GPS Stations Research Articles

Mapping of Mean Deformation Rates Based on APS-Corrected InSAR Data Using Unsupervised Clustering Algorithms

Different interferometric approaches have been developed over the past few decades to process SAR data and recover surface deformation, and each approach has advantages and limitations. Finding an accurate and reliable interval for preparing mean deformation rate maps (MDRMs) remains challenging. The primary purpose of this paper is to implement an application consisting of three unsupervised clustering algorithms (UCAs) for determining the best interval from SAR-derived deformation data, which can be used to interpret long-term deformation processes, such as subsidence, and identify displacement patterns. Considering Port Harcourt (in the Niger Delta) as the study area, it was essential to remove the sources of error in extracting deformation signals from SAR data, spatially ionospheric and tropospheric delays, before using UCAs to obtain its characteristics and real deformation data. Moreover, another purpose of this paper is to implement the advanced integration method (AIM) for atmospheric phase screen (APS) correction to enhance deformation signals obtained through different SAR processing approaches, including interferometric SARs (two-pass interferometry, InSAR) and multitemporal interferometry SARs (n-pass interferometry, DInSAR; permanent scatterer interferometry (PSI); and small baseline subset (SBAS)). Two methods were chosen to evaluate and find the best technique with which to create an MDRM: The first one was to compare the signals corrected by the AIM and the vertical component of the GPS station, which showed the AIM providing 58%, 42%, and 28% of the matching with GNSS station outputs for InSAR, PSI, and SBAS, respectively. Secondly, similarity measures and Davies–Bouldin index scores were implemented to find an accurate and reliable interval in which the SBAS technique with the unsupervised K-medians method has been chosen. Based on GNSS vertical deformation in a 500 m radius around the station, the SBAS K-medians technique expressed up to 5.5% better deformation patterns than the map of SAR processing techniques.

Combined GRACE and GPS to Analyze the Seasonal Variation of Surface Vertical Deformation in Greenland and Its Influence

The geophysical effects are the main factor that causes the nonlinear motion of the station, and a comprehensive analysis of the relationship between the GRACE seasonal load deformation and the GPS station coordinates is helpful to study the physical mechanism that causes the nonlinear motion of the station. Aiming at the continuous GPS coordinate time series in Greenland, this paper comprehensively analyzes the correlation between GRACE seasonal load deformation and GPS station coordinates. First, in order to improve the accuracy of GPS station coordinates, the principle component analysis (PCA) method was used to eliminate the common mode error (CME) of the station coordinates. The results show that this method effectively reduces the uncertainty of the station coordinates time series. Secondly, when extracting seasonal signals, it is found that the singular spectrum (SSA) method can effectively obtain the time-varying part of seasonal signals, and its extraction effect is better than that of the least square fitting (LSF) method. Finally, the seasonal relationship between GRACE load deformation and GPS station coordinates is analyzed from the aspects of time series change, correlation, and WRMS reduction. It is found that there are differences in the amplitude and phase parts of the time series. The mean value of correlation is 0.73, the maximum reduction of WRMS is 55.20% (QAQ1 station), and the minimum is −22.69% (KMJP station), indicating that most stations mainly exhibit seasonal load deformation, while individual stations cannot effectively reflect. In addition, the influence of GRACE seasonal load deformation on the station coordinate parameters is quantitatively analyzed. The results show that the best noise model of the station is mainly WN + FN, which effectively reduces the velocity uncertainty of the station coordinate, and weakens the seasonal term oscillation.

