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Journal of Applied Geodesy

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

Sprache: Englisch

Erstveröffentlichung: 22. März 2007

Erscheinungsweise: 4 Hefte pro Jahr

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Über diese Zeitschrift

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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Ihre Vorteile

Your benefits:

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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Mitigation of chirp interference in NavIC signals using NWPR and SNV estimator

23. September 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 .
Open Access
Exploring LSTM neural networks for sea level forecasting based on two-decadal tidal and meteorological data

22. September 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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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

18. September 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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Comparative analysis of CYGNSS-derived soil moisture and its spatiotemporal distribution across Egypt and Africa

18. September 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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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

27. August 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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Quality analysis of reference GPS stations in Ecuador

30. Juni 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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Investigating the preparation phase of volcanic eruptions using Swarm and GPS-TEC satellite data: The case of the 29 May 2024 Iceland-Sundhnúkur volcanic eruption

27. Juni 2025

Mehdi Akhoondzadeh

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In the last 6 months, 5 eruptions have been reported at the location of Iceland’s volcanoes. In this study using the electron density and temperature data measured by the LP sensor onboard the Swarm satellites (A, B, C), the volcanic ionospheric anomalies around the location and time of the Sundhnúkur volcano have been investigated. Most parameters measured by the three Swarm satellites show striking anomalies on 34 and 8 days before the eruption. Also, in this study, GPS-TEC data were used as a volcanic precursor, and median-interquartile method was implemented to detect hidden and highly nonlinear volcano-ionospheric anomalies. This precursor detected clear anomalies in the time interval of 8 days before the eruption. Also, the values of AOD (Aerosol Optical Depth) parameter indicate abnormal behavior on 9 days prior to the event. To reduce the uncertainty of the detected volcanic anomalies, a confutation analysis was also performed, and no clear anomalies were observed in the same spatial and temporal interval studied, but in 2019. The observed anomalies are consistent with geological and seismic reports. For more detailed analysis, we separately investigated the tracks of the satellites crossing the volcano’s buffer zone. Observed anomalies in the time series analysis were acknowledged. Therefore, the results of this study emphasizes that Swarm satellite data, along with other satellite and field data, can be used to predict, detect and track volcanic activities and it is shown that by comparison with other lithospheric and atmospheric precursors, uncertainty in eruption prediction can be reduced.
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Assessing ground deformation monitoring techniques in Midvaal, South Africa

27. Juni 2025

Thobani Maluleka, Siphiwe Matthews Mphuthi

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Ground subsidence, the gradual sinking of the earth’s surface, poses a significant challenge globally, affecting regions like Midvaal, South Africa. This study employed Persistent Scatterer (PS) and Small Baseline Subset (SBAS) InSAR time-series analysis, continuous Global Navigation Satellite Systems (cGNSS) validation, and Random Forest machine learning to monitor and model ground subsidence using Sentinel-1 data (2019–2021). SBAS InSAR showed higher ground subsidence rates than PS InSAR, with cGNSS validation revealing InSAR limitations. Factor analysis identified NDVI, NDWI, lithology, and elevation as key drivers. The Random Forest model generated a susceptibility map, classifying areas into five vulnerability levels. Results indicate that Midvaal experiences significant ground subsidence, likely due to groundwater extraction for agricultural activities and mining, impacting approximately 3.4 % of the study area (118.85 sq. km). This study provides critical insights for sustainable land management and infrastructure planning in ground subsidence-prone regions.
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Developing Malaysia continuous hydrographic datum (MyCHD) by assimilating tide gauge, satellite altimeter, and global hydrodynamic model

27. Juni 2025

Mohd Faizuddin Abd Rahman, Mohammad Hanif Hamden, Ami Hassan Md Din, Mohd Razali Mahmud

