e_2159, SGG-UGM-2) and three regionals (IndGG-SH2021, IndGG-CUT2021, and IndGG-LSMSA2021). Interpolated gravity values, geoidal heights, and geodetic coordinates were utilized to derive geopotential numbers, which were further analyzed to estimate orthometric heights and quantify the discrepancies obtained using currently available data. Our results indicate that recent global geoid models, particularly XGM2019e_2159 and SGG-UGM-2, have improved and have consistency with respect to regional geoid models, mainly with IndGG-SH2021 in terms of accuracy and reliability. Stations located in moderate terrain zones such as Bangalore, Delhi, and Hyderabad showed minimal variations (<±15 cm) in orthometric heights, However, significant discrepancies were observed in mountainous regions like Kashmir, where orthometric height differences exceeded ±25 cm, especially with the IndGG-CUT2021 model. Based on these findings, it is strongly recommended to use gravimetric geoid models derived from satellite missions to analyze the strength of regional models that allow to observation of the trend of the results in each model to verify its consistency. Furthermore, obtain absolute gravity data for India’s vertical datum modernization.
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Investigations on different spectral techniques to improve the gravimetric geoid model for the central part of Java, Indonesia, using terrestrial, airborne, and altimetric-based gravity observations

September 18, 2025

Brian Bramanto, Rahayu Lestari, Arisauna M. Pahlevi, Kosasih Prijatna, Agustina N. Syafarianty, Dina A. Sarsito, Vera Sadarviana, Widy Putra, Bagas Triarahmadhana, Teguh P. Sidiq, Safirotul Huda, Febriananda Ladivanov, Muhammad S. Fathulhuda, Irwan Gumilar, Dudy D. Wijaya

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In the modern era, deriving accurate geoid models is crucial for various engineering and geoscience applications. The geoid facilitates the transformation of ellipsoidal heights from Global Navigation Satellite System (GNSS) measurements to orthometric heights and aids in determining geostrophic ocean surface currents. This study assesses different spectral methods, including two-dimensional Fast Fourier Transform (FFT), multiband spherical FFT, and one-dimensional FFT, for evaluating the Stokes’ function in gedsaata and Stokes’ kernel. The geoid modeling process is divided into three major stages: gravity data assessment, regularization of scattered gravity datasets onto the topographical surface, and geoid computation under the Remove-Compute-Restore (RCR) mode with Residual Terrain Model (RTM) reduction. Results indicate that the multiband spherical FFT method outperforms others, leading to the adoption of the Institut Teknologi Bandung-Central Java 2024 (ITBCJ24) geoid model, which achieves a root mean squared error (RMSE) of 0.068 m relative to GNSS-leveling observations and a relative accuracy of 4.409 ppm. The study also highlights the significance of gravity data coverage and distribution by comparing geoid models derived from terrestrial, airborne, and altimetric-derived gravity observations against the model relying solely on terrestrial gravity observations. Although the latter performs similarly at validation points, prominent discrepancies in geoidal height outside the validation region highlight the importance of uniform and dense gravity data coverage. Finally, the ITBCJ24 geoid model is compared to existing geoid models in Indonesia, showcasing its superiority with RMSE values of 0.117 m and 0.166 m for Indonesia’s regional geoid model of INAGEOID2020 and Earth Geopotential Model 2008 (EGM2008) model, respectively.
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Multi-scale accuracy evaluation and adaptability analysis of different atmospheric weighted mean temperature models in China