Analysis of temporal and spatial variation characteristics of midlatitude summer nighttime anomaly in low and middle solar activity period

The spatiotemporal variation characteristics of midlatitude summer nighttime anomaly (MSNA) are essential for ionospheric modeling in the MSNA region. Based on GIM TEC, COSMIC NmF2, COSMIC IEC (Integrate Electron Content), and GPS TEC, this paper analyzes the spatiotemporal variation characteristics of MSNA during the low and middle solar activity period. First, we use the fourth-order Fourier function to fit the TEC, NmF2, and IEC. Second, we calculate an MSNA index and give its spatiotemporal distribution during the low and middle solar activity period. Third, on the basis of GIM TEC and GPS TEC, we describe the spatiotemporal distribution of TEC peak moments from October to January (Oct-Jan) and May to August (May-Aug). Our detailed analysis shows the following: (1) MSNA in the Southern Hemisphere is most significant in Oct-Jan. Moreover, MSNA in the Northern Hemisphere is most significant in May-Aug. (2) MSNA mainly occurs in three regions: South America and Antarctica, Western Europe to eastern North America, and Northeast Asia to the Pacific. (3) When solar activity increases, the MSNA region in the Northern Hemisphere becomes smaller, and the MSNA index is unchanged. Moreover, the MSNA region in the Southern Hemisphere is unchanged, but the MSNA index increases. (4) From Oct-Jan, there are some apparent differences between the east and west sides of the MSNA region of the Antarctic Peninsula. The peak moments of TEC in the west region concentrate before midnight (20:00–22:00 LT), and the peak moments of TEC in the east region concentrate after midnight (00:00–08:00 LT). As the level of solar activity increases, the peak moments in the eastern region are significantly shifted to later local time. (5) As the level of solar activity increases, the incidence of MSNA at three GPS stations (OHI300ATA, YSSK00RUS, and BRST00FRA) shows a decreasing trend.

LSTM-Based Deep Learning Methods for Prediction of Earthquakes Using Ionospheric Data

The ionosphere may play an essential role in the atmosphere and earth. Solar flares due to coronal mass ejection, seismic movements, and geomagnetic activity cause deviations in the ionosphere. The main parameter for investigating the structure of the ionosphere is Total Electron Content (TEC). TEC values obtained from GPS stations are a powerful technique for analyzing the ionospheric response to earthquakes and solar storms. This article analyzes the relations between earthquakes and TEC data to detect earthquakes. Our goal is to propose a prediction model to detect earthquakes in previous days. The ionospheric variability during moderate and severe earthquake events of varying strengths for 2012-2019 is discussed in this paper. The proposed models use LSTM-based (Long Short-Term Memory) deep learning models to classify earthquake days by analyzing TEC values of the last days. The LSTM-Based prediction models are compared against the SVM (Support Vector Machine), LDA (Linear Discriminant Analysis) classifier and Random Forest classifier to evaluate the proposed models based on earthquake prediction. The results reveal that the proposed models improve in detecting the earthquakes at an accuracy rate of about 0.82 and can be used as a successful tool for detecting earthquakes based on the previous days.

Geodetic Strain of the Baribis Fault Zone in West Java, Indonesia

The Baribis Fault’s status, which is located in the northern part of Java, as an active or inactive fault is a matter of considerable debate. In this study, we investigate the strain rate of the Baribis fault zone’s segment in northeastern West Java, Indonesia, as revealed by a dense network of GPS stations. We analyzed 17 surveyed GPS stations combined with continuous GPS sites over West Java from 2017 to 2021, then we estimate the GPS velocities fields. We calculated the strain rate and estimated it from the GPS velocities. In general, the Baribis fault zone experiences a significant strain rate (> 50 nano-strain/yr) with the compressional dilatation strain associated with the ongoing deformation in that area. The dilatation strain suggest that the northeastern Baribis fault in the West Java is an active thrust fault system. This information is essential to supporting a disaster mitigation program.