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The advancement of multi-mission satellite altimeters has greatly enhanced the conventional approach of using a tide gauge station to establish a localised hydrographic datum. However, there are still several limitations in continually depending on a small number of sparsely distributed tide gauge stations and wide satellite altimeter track missions, even with its continuous monitoring of ocean data at local and worldwide coverage. Such limitation has left a region farther away from the satellite altimeter track and tide gauge stations without any hydrographic data. Hence, this study aims to develop Malaysia’s Continuous Hydrographic Datum (MyCHD) by combining the satellite altimeter, tide gauge station, and global hydrodynamic model (GHM). In addition, the reliability of MyCHD was also assessed to determine the rate of improvement by incorporating GHM as additional hydrographic data. The research methodology involves collecting data from the Department of Survey and Mapping Malaysia (DSMM) tide gauge stations along Malaysia’s coastline, as well as satellite altimetry data from TOPEX, Jason-1, Jason-2, and GEOSAT Follow-On (GFO) via the Radar Altimeter Database System (RADS). Additionally, Indian Ocean GHM data from Oregon State University (OSU) was also utilised. The tide gauge, satellite altimetry, and GHM datasets encompass 26 years of tidal observations, spanning from 1993 to 2018. All hydrographic data were processed using harmonic analysis in Unified Tidal Analysis and Prediction (UTide) within MATLAB to establish the hydrographic datum. The derived Lowest and Highest Astronomical Tide (LAT and HAT) from tide gauge, satellite altimetry, and GHM data were referred to the Mean Sea Level (MSL) for compatibility in data integration; these were designated as LAT MSL  and HAT MSL , respectively. Then, using ArcGIS software, the LAT MSL  and HAT MSL were interpolated using Inverse Distance Weighting (IDW). In contrast to the integration of tide gauge and satellite altimeter, the statistical assessment showed that the integration of tide gauge, satellite altimeter, and GHM has a better agreement with the DSMM tide gauges, with a Root Mean Square Error (RMSE) of ± 0.671 m for LAT MSL and ± 0.370 m for HAT MSL . In percentage terms, incorporating GHM data with tide gauge and satellite altimeter in establishing MyCHD has significantly improved its reliability by 17 % for LAT MSL and 30 % for HAT MSL respectively. In conclusion, the hydrographic datum is now available at any coordinate along Malaysia’s coast with the establishment of MyCHD (LAT MSL and HAT MSL ).
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GNSS interferometric reflectometry as a passive remote sensing method for studying environmental phenomena

26. Juni 2025

Mohamed Abdelhamid

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Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) is a versatile remote sensing technique that utilizes reflected GNSS signals for environmental monitoring. By analyzing interference patterns between direct and reflected GNSS signals, GNSS-IR enables the estimation of surface characteristics such as soil moisture, water level, and snow depth. This study investigates snow accumulation, soil moisture, and water level measurements using GNSS-IR over extended periods, providing insights into climate-related trends. Data from GNSS stations in both the northern and southern hemispheres were analyzed. Snow depth was monitored at two stations over a decade, revealing fluctuations in accumulation and highlighting potential impacts of climate change. Soil moisture was analyzed at a grass-covered site, with comparisons before and after vegetation correction. Water levels were measured using GNSS-IR data near a coastal stream, capturing clear tidal signatures. Results show consistent reflector height variations corresponding to snow depth changes, soil moisture dynamics, and water level oscillations (including tides), demonstrating the robustness of GNSS-IR for environmental monitoring of snow, soil moisture, and sea level.
Open Access
Linking persistent scatterers to airborne laser scanning points for identifying real objects reflecting SAR signal

25. Juni 2025

Natalia Wielgocka, Grzegorz Jóźków, Freek van Leijen, Ramon Hanssen, Kamila Pawłuszek-Filipiak

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The Persistent Scatterers Interferometry (PSI) method enables displacement estimation with millimeter accuracy. However, the uncertain positioning of Point Scatterers (PS) makes it difficult to associate them with real objects in space and hampers the interpretation of the results. This article proposes a methodology to enhance the accuracy of PS positions. The methodology successfully establishes links between PS and real objects by associating them with the most likely candidate points extracted from Airborne Laser Scanning (ALS) point clouds. The selection process for suitable candidates is based on ALS analysis of return number, classification, and geometric features determined by neighborhood analysis. The linking process involves determining global transformation parameters for PSs using the Iterative Closest Point (ICP) algorithm. Then, the nearest neighbor search within the error ellipsoid of the PS positions is performed. Tests conducted demonstrated that this method allows for linking more than 80 % and 65 % of the PS derived from Sentinel-1 and TerraSAR-X mission data, respectively, in both ascending and descending geometries. To validate the obtained results, in addition to the quantitative assessment, a qualitative analysis is performed based on a developed 3D visualization module showing all stages of the proposed methodology.
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Statistical analysis of Precipitable Water Vapor and rainfall variability in different geographical conditions of the Indian region

25. Juni 2025

Aaryan Kulkarni, Vesapogu Sujana Deepthi, Nishant Kumar, Sridhar Miriyala, Devanaboyina Venkata Ratnam