January 7, 2026

Bingbing Zhang, Junkuan Zhu, Yi Shen

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The atmospheric weighted mean temperature (Tm) plays a critical role in deriving precipitable water vapor (PWV) from zenith wet delay (ZWD) in GNSS meteorology. Although numerous empirical Tm models have been rigorously validated at regional and global scales, their applicability and reliability across China remain insufficiently characterized. To address this gap, this study systematically evaluated four representative Tm models – Hourly Global Pressure and Temperature 2 (HGPT2), Global Pressure and Temperature 3 (GPT3), Global Tropospheric Model (GTrop), and China Tropospheric Model (CTrop) – using stratified meteorological data from 87 radiosonde stations in China (2010–2019). Model performance was assessed through bias and root mean square error (RMSE) metrics. Key findings reveal significant spatial heterogeneity in model accuracy across China’s four geographic regions. The GTrop and CTrop models demonstrated superior accuracy and nationwide stability, whereas HGPT2 and GPT3 exhibited pronounced limitations in mid-to-high latitudes. Notably, the CTrop model outperformed GTrop at select stations, achieving the lowest overall bias (0.39 K) and RMSE (3.95 K) among all models. Altitudinal analysis indicated that all models performed optimally below 1,000 m, with GTrop and CTrop showing marked accuracy improvements at higher elevations. Temporal analysis further highlighted CTrop’s robustness, exhibiting minimal errors across seasonal and diurnal variations. However, all models were constrained by limited Tm value ranges. Collectively, these results establish CTrop as the most accurate and stable Tm model for PWV retrieval in China.
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Optimized ensemble single frequency ionospheric TEC model over the low latitude Indian region for GNSS applications

November 5, 2025

Raja Sekhar Chakali, Venkata Ratnam Devanaboyina

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An ionospheric broadcast model in a low-cost single-frequency GNSS receiver provides ionospheric corrections to improve its positional accuracy. This study evaluates the performance of the Klobuchar, NeQuick-G models, and proposes an optimized ensemble ionospheric model during the minimum (2020) and maximum (2024) phases of Solar Cycle 25 over the Indian low-latitude and equatorial regions. Dual-frequency Total Electron Content (TEC) data from International GNSS Service (IGS) stations over the Indian region, including JMSM, LCK4, JDPR, SHLG, and IISC stations data were analysed to quantify the proposed ionospheric TEC model accuracy under both quiet and disturbed geomagnetic conditions. The year 2024 exhibited strong solar activity, with Dst values reaching −412 nT and Kp index up to 9 during the May 10-11 geomagnetic storm. Model errors were computed as the difference between observed and predicted Vertical TEC (VTEC) values. The proposed optimized ensemble model, based on performance-weighted integration of Klobuchar and NeQuick-G outputs, consistently achieved the lowest RMSE values, ranging from 1.66 TECU (winter 2020) to 6.98 TECU (May 2024 storm), compared with the NeQuick-G (up to 30.07 TECU) and Klobuchar (up to 40.02 TECU). The analysis of proposed optimized ensemble ionospheric model revealed clear seasonal behaviour capture, with VTEC maxima during the equinoxes (50–100 TECU) and minima during solstices (20–40 TECU). Results demonstrate that the optimized model significantly enhances ionospheric prediction accuracy under both quiet and storm-time conditions, offering a robust solution for single-frequency GNSS applications in low-latitude regions strongly affected by ionospheric variability.
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Comparative analysis of CYGNSS-derived soil moisture and its spatiotemporal distribution across Egypt and Africa

September 18, 2025

Ahmed Salah El-Din, Ibrahim Fouad Ahmed, Ashraf El-Kutb Mousa, Gamal El-Fiky

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Soil Moisture Content (SMC) is a crucial variable influencing Earth’s environmental processes, including the water cycle, energy balance, and carbon cycle. Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a powerful tool for monitoring SMC. The Cyclone Global Navigation Satellite System (CYGNSS), a mission consisting of eight microsatellites launched by NASA in 2016, utilizes GNSS-R to provide high-temporal-resolution soil moisture estimates. This study conducts a comparative analysis of CYGNSS-derived SMC data against SMAP, SMOS, CEDA, and ERA5 datasets over Egypt and Africa from 2017 to 2021. Using tolerance and interpolation techniques, the analysis revealed strong correlations between CYGNSS and the other datasets, with overall correlation values of 0.78 (SMAP), 0.64 (SMOS), 0.74 (CEDA), and 0.80 (ERA5). The corresponding RMSE values were 0.022, 0.018, 0.027, and 0.035 cm 3 /cm 3 , respectively. Interpolation results showed correlations of 0.76, 0.47, 0.54, and 0.39, with RMSE values of 0.03, 0.065, 0.045, and 0.076 cm 3 /cm 3 , respectively. Additionally, the study analyzes the spatiotemporal distribution of soil moisture across Egypt and Africa, revealing regional variations and trends over the study period. These findings demonstrate CYGNSS’s effectiveness in capturing soil moisture variations, particularly in Egypt.
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Assessment of GNSS signal strength and positioning performance using single/dual-frequency android smartphones