Storm-time variability of ionospheric irregularities over South America

The generation and development of ionospheric irregularities is an important topic of study in space weather, mainly because of their adverse effects on navigation and positioning systems, as well as in trans-ionospheric communications. To improve our prediction capabilities, it is necessary to better understand their variabilities during different geomagnetic conditions. The purpose of this research is to analyse the occurrence characteristics of ionospheric irregularities over South America during geomagnetic storms. Using data from six ionosondes and GPS stations in Brazil and Perú, observations from the JULIA radar and Swarm in situ electron density measurements, we examined the presence of irregularities during three intense storms (October 12, 2016, October 7, 2015 and August 25, 2018). Our data show that during the geomagnetic storms that occurred in October 2016 and October 2015, in the Brazilian region, the generation of ionospheric irregularities was usually inhibited during the storm recovery phase. During the main phase, spread-F was generated over the stations located close to the northern crest of the EIA, and it was inhibited over Cachoeira Paulista, a station near the southern crest. During the August 2018 storm, local winter, the geomagnetic activity may have helped generate the irregularities in all the stations analysed regardless of the phase of the storm. We suggest that the generation (inhibition) of irregularities is related to the effect of eastward (westward) storm time electric fields—disturbance dynamo electric fields and prompt penetration electric fields—that created favourable (unfavourable) conditions for the generation of irregularities by uplifting (lowering) the F region.

Global Ionospheric Disturbance Propagation and Vertical Ionospheric Oscillation Triggered by the 2022 Tonga Volcanic Eruption

The Tonga volcano erupted on 15 January 2022, at 04:15:45 UTC, which significantly influenced the atmosphere and space environment, at the same time, an unprecedented opportunity to monitor ionospheric anomalies is provided by its powerful eruption. In current studies of traveling ionospheric disturbance (TID) triggered by the 2022 Tonga volcanic eruption, the particular phenomenon of ionospheric disturbances in various parts of the world has not been reasonably explained, and the vertical ionospheric disturbances are still not effectively detected. In this paper, we calculate the high-precision slant total electron content (STEC) from more than 3000 ground-based GPS stations distributed around the world, then we obtain the radio occultation (RO) data from near-field COSMIC-2 profiles and investigate the horizontal TID and the vertical ionospheric disturbances by the singular spectrum analysis (SSA). Horizontal TID propagation captured by GPS STEC results indicates that acoustic-gravity waves dominate the energy input at the beginning of the ionospheric disturbance with an approximate speed of 1050 m/s initially. With the dissipation of the shock energy, lamb waves become a dominant mode of ionospheric disturbances, moving at a more stable speed of about 326 m/s to a range of 16,000 km beyond the far-field. Local characteristics are evident during the disturbance, such as the ionospheric conjugation in Australia and the rapid decay of TID in Europe. The shock-Lamb-tsunami waves’ multi-fluctuation coupling is recorded successively from the COSMIC-2 RO observation data. The shock and Lamb waves can perturb the whole ionospheric altitude. In contrast, the disturbance caused by tsunami waves is much smaller than that of acoustic-gravity waves and Lamb waves. In addition, influenced by the magnetic field, the propagation speed of TID induced by Lamb waves is higher towards the northern hemisphere than towards the southern hemisphere.

Geodetic observation of strain accumulation in the Banda Arc region

The Banda Arc region has produced several large destructive earthquakes, some of which have been followed by tsunamis. To better understand the earthquake potential in this area, we performed a comparison between geodetic and seismic moment rates. Data were collected from 110 continuous and campaign GPS stations observed for approximately ten years. The results show that the derived velocity field indicates that the Banda Arc deformation is characterized mainly by crustal shortening caused by the interaction of the Australian, Pacific, and Philippine Sea plates. Meanwhile, the contraction strain pattern dominates the Banda Arc area except around Papuan Bird’s Head. Areas with high strain rates have a history of significant seismicity, such as the Flores-Wetar Back Arc, the area around Ambon, and the Papuan Bird’s Head. The ratio of the geodetic moment rate to the seismic moment rate in the Banda, Bird’s Head, South Sulawesi, and Sumba zones are ∼1.5–7.0, indicating a moment deficit rate. The moment deficit rate provides an equivalent earthquake potential of Mw 7.7–8.1. This potential may be related to an aseismic deformation or stress accumulation, the under-sampling of long-term earthquake rates within the seismic catalogs, or a composite of these factors.