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Monitoring Precipitable Water Vapor (PWV) with Global Navigation Satellite System (GNSS) receivers is becoming a more viable and effective solution for meteorological applications such as rainfall prediction, climate change, and weather forecasting etc. This study investigates the statistical relationship between GNSS-derived Precipitable Water Vapor (PWV) and rainfall variability across five Indian cities, Bangalore, Hyderabad, Guwahati, Thiruvananthapuram, and Madurai, representing diverse geographic and climatic zones. GNSS-derived PWV data from the GPS Aided Geo Augmented Navigation (GAGAN) network and rainfall data from the Indian Meteorological Department (IMD) were considered from March 2013 to February 2014. Data has been analyzed based on seasonal trends and the dynamic interaction between atmospheric moisture and precipitation. The results represented significant spatial and temporal differences in rainfall patterns, with Thiruvananthapuram recording the highest monthly rainfall (143.90 mm in October 2013) due to dual monsoon exposure, and Madurai the lowest (88.5 mm in October 2013) owing to its rain-shadow location. Guwahati shows strong orographic influence and early monsoon peaks (121.30 mm in June 2013), while inland cities like Bangalore and Hyderabad experience delayed rainfall peaks during post-monsoon periods. Average monthly rainfall and PWV values were found to be closely linked to geographical factors such as elevation, topography, and proximity to coastlines. A clear correlation was observed between PWV and subsequent rainfall events; sharp increases in PWV exceeding 30 mm daily or rising at rates above 0.5 mm/h often preceded heavy precipitation.
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Evaluating stochastic models for estimating site velocity from daily and weekly GNSS time series in the stable region of the South American plate

23. Juni 2025

Haroldo Antonio Marques, Lucas Gonzales Lima Pereira Calado, João Francisco Galera Monico, Heloisa Alves Silva Marques, Maurício Carvalho Mathias de Paulo, Gabriela de Oliveira Nascimento Brassarote

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Accurate estimation of GNSS station velocities requires a precise characterization of stochastic noise in coordinate time series. This study evaluates stochastic models for estimating site velocities using weekly network and daily PPP GNSS solutions from 74 stations in the stable South American mid-plate. The functional model incorporated seasonal components, while the stochastic model was based on noise variance estimates. The Non-Negative Least Squares Variance Component Estimation method was applied to estimate noise amplitudes, classifying noise as a combination of white and colored components. Additionally, the spectral index was refined using Maximum Likelihood Estimation. Results show that most time series are best described by a combination of white and flicker noise, with differences in spectral properties between weekly and daily solutions. The impact of these models on velocity uncertainties was assessed, showing that neglecting an appropriate noise model can lead to overestimated uncertainties. These findings contribute to improving GNSS-based velocity estimations for geodynamic studies.
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Regional assessment of high-degree combined global gravity field model for geoid modelling over Nigeria

23. Juni 2025

Michael Bako

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Given the multitude of global gravity field model (GGMs) at our disposal, evaluating them against independent data is indispensable for delineating their quality and ascertaining their accuracy in Nigeria regions. In this study, we evaluated five combined GGMs (specifically SGG-UGM-2, XGM2019e_2159, GECO, EIGEN-6C4, and EGM2008) over Nigeria. Our evaluation is conducted using geoid undulations (mainly in FCT-Abuja) and free-air gravity anomalies (covering the whole country, Nigeria). The results showed that the differences between observed and GGMs implied geoid undulations at 20 GNSS/levelling points over FCT-Abuja (small area) revealed that XGM2019e_2159 fit better with standard deviation (SD) of 11.9 cm over the study area compared to other four evaluated combined GGMs. On the other hand, SD of the differences between observed and GGMs implied free-air gravity anomalies over Nigeria showed that XGM2019e_2159 performs slightly better than the other four evaluated combined GGMs with an SD of 7.04 mGal. These results further indicate a good prospect for the development of a precise gravimetric geoid model over Nigeria using XGM2019e_2159 model. However, more GNSS/levelling stations will be required for fittings of the gravimetric geoid model to the national vertical datum of Nigeria.
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Global equatorial F- and E-region ionospheric irregularities from COSMIC-RO and SCINDA-GNSS observations