November 4, 2025

Devadas Kuna, Naveen Kumar Perumalla

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The integration of Global Navigation Satellite System (GNSS) chips in commercial smartphones has enabled cost-effective geolocation and navigation applications. Modern GNSS-enabled smartphones can record raw GNSS data using freely available Android apps, making them viable for geodetic applications without additional hardware or software costs. Despite their advantages, challenges such as noisy GNSS observations, environmental effects, and device-holding modes limit the accuracy of smartphone-based positioning. This study investigates the feasibility of using low-cost, single/dual-frequency Android smartphones (Huawei Nova 3e, Moto G52, and Poco M3) for acquiring raw GNSS observations in indoor and outdoor environments, with a focus on signal strength and positioning precision (with respect to the median solution). Dual-frequency linear combinations (L1/E1, L5/E5) were used to reduce first-order ionospheric delays to improve relative positioning precision. The study further analyzes the performance of Weighted Least Squares (WLS) and Kalman Filtering (KF) for smartphone-based positioning. Results highlight the benefits of KF for dual-frequency smartphones and reveal that satellite acquisition primarily depends on the GNSS chipset used. These findings provide valuable insights for the geospatial and GNSS research community, demonstrating the potential of GNSS smartphones for cost-effective and practical applications.
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Characteristics of hydrological loading signals in GNSS observations: a case study from IITK and LCK4 stations

January 7, 2026

Jagat Dwipendra Ray, Kutubuddin Ansari, Walyeldeen Godah

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The study investigates surface deformation caused by hydrological mass changes using Global Navigation Satellite System (GNSS) data and a hydrological model at two International GNSS Service (IGS) stations – IIT Kanpur (IITK) and Lucknow (LCK4) – located in the Ganges basin. A key novelty of this work is the comparative assessment of GNSS-observed and Land Surface Discharge Model (LSDM) – modeled vertical Earth surface deformation over North India. The goal is to assess how variations in terrestrial water storage affect vertical crustal deformation in this region. GNSS-derived vertical displacement time series were compared with those modeled using the Land Surface Discharge Model (LSDM), that provides terrestrial water storage changes at a 0.5° × 0.5° spatial resolution. Both GNSS and LSDM time series exhibit a clear annual cycle, reflecting the dominant impact of seasonal hydrological loading. To analyze the relationship between GNSS-observed and LSDM-modeled deformations, wavelet transform analysis was employed to detect time-localized spectral power and coherence across frequencies between the two datasets. Correlation coefficients between GNSS and LSDM deformation exceed 0.7 at both IGS stations, indicating strong agreement. However, LSDM explains only about 40–60 % of the variance observed in the GNSS data, suggesting the influence of other geophysical or environmental factors are not captured by the model. Wavelet coherence analysis confirms strong correlation in the annual frequency band.
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Investigating the relationship between accuracy and orders of global geopotential models over GNSS/Levelling stations: a case study of Egypt

August 7, 2025

Gomaa M. Dawod, Essam M. Al-Krargy, Ghada G. Haggag

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Although there are several factors could affect the accuracy performance of Global Geopotential Models (GGMs), the current research investigates if the order of a model represents the key aspect influencing its accuracy. Fourteen GGMs, with variable orders, have been selected to be tested over 1,100 Global Navigation Satellite Systems (GNSS)/Levelling stations in Egypt. The performance of global models has been analyzed against that of a national geoid model. Additionally, the performance of GGMs over variable topography in Egypt has been investigated too. Based on the available data and the attained findings, it has been found that the low-order GGMs produced mean geoid undulations very far from that of the national model. Over the available checkpoints, it has been recognized that the accuracy of high-order GGMs is less than ± 0.276 m. However, a particular medium-order model produced a better performance with a standard deviation equals ± 0.193 m. Other medium-order models resulted in accuracy varies between ± 0.238 m and ± 0.371 m. In addition, the models produced slightly better performance over high-elevation topography in Egypt. Furthermore, statistical analysis demonstrates that the correlation between model’s order and accuracy equals −0.38 which indicates that such an association is weak. The regression coefficient of determination has been estimated as 0.14 which concludes that the regression is feeble since only 14 % of the accuracy variations are affected by the model’s order. Such remarks highlight that there is no significant association between the order and accuracy of GGMs over GNSS/Levelling stations in Egypt.
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CRS transformations in North Macedonia: accuracy, offsets, and harmonization pathways