Lithosphere Ionosphere Coupling Associated with Seismic Swarm in the Balkan Peninsula from ROB-TEC and GPS

With the rapid development of global navigation satellite systems (GNSS) and their increasingly wide range of applications in atmospheric science, total electron content (TEC) data are widely used in the theoretical study of layer coupling related to seismicity. This study detected and analyzed pre-earthquake ionospheric anomalies (PEIA) by using TEC data from the Royal Observatory of Belgium (ROB), and analyzed coseismic ionospheric disturbance (CID) with vertical TEC (VTEC) from the GPS stations in earthquake preparation areas. The results show that PEIA appear to increase continuously from 08:00–12:00 UT in the 3 days before a seismic swarm of Mw > 5.0. The ionosphere over the seismogenic zones exhibited large-scale anomalies when multiple seismogenic zones of the Balkan Peninsula spatially and temporally overlapped. Moreover, the TEC around the earthquake centers showed a positive anomaly lasting for 7 h. In a single seismogenic zone in Greece, the TEC around the earthquake center reached over +3.42 TECu. In addition, the CID observed from GPS stations shows that with the increase in the number of earthquakes, the ionosphere over the seismogenic area is more obviously disturbed, and after three strong earthquakes, TEC suddenly decreased over the seismogenic area and formed a phenomenon similar to an ionospheric hole. We conclude that a lithosphere–atmosphere–ionosphere coupling mechanism existed before the seismic swarm appeared in the Balkan Peninsula. Earthquake-induced VTEC anomalies occurred more frequently within a 3–10 day window before the earthquake. This phenomenon is particularly evident when multiple seismogenic zones overlap spatiotemporally.

Can GPS and GRACE data be used to separate past and present-day surface loading in a data-driven approach?

SUMMARY Glacial isostatic adjustment (GIA) and the hydrological cycle are both associated with mass changes and vertical land motion (VLM), which are observed by GRACE and GPS, respectively. Hydrology-related VLM results from the instantaneous response of the elastic solid Earth to surface loading by freshwater, whereas GIA-related VLM reveals the long-term response of the viscoelastic Earth mantle to past ice loading history. Thus, observations of mass changes and VLM are interrelated, making GIA and hydrology difficult to quantify and study independently. In this work, we investigate the feasibility of separating these processes based on GRACE and GPS observations, in a fully data-driven and physically consistent approach. We take advantage of the differences in the spatio-temporal characteristics of the GIA and hydrology fields to estimate the respective contributions of each component using a Bayesian hierarchical modelling framework. A closed-loop synthetic test confirms that our method successfully solves this source separation problem. However, there are significant challenges when applying the same approach with actual observations and the answer to the main question of this study is more nuanced. In particular, in regions where GPS station coverage is sparse, the lack of informative data becomes a limiting factor.

Determination of tectonic and nontectonic vertical motion rates of the North China Craton using dense GPS and GRACE data

• The elastic (un-)loading response to mass changes is calculated using GRACE data. • The average estimated tectonic uplift rate in the mountain areas is 1.37 ± 0.6 mm/yr. • The maximum land subsidence rate in the North China Plain is 72.0 ± 1.2 mm/yr. • A high-resolution water mass variation model is needed. Previous geodetic vertical observations show that both uplift and subsidence occur in the North China Craton. While significant land subsidence occurs in the North China Plain, uplift is observed in the surrounding mountain areas. However, previous studies neither separate the tectonic and nontectonic vertical motions nor correct for elastic response to near surface mass changes. Here, we reply on the more GPS data from 1999 to 2020 and GRACE data from 2002 to 2020 to estimate the vertical motion rates. After removing the elastic (un-)loading deformation due to near surface mass variations, we obtain the tectonic uplift rates at GPS stations built on bedrock in the mountain areas like the Shanxi Plateau and land subsidence rates mainly in the North China Plain. The tectonic rock uplift mainly occurs in the Shanxi Plateau, Yanshan Montains, Shandong Peninsula and Dabie orogen, with an average uplift rate of 1.37 ± 0.6 mm/yr, which is larger than the long-term geological uplift rate. The land subsidence mainly concentrates in the North China Plain, Shanxi Graben, and Jiangsu province with the maximum subsidence rate of 72 ± 1.2 mm/yr. The mismatch between the geodetic and geological uplift rates suggests that a high-resolution water mass loss in the North China Plain is needed.