13. Juni 2025

Aramesh Seif, Sampad Kumar Panda, Scott M. Bailey

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This study utilizes data from the FORMOSAT-3/Constellation Observing System for Meteorology, Ionosphere, and Climate radio occultation (COSMIC-RO) observations and ground-based Scintillation Network Decision Aid (SCINDA) GNSS recordings at four longitudinal stations situated in the vicinity of the magnetic equator for probing the characteristics of the ionospheric F and E region irregularities in the equatorial region. We utilize the amplitude scintillation index (S4) derived from these datasets to understand the morphology of nighttime and daytime plasma irregularities in the equatorial ionosphere. By combining ground-based data with a limb-viewing geometry from space, valuable complementary information has been obtained on the nighttime/daytime scintillation occurrences and their morphological associations with the equatorial irregularities in the F (equatorial plasma bubbles, EPB) and E (sporadic E layer; Es) region ionosphere. The occurrence of amplitude scintillation retrieved from COSMIC RO data was calculated to analyze its diurnal and seasonal variations. By conducting a statistical analysis on a dataset in 2013, we observed that the occurrence of ionospheric scintillation, as measured by both techniques, displayed similar variations. In this study, it is observed that scintillation in daytime is associated with Es and is predominantly seen over the Asian sector whilst nighttime scintillation associated with plasma bubbles is most frequently observed in the African sector. These results emphasize the need for RO profiles from active missions to serve as effective tools for monitoring scintillation events both regionally and globally.
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AI-driven versus traditional ionospheric modeling approaches for GNSS positioning in Egypt

1. Januar 2000

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

1. Januar 2000

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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Intrinsic and extrinsic calibration of a UAV-based multi-sensor system

1. Januar 2000

Arman Khami, Ingo Neumann, Sören Vogel

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The integration of multiple sensors, such as cameras and LiDARs, is increasingly employed in vehicle navigation and 3D environmental mapping. Accurate multi-sensor data fusion relies heavily on the precise estimation of extrinsic parameters, which define the geometric transformations between sensors. However, when low-cost sensors are used, systematic errors in their intrinsic characteristics often introduce inaccuracies in subsequent applications. To address this challenge, we investigate the impact of intrinsic calibration of a low-cost LiDAR on the accuracy of its extrinsic calibration parameters. Our study evaluates a generalized intrinsic calibration approach that assumes a single scale factor and bias for the LiDAR’s laser rays, in contrast to a detailed model where individual scale factors and biases are estimated for each ray. While the generalized approach exhibits noticeable deviations from the systematic parameters of some rays, it has a substantial positive impact on the estimated extrinsic parameters of the LiDAR, leading to improved mounting accuracy. This improvement highlights the critical role of intrinsic calibration in achieving reliable extrinsic calibration for multi-sensor systems. To ensure robust extrinsic calibration, we decouple the intrinsic and extrinsic calibration processes, thereby providing rectified input data for extrinsic calibration. Furthermore, we present an extrinsic calibration approach for a multi-sensor system comprising an inertial measurement unit, two cameras, and a LiDAR, where the cameras and LiDAR share only a narrow overlapping field of view, resulting in minimal shared information. By employing a high-accuracy reference instrument, we address the limited overlap issue and validate both the extrinsic calibration results and the impact of the LiDAR’s intrinsic calibration. Our findings demonstrate that untreated LiDAR intrinsic errors lead to significant deviations in the extrinsic calibration parameters, underscoring that intrinsic calibration is not merely a preliminary step but a vital factor in ensuring accurate extrinsic calibration in multi-sensor systems.
Open Access
Sensitivity quantification of spatially averaged displacement estimates in TLS-based geomonitoring

1. Januar 2000

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.
Open Access
Using robotic total station networks for 360° prism deviation reduction

1. Januar 2000

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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Unificative methodology for determining recent dynamic parameters of tectonic plates based on GNSS data

1. Januar 2000

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.
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Geopotential-number estimation based on regional and global geoid models towards vertical datum modernization in India

1. Januar 2000

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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Hybrid algorithm for identification of stable reference points in a monitoring network

1. Januar 2000

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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Optimized ensemble single frequency ionospheric TEC model over the low latitude Indian region for GNSS applications

1. Januar 2000

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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An autoregressive adaptive Kalman filter carrier tracking approach for mitigating ionospheric scintillation effects in GNSS receivers

1. Januar 2000

Ram Kumar Vankadara, Melania Susi, Abhijit Dey, Emanuele Pica, Alex Minetto, Sampad Kumar Panda