December 3, 2025

Bashkim Idrizi

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For over a century, North Macedonia has relied on coordinate reference systems (CRS) inherited from former Yugoslavia, resulting in inconsistencies between legal definitions, institutional practice, and usage. Despite several legal revisions, no comprehensive national framework has yet resolved these inconsistencies, leaving a critical research gap concerning the harmonization of CRS variants and their implications for interoperability. This study traces the historical development of CRS in the country, analyzes harmonization challenges, and compares regional transitions. Methodologically, the paper combines historical, legal, and technical analysis with comparative assessment of EPSG codes and transformation parameters, offering a systematic evaluation of CRS accuracy and offsets. Currently, three CRS variants (EPSG:6204, EPSG:6316, and EPSG:9945) coexist, producing offsets of 7,000 km in easting and 4,000 km in northing, which hinder GIS integration. Unlike neighboring states adopting ETRS89, North Macedonia lags behind. The findings highlight the need for an officially recognized transition toward an ETRS89-based CRS to achieve national and regional interoperability. Coordinated reforms, including EPSG registry recognition and transition to ETRS89, are essential for interoperability and reliable spatial infrastructure.
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Establishment of the new gravity reference frame of Kazakhstan (QazGRF)

December 3, 2025

Roman Sermiagin, Anel Islyamova, Adlet Kutpanov, Danabek Tazhedinov, Andrey Drozd, Samat Kinzhiguzhinov, Danil Lymarev, Mikhail Merkulov

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The article presents the results of establishing a new national gravimetric reference frame of Kazakhstan (QazGRF) based on absolute gravity measurements. The work was carried out during two field campaigns in 2023 and 2024 for zero-order and first-order stations, respectively, with each campaign lasting no more than three months. As a result, 74 primary absolute stations were created, and around each of them, within a radius of up to 100 km, secondary points were built–ranging from 1 to 20 depending on the order and local conditions. In total, the QazGRF comprises 218 primary and secondary stations. The gravity at the secondary points was determined by relative gravimetry, and the vertical gravity gradient was measured at each absolute station. The work followed the requirements for establishing the International Terrestrial Gravity Reference Frame (ITGRF). Data were processed using both standard software and specially developed packages for the adjustment of local gravimetric networks and for determining the vertical gravity gradient parameters. The mean total standard uncertainty of the gravity values at the primary absolute stations does not exceed 6.5 μGal, with the best results reaching 6.0 µGal, while at the secondary stations it does not exceed 7.7 µGal, with the best results of 7.3 µGal. This implementation represents the first realization of the national gravity reference frame of Kazakhstan using the absolute method.
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Estimation of precipitable water vapour by GNSS meteorology in Black Sea region of Türkiye

November 17, 2025

Emine Tanır Kayıkçı, Kutubuddin Ansari, Vincenza Tornatore, Selma Zengin Kazancı, Mualla Yalçınkaya

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This study investigates the estimation of precipitable water vapour (PWV) using Global Navigation Satellite System (GNSS) meteorology in the Black Sea region of Türkiye, an area characterized by high rainfall and significant climatic variability. GNSS observations from four permanent stations (SAME, SOMU, MACK, and TRAB) between October 2017 and December 2019 were processed with Bernese 5.2 software to retrieve zenith total delay and derive PWV. The Vienna Mapping Function 1 (VMF1) was applied with a 10° elevation cut-off angle, and orography-dependent pressure and temperature fields were used for tropospheric modeling. The results were compared with radiosonde measurements from Samsun station and ERA-Interim reanalysis data to assess reliability. Findings show that GNSS-derived PWV varied between 1 and 46 mm, with strong seasonal and diurnal cycles higher in summer and daytime, and lower in winter and nighttime. Radiosonde PWV exhibited strong correlation with GNSS PWV ( r > 0.9), while ERA-Interim tended to overestimate values, particularly at higher elevation sites. GNSS PWV demonstrated a strong positive correlation with surface temperature (∼0.8) and an inverse relationship with atmospheric pressure. These results confirm the potential of GNSS meteorology as a reliable tool for continuous and high-resolution monitoring of atmospheric water vapour, supporting weather forecasting and climate studies in the Black Sea region.
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An IoT-integrated SVMD-RVFL framework for ionospheric monitoring toward enhanced GNSS navigation applications