Magma pressurization sustains ongoing eruptive episode at dome-building Soufrière Hills volcano, Montserrat

Abstract Dome-building volcanoes, where long-term eruptive episodes can be interspersed with periods of intra-eruptive repose, are particularly challenging for volcanic hazard assessment. Defining the end of eruptive episodes is vitally important for the socioeconomic recovery of affected communities but highly problematic due to the potential for rapid transition from prolonged, seemingly low-risk repose to dangerous effusive or explosive activity. It is currently unclear what constitutes the end of repose and an eruptive episode. We show that analysis of surface deformation can characterize repose and help define an eruptive episode. At Soufrière Hills volcano, Montserrat, the long-term post–2010 deformation at 12 continuous GPS stations requires the pressure in the magma system to have increased with time; time-dependent stress relaxation or crustal creep cannot explain the deformation trends alone. Continued pressurization within the magmatic system during repose could initiate a renewed eruption, qualifying as sustained unrest and therefore continuation of the eruptive episode. For Soufrière Hills volcano, persistent magma pressurization highlights the need for sustained vigilance in the monitoring and management of the volcano and its surroundings, despite the last eruptive activity ending in 2010. Our results show promise for application to other dome-building volcanoes.

Offsets analysis of GPS stations in Taiwan

Offsets analysis of GPS stations in Taiwan

Troposphere Delay Remote Sensing Using Single GPS Receiver

The most prominent spatially correlated errors in GNSS observations are well known to be atmospheric effects. The ionosphere and troposphere are the two main layers of the Atmosphere that cause delays in GNSS observations. A linear combination of the dual-frequency data can be used to reduce ionospheric delay. Unlike the ionospheric delay, the tropospheric delay cannot be eliminated using the same methods. The troposphere is primarily associated with GPS. The delay it causes in GPS signals is regarded as one of the primary sources of errors that must be eliminated to determine accurate positions. This paper's main purpose is to develop a new source code that can estimate the effect of tropospheric delay over any GPS station. The tropospheric delay in this proposed code is estimated utilizing sequential least-squares adjustment using a model depending on Niell Mapping Function (NMF). This model, known as the Tropospheric Delay Estimation program, was created in the MATLAB® environment (TDE). This research presents the results of tropospheric delay during DOY 2, 2020 of actual data from ten ground-based IGS stations distributed over Antarctica, China, Canada, Fiji, Russia, Greenland, and Portugal IGS stations worldwide. For validation of the proposed code results, they were compared with troposphere delay results of the International GNSS Service (IGS). Good agreement and high correlation were found between both results. In comparison to IGS, the proposed code's standard deviations range from 0.0000525 m to 0.008154 m, indicating how accurate this study is in terms of agreement of solutions provided by IGS. Finally, the MATLAB software can accurately estimate troposphere delay with an adaptable temporal resolution for GPS users.