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Ionospheric scintillation causes a serious threat to the accuracy, integrity, and reliability of Global Navigation Satellite System (GNSS) receivers, leading to significant amplitude fading, and rapid phase fluctuations. The GNSS receivers with traditional carrier-tracking loops may sometimes fail to retain signal integrity during high scintillation scenarios, leading to degraded positioning performance or even loss of lock and can seriously affect the dynamic systems and safety of life-critical applications. We present an Autoregressive Adaptive Kalman Filter (AR-KF) based tracking approach to enhance the robustness of the GNSS receivers under scintillation conditions. The adaptive KF algorithm in the proposed framework dynamically adjusts the time-varying characteristics of the parameters in its tracking loop by leveraging insights gained from a sophisticated and high rate software defined radio-frequency (RF) system collocated by a specialized ionospheric monitoring GNSS receiver whereas the succeeding AR algorithm plays a crucial role by intelligently predicting and refining the carrier phase estimates, thereby mitigating the distortions and enhancing the GNSS tracking loop resiliences. The efficacy of the proposed filtering algorithm is evaluated using real-time GNSS signals affected by weak, moderate, and strong scintillation conditions. Experimental results demonstrate that the combined approach in this work can ensure relatively robust navigation and timing performance by effectively tracking even in severe scintillation conditions. The analysis revealed minimal intervention of the algorithm during weak scintillation but intelligently improving the performance in moderate, and strong scintillation scenarios. The findings from this study suggest the effectiveness of integrating adaptive KF and AR architecture through advanced signal processing methodologies into GNSS receivers, offering a consistent solution for navigational applications during strong scintillation conditions.
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Assessment of orthometric height determination utilizing network of multi-baselines of GNSS Continuously Operating Reference Stations

1. Januar 2000

Chaiyaporn Kitpracha, Panithan Bamrungrad, Chalermchon Satirapod

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Global Navigation Satellite Systems (GNSS) offer a modern, efficient alternative to traditional leveling methods, with advantages in accuracy, cost-effectiveness, and adaptability to diverse terrains. This study examines GNSS leveling techniques using Thailand’s Continuously Operating Reference Station (CORS) network. A multi-baseline network approach is proposed to enhance redundancy, enabling weighted least squares adjustment for both absolute and relative methods. The performance of the multi-baseline approach is compared to the single-baseline method to assess its benefits. Results indicate that the multi-baseline absolute method achieves an accuracy of approximately 4 cm, surpassing the single-baseline absolute method and demonstrating a robustness to orthometric height errors caused by reference station anomalies. On the other hand, the relative method shows degraded performance for both single and multi-baseline approaches due to biases in antenna eccentricity, which necessitate reducing the ellipsoidal height at the marker point to the Permanent Bench Mark (PBM) level.
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Assessment of GNSS signal strength and positioning performance using single/dual-frequency android smartphones

1. Januar 2000

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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Investigating the relationship between accuracy and orders of global geopotential models over GNSS/Levelling stations: a case study of Egypt

1. Januar 2000

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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Estimation of precipitable water vapour by GNSS meteorology in Black Sea region of Türkiye

1. Januar 2000

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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Assessment of temporal variations of geoid, ellipsoidal and orthometric heights at proposed IHRF sites using space geodetic data

1. Januar 2000

Walyeldeen Godah, Samuel Milki Yadeta, Malgorzata Szelachowska, Georgia Fotopoulos

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The determination of accurate geoid, ellipsoidal and orthometric heights is essential for applications related to surveying engineering, geodetic and geoscience research. The International Association of Geodesy (IAG) defined the International Height Reference System (IHRS) as the conventional gravity field-related global height system. The realization of the IHRS to establish an International Height Reference Frame (IHRF) and its temporal variations, is an ongoing geodetic task. The objective of this research is to assess temporal variations of geoid, ellipsoidal and orthometric heights at proposed IHRF sites using space geodetic data, namely Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO), Global Navigation Satellite Systems (GNSS), Very Long Baseline Interferometry (VLBI), Satellite Laser Ranging (SLR), Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) and hydrological model. GRACE/GRACE-FO-based and GLDAS-based Global Geopotential Models were utilized to determine temporal variations of geoid height (Δ N ) and time-dependent changes of ellipsoidal height (Δ h ) at proposed IHRF sites. Moreover, Δ h at proposed IHRF sites were also obtained from GNSS, VLBI, SLR and DORIS solutions. Temporal variations of orthometric height (Δ H ) at proposed IHRF sites were determined by combining Δ N and Δ h . Results reveal that Δ N , Δ h , and Δ H at proposed IHRF sites are not negligible as they can reach several centimetres in terms of seasonal variations and at the and 1 cm level annually. These Δ N , Δ h , and Δ H would be required for the modernization and unification of international/national vertical datums in addition to contemporary requirements for precise height measurements.
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An IoT-integrated SVMD-RVFL framework for ionospheric monitoring toward enhanced GNSS navigation applications

1. Januar 2000

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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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

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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
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
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Caijun Xu, Wuhan University, Wuhan, Hubei, China

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