November 4, 2025

Jyothi Ravi Kiran Kumar Dabbakuti, Mallika Yarrakula, Shameem Syed, Venkateswara Rao Musala, Gopi Krishna Popuri

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Total electron content (TEC) is a important parameter in the domains of space weather studies and Global Navigation Satellite System (GNSS)-based navigation and communication applications. Conventional linear forecasting models face difficulties in effectively representing the complex nonlinear behaviors of the ionospheric dynamics. On the other hand, nonlinear approaches derived from advanced learning methods offer higher accuracy, but they necessitate substantial computational resources, building them impractical for real-time use in resource-constrained IoT environments. The emergence of Internet of Things (IoT) technology has facilitated the accessibility of affordable GNSS data associated through cloud platforms, allowing for ongoing and instantaneous collection of TEC data. In this paper, an efficient Successive Variational Mode Decomposition (SVMD) and Random Vector Functional Link (RVFL) framework is implemented to predict TEC via cloud platforms through Think Speak channels. The TEC observations from the year 2018 at Bengaluru (Geographic: 13.02° N, 77.57° E) is consider for analysis. The SVMD adaptively decomposes the TEC signal without requiring predefined mode selection, while RVFL enables fast training using random weights, direct connections, and universal approximation capabilities. The proposed model was evaluated using GNSS data from Bengaluru (13.02° N, 77.57° E). The results demonstrate that the SVMD–RVFL has an accuracy of 0.55 TECU for Root Mean Square Error (RMSE), 0.61 TECU for Mean Absolute Error (MAE), 7.64 % for Mean Absolute Percentage Error (MAPE), a correlation coefficient of 99.32 % and a training time of 3.82 s. The proposed approach demonstrates high precision and a low computational load, making it suitable for real-time ionospheric monitoring systems and IoT technologies.
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A local 3-D ionospheric model based on COSMIC-2 radio occultation GNSS data and deep neural networks

January 19, 2026

Ismail Zaher, Zaki Zeidan, Mostafa Rabah, Mahmoud El-Mewafi

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The growing availability of ground and space-based Global Navigation Satellite System (GNSS) observations has significantly enhanced our ability to monitor ionospheric variability with improved spatial and temporal resolution. The FORMOSAT-7/COSMIC-2 (F7/C2) mission provides a comprehensive database of high vertical resolution radio occultation (RO) profiles, enabling detailed long-term ionospheric studies. This work presents a three-dimensional ionospheric electron density model over Egypt, developed using Deep Neural Networks (DNN) trained on F7/C2 RO data from 2020 to 2024, designated as 3D-DNN Ion-EG. The optimized DNN architecture captures complex nonlinear relationships between electron density and nine geophysical and temporal inputs: latitude, longitude, altitude, universal time, day of year, year, solar flux (F10.7), and geomagnetic indices (ap and Dst). The 3D-DNN Ion-EG model demonstrates high predictive accuracy for ionospheric electron density, achieving an R 2 of 0.93 and RMSE of 121,000 el/cm 3 during independent testing on 36,856 F7/C2 observations. Comprehensive validation shows that the model outperforms the International Reference Ionosphere (IRI-2020 and IRI-Plas) across multiple parameters including electron density, total electron content (TEC), F2-layer peak density (NmF2), and complete vertical profile reconstructions. The model successfully captures ionospheric variability under both quiet and disturbed geomagnetic conditions, demonstrating superior performance in Egypt’s complex low-latitude environment near the Equatorial Ionization Anomaly (EIA). These results highlight the model’s potential for high-resolution ionospheric modeling over Egypt, with promising applications in GNSS error correction, space weather forecasting, and upper atmospheric research.
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Direction-resolved azimuth–elevation metrics for GNSS station quality assessment