Wavelet analysis based VTEC variability over mid-latitude region Sukkur, Pakistan and its comparison with IRI models during 2019-2020

The Total Electron Content (TEC) from the Sukkur GPS station is studied during the final phase of the solar cycle 24 and the initial phase of solar cycle 25 (2019-2020). TEC comparisons are made with three international reference ionospheric models: IRI-2007, IRI-2012 and IRI-2016. The finding of the study indicates that IRI-2016 is better than IRI-2007 and IRI-2012 in monthly values using wavelet transformation. Moreover, the seasonal variations between observed and modelled VTEC were observed maximum during the spring season. Similarly, the IRI-2016 exhibited maximum correlation (i.e., r > 0.8) as compared to the other two models for both solar cycle phases. This study also includes a cross-correlation of GPS-VTEC with several storm indices (Kp, Dst, Ap) via wavelet transformation. In this paper, the wavelet spectrum is analysed for two-year data (2019-2020) to visualize the impact of geomagnetic storm indices on VTEC. Storms of different intensities during 2019-2020 solar activity were also analysed, where maximum correlation from wavelet transformation between GPS VTEC and geomagnetic indices was recorded during the initial solar phase of cycle 25. These kinds of studies assist to correct the measured GPS VTEC and help to improve predicted VTEC over mid-latitude regions.

Effects of Total Solar Eclipse on Ionospheric Total Electron Content over Antarctica on 2021 December 4

The effects of a total solar eclipse that occurred on 2021 December 4 on ionospheric total electron content (TEC) over Antarctic stations were studied. The study was based on GPS data obtained over Antarctica on the day of the eclipse and the days before and after the eclipse over six GPS stations. The findings of this study show that a total solar eclipse lowers the amount of ionization reaching the Earth’s surface with TEC values dropping across the stations. Finally, the enhancement of ΔTEC is quite different from one station to another station. This may also be due to the effect of solar heating conditions and the density of the Sun as exerted over the stations with the Sun side over one station and the clouded part over the others.

Size Composition of Hexaplex (Muricanthus) nigritus (Mollusca: Muricidae) in the Intertidal Zone of Five Islands of the Southeastern Gulf of California, Mexico

Background: Currently, there is no fishery regulation for Hexaplex (Muricanthus) nigritus in northwestern Mexico. The size composition of gastropod H. nigritus was recorded from five islands of Navachiste Bay, Sinaloa (Gulf of California, Mexico). Methods: Samples were taken every two months from February to December 2018. Islands established a georeferenced GPS station: Guasayeye, La Huitussera, Tesobiate, El Metate and San Lucas, Sinaloa, Mexico. The snail H. nigritus was collected in the littoral zone of the islands during the low tide syzygy tides. The organisms were collected directly at random and the total length (TL), width (WI) and height (HI) (0.01 mm) and total fresh weight (W) and muscle foot weight (FW) (0.1 g sensitivity). In addition, the shape of the growth was estimated with the equation that describes the relationship between length and weight. Result: The island of Guasayeye was a greater abundance (48%) and the least La Huitussera (4%). The mean total length (TL) was greater in San Lucas and La Huitussera (99.5±7.2 and 95.1±15.5 mm, respectively) and lower values were recorded in Tesobiate (73.8±11.4 mm). The maximum weight recorded was 347.2 g on El Metate island. A significance in length and weight were obtained between the islands. In addition, in H. nigritus high correlations were obtained relationships, indicating positive allometric growth. For their sizes and abundance, the snail H. nigritus is a potentially interesting fishing resource for the fishers of northwestern Mexico.

Application of RNN on GNSS Reflectometry Sea level monitoring

ABSTRACT Global Navigation Satellite System reflectometry (GNSS-R) can be used to monitor the sea level with the signal-to-noise ratio (SNR) using the spectral analysis approach where the additional frequencies in SNR lead to small errors. This study is the first attempt to apply the Recurrent Neural Networks (RNN) approach to reduce the effect of additional frequencies in SNR. The output from the RNN approach is processed by the spectral analysis to estimate the frequency. To analyse the number of effective results, all results are processed by the outlier removal method which removes the outliers only depending on the results under low elevation angles. The data set used in the experiment is sampled from the SC02 GPS station. The experiment is set up by using abnormal elevation angle ranges to observe the performance. The results from the RNN-based method, detrend SNR method and EMD-based method are compared to the reference sea level data. RNN models are trained differently in three experiments based on 7-day historical sea level data, 7-day tide prediction data and 1-month tide prediction data. The results show that the RNN increases the temporal resolutions for all experiments and provides sufficient accuracy as compared to the detrend SNR method and EMD-based method. Using tide prediction data instead of sea level data as the training data improves temporal resolutions and correlations. RNN can be applied as the data preparation and denoising method for SNR spectral analysis sea level monitoring. Compared to the EMD-based method, the RNN-based denoising method is more suitable for short SNR data records.

Three-dimensional coseismic deformation of the 2016 MW7.8 Kaikuora, New Zealand earthquake obtained by InSAR and offset measurements

The 2016 MW7.8 Kaikoura earthquake struck the northern part of south Island, New Zealand, within the active and complex Australia–Pacific plate boundary system. Firstly, we used the InSAR method to obtain coseismic LOS deformation fields based on SAR images and applied offset tracking methods to obtain offset measurements based on optical satellite images. The maximum displacement of about 6 m is detected in the direction away from the satellite on the south-west side and also towards the satellite on the north-east side. The 3D deformation field is then resolved by the combination of these measurements with a least-square solve method, and comparisons with 3 components of GPS stations show good consistency. Despite complex features demonstrated in the 3D deformation field, there are still clear spatial correlations between surface deformation and faults distribution. It reveals that more than ten faults were ruptured during the earthquake, including some faults were previously understudies for their tectonic activities. The maximum horizontal deformation of about 10 m occurs along the Kekerengu fault with the vertical deformation up to 2 m. The 3D deformation shows that the mainshock is a multi-segments faulting with a rupture process of strike-slip, compression, transpressional rupture and strike-slip in space along the NE direction.

Improving the performance of time varying spherical radial basis functions in regional VTEC modeling with sparse data

Least-squares parameterization of retrieved Vertical Total Electron Content (VTEC) from permanent dual-frequency GPS stations in terms of Time Varying Spherical Radial Basis Functions (TV-SRBFs) with optimal shape parameter leads to proper regional VTEC reconstruction at Ionospheric Pierce Points (IPPs). However, in the area where there is no observation, the modeling result is not satisfactory. This feature is especially tangible when the number of IPPs in the study area is low with poor geometric distribution, which leads to a rank deficient problem. Whereas, if the global ionospheric maps (GIMs) are used as a background in estimating the optimal shape parameter of TV-SRBFs and coefficients of the expansion, the stated obstacle to produce accurate regional ionospheric maps will be removed. For this purpose, an objective function is defined and optimized. The objective function consists of three terms. First, L-2 norm of the differences between the reproduced VTECs and values obtained from the receivers’ observations. Second, L-2 norm of the differences between the reproduced values on a regular grid with the values obtained from the spatial interpolation of GIM at a specific moment in the modeling interval. Third, the discrete smoothing norm of the coefficients of TV-SRBFs. Since the obtained VTECs from GPS receivers are more accurate than the resulted VTECs from interpolation of GIMs and also a regularization parameter is needed due to the ill-posedness, the three objectives cannot be considered with the same weights in the multi-objective optimization. Hence the weighted sum method with the preference-based solution is applied to obtain the optimal relative weight of GIMs, the regularization parameter and the coefficients. Moreover, utilizing the least-squares collocation (LSC) can also improve the modeling accuracy to some extent. The proposed method is applied for hourly regional VTEC modeling over Iran from 3 May to 9 May 2016, which had both low and very high geomagnetic activities. A portion of the retrieved VTECs which is excluded from the modeling dataset, is considered as test data. The Root Mean Square (RMS) of the differences between obtained VTECs from regional constructed model and test data is 0.94 TECU in the study period. RMS of the differences between obtained VTECs from the regional model and VTECs of two control stations which are not involved in the modeling are 1.12 TECU and 1.24 TECU. Also, the regional model performs well in ionospheric delay estimation and the accuracy of single-frequency positioning at control stations in the study period is better than 0.7 m.