January 19, 2026

Revathi Nagarajan, Onkar Dikshit, Nagarajan Balasubramanian

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Satellite geometry and sky visibility critically influence Global Navigation Satellite System (GNSS) observation quality. Conventional quality measures such as multipath, cycle slip, SNR ratio, Position Dilution of Precision (PDOP) require sufficient valid data and time-consuming processing, whereas azimuth–elevation (Az–El) metrics can be derived directly from raw observations in RINEX files and satellite ephemeris. In this study, we propose a simple set of Az–El metrics to characterize site suitability and evaluate their ability to replicate the PDOP-based composite (baseline). We compared normalized composite scores from both approaches (Az–El composite (proposed)) using one year of GPS data from 66 continuously operating reference stations (CORS) in northern India (2024). All metrics were ECDF-scaled to [0–1], and ‘lower-is-better’ terms were flipped so higher values always indicate better quality. Agreement between Az–El and PDOP composites remained high (Spearman ρ ≈ 0.956, Kendall τ ≈ 0.831); 3-class accuracy ≈ 84.6 % with Cohen’s κ ≈ 0.769 (tertiles), with no Good↔Limited class flips. These results show that Az–El metrics provide a rapid, processing-light field-ready based QC, suitable for large-scale monitoring and national reference-frame operations. Unlike PDOP, the Az–El metrics explicitly localize direction-specific obstructions (largest blocked sector) and overall sky openness, enabling targeted field remediation and routine QC.

Special Issue: Joint International Symposium on Deformation Monitoring 2025

Special Issue: Deformation Monitoring

Special Issue: Deformation Monitoring

Special Issue: Deformation Monitoring

Special Issue on Multi-sensor Systems in Engineering Geodesy and Navigation

Journal of Applied Geodesy publishes special and thematic issues focussed on important and emerging topics in the field of study. The journal has established a rigorous process to ensure that any special issue manuscripts follow the same high-quality standards and peer review processes as regular manuscripts. For further information on the journal’s peer review policy please see the "Instructions for Authors".

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Volume 19 | Issue 3 Special Issue: Joint International Symposium on Deformation Monitoring 2025

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Editors-in-Chief
Hans-Berndt Neuner, TU Wien, Austria
Chris Rizos, University of New South Wales, Sydney, Australia

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Xiaoli Ding, The Hong Kong Polytechnic University, Hong Kong, China
Andreas Eichhorn, Technische Universität Darmstadt, Darmstadt, Germany
Naser El-Sheimy, The University of Calgary, Calgary, Canada
Linlin Ge, University of New South Wales, Sydney, Australia
Vassilis Gikas, National Technical University of Athens, Athens, Greece
Dorota Grejner-Brzezinska, The Ohio State University, Columbus, USA
Cheinway Hwang, Chiao Tung University, Hsinchu City, Taiwan
Allison Kealy, University of Melbourne, Victoria, Australia
Heiner Kuhlmann, Universität Bonn, Bonn, Germany
Hansjörg Kutterer, Bundesamt für Kartographie und Geodäsie, Frankfurt, Germany
Xiaolin Meng, University of Nottingham, Nottingham, United Kingdom
Gyula Mentes, Geodetic and Geophysical Research Institute of HAS, Sopron, Hungary
Hans-Berndt Neuner, Vienna University of Technology, Vienna, Austria
Wolfgang Niemeier, Technical University Braunschweig, Braunschweig, Germany
Alexander Reiterer, Fraunhofer Institute for Physical Measurement Techniques IPM, Freiburg, Germany
Guenther Retscher, Vienna University of Technology, Vienna, Austria
Volker Schwieger, University of Stuttgart, Stuttgart, Germany
Peter Teunissen, Delft University of Technology, The Netherlands and Curtin University of Technology, Perth, Australia
Andreas Wieser, ETH Zürich, Zürich, Schweiz
Caijun Xu, Wuhan University, Wuhan, Hubei, China

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1862-9024

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1862-9016

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First published:

March 22, 2007

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4 issues per year

eISSN: 1862-9024

ISSN: 1862-9016

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