The contribution of radar interferometry to the assessment of landslide hazards

Interferometric analysis of repeat pass radar images (InSAR) enables the mapping of slope movements with high accuracy, being of great relevance for the assessment of landslide risk. The InSAR method is briefly explained, with emphasis on data processing for landslide motion mapping. Constraints of the method are discussed, mainly resulting from temporal decorrelation of the radar signal in vegetated areas. Application examples for InSAR mapping of very slow slope movements, using SAR data of the European Earth Observation Satellite ERS, are shown for a mass waste above an alpine traffic route and for slope deformation in a mountain village. The comparison with GPS measurements of surface motion shows RMSE = 3.7 mm a⁻¹ between the InSAR and GPS retrieved motion, where part of this difference is attributed to the different observation periods. The investigations demonstrate the good capability of InSAR for detecting and monitoring surface deformation on mountain slopes, thus providing valuable support for landslide inventories and risk assessment.     

Coastal sea level changes in Europe from GPS,tide gauge,satellite altimetry and GRACE, 1993–2011

Sea level changes are threatening the human living environments, particularly along the European Coasts with highly dense population. In this paper, coastal sea level changes in western and southern Europe are investigated for the period 1993–2011 using Global Positioning System (GPS), Tide Gauge (TG), Satellite Altimetry (SA), Gravity Recovery and Climate Experiment (GRACE) and geophysical models. The mean secular trend is 2.26 ± 0.52 mm/y from satellite altimetry, 2.43 ± 0.61 mm/y from TG+GPS and 1.99 ± 0.67 mm/y from GRACE mass plus steric components, which have a remarkably good agreement. For the seasonal variations, annual amplitudes of satellite altimetry and TG+GPS results are almost similar, while GRACE Mass+Steric results are a little smaller. The annual phases agree remarkably well for three independent techniques. The annual cycle is mainly driven by the steric contributions, while the annual phases of non-steric (mass component) sea level changes are almost a half year later than the steric sea level changes.     

Atmosphere sounding by GPS radio occultation: First results from TanDEM-X and comparison with TerraSAR-X

On 21 June 2010 the TerraSAR-X satellite was joined by the TanDEM-X satellite. A Global Positioning System (GPS) radio occultation (RO) experiment using the twin satellites has been carried out to estimate the precision of GPS atmospheric soundings. For the Day Of Year (DOY) 330–336, 2011, we analyze phase and amplitude data recorded by GPS receivers separated by a few hundred meters in a low earth orbit and derive collocated atmospheric refractivity profiles. In the altitude range 10–20 km the standard deviation between TerraSAR-X and TanDEM-X refractivity does not exceed 0.15%. The standard deviation is rapidly increasing for lower and higher altitudes; close to the surface and at an altitude of 30 km the standard deviation reaches 0.8% and 0.5%, respectively. Systematic deviations between TerraSAR-X and TanDEM-X refractivity in the considered altitude range (0–30 km) are negligible. The results confirm the anticipated high precision of the GPS RO technique. However, the difference in the retrieved refractivity in the lower troposphere for different Open Loop (OL) signal tracking parameters, altered onboard TanDEM-X for DOY 49–55, 2012, calls for an in depth analysis. At the moment we can not exclude that a potential bias in the OL Doppler model introduces a bias in our retrieved refractivity at altitudes <8$<8$ km.     

Estimation of GPS instrumental biases from small scale network

With 4 GPS receivers located in the equatorial anomaly region in southeast China, this paper proposes a grid-based algorithm to determine the GPS satellites and receivers biases, and at the same time to derive the total electron content (TEC) with time resolution of 15 min and spatial resolution of 1° by 3.5° in latitude and longitude. By assuming that the TEC is identical at any point within a given grid block and the biases do not vary within a day, the algorithm arranges unknown biases and TECs with slant path TEC from the 4 receivers’ observations into a set of equations. Then the instrumental biases and the TECs are determined by using the least squares fitting technique. The performance of the method is examined by applying it to the GPS receiver chain observations selected from 16 geomagnetically quiet days in four seasons of 2006. It is found that the fitting agrees with the data very well, with goodness of fit ranging from 0.452 TECU to 1.914 TECU. Having a mean of 0.9 ns, the standard deviations for most of the GPS satellite biases are less than 1.0 ns for the 16 days. The GPS receiver biases are more stable than that of the GPS satellites. The standard deviation in the 4 receiver bias is from 0.370 ns to 0.855 ns, with a mean of 0.5 ns. Moreover, the instrumental biases are highly correlated with those derived from CODE and JPL with independent methods. The typical precision of the derived TEC is 5 TECU by a conservative estimation. These results indicate that the proposed algorithm is valid and qualified for small scale GPS network.     

Using altimetry and seafloor pressure data to estimate vertical deformation offshore: Vanuatu case study

Measuring ground deformation underwater is essential for understanding Earth processes at many scales. One important example is subduction zones, which can generate devastating earthquakes and tsunamis, and where the most important deformation signal related to plate locking is usually offshore. We present an improved method for making offshore vertical deformation measurements, that involve combining tide gauge and altimetry data. We present data from two offshore sites located on either side of the plate interface at the New Hebrides subduction zone, where the Australian plate subducts beneath the North Fiji basin. These two sites have been equipped with pressure gauges since 1999, to extend an on-land GPS network across the plate interface. The pressure series measured at both sites show that Wusi Bank, located on the over-riding plate, subsides by 11 ± 4 mm/yr with respect to Sabine Bank, which is located on the down-going plate. By combining water depths derived from the on-bottom pressure data with sea surface heights derived from altimetry data, we determine variations of seafloor heights in a global reference frame. Using altimetry data from TOPEX/Poseidon, Jason-1, Jason-2 and Envisat missions, we find that the vertical motion at Sabine Bank is close to zero and that Wusi Bank subsides by at least 3 mm/yr and probably at most 11 mm/yr.     

Kalman filtering for GPS/magnetometer integrated navigation system

This paper investigated the data processing method for a GPS/IMU/magnetometer integrated system with Kalman filtering (KF). As a result of GPS/IMU/magnetometer land vehicle system, dead-reckoning of magnetometer and accelerometer integrated subsystem bridged very well the GPS signal outage due to the trees on the two sides of the road. Both differential GPS data processing method and the carrier-phase method with magnetometers’ outputs for predicting the car position, velocity, and acceleration (PVA) are presented. The results from DGPS with Kinematical Positioning (KINPOS) software shown that the averages of the north, east, and down direction standard deviation (short for “std”) are 0.014, 0.010, and 0.018 m, respectively. The std of velocities and accelerations derived by the position and velocity differentiation are 10, 7, 13 mm/s, 7, 5, 9 mm/s², respectively. This method for getting velocities and accelerations requires higher accurate position coordinates. But the position accuracy has frequently been degraded in this case when the car drove under the trees or other similar kinematical environments. That caused the larger velocity and acceleration errors. While the results from the carrier-phase method are std of the velocities = 2.1 mm/s, 1.3 mm/s, 3.7 mm/s in north, east, down, and std of the accelerations = 1.5 mm/s², 0.9 mm/s², 2.3 mm/s² for the static test period; as compared with KINPOS software results, std of the velocity difference between the carrier-phase method and the DGPS method = 7 mm/s, 6.9 mm/s, 9.7 mm/s in north, east, down direction, and std of acceleration difference = 5.0 mm/s², 4.5 mm/s², 7.5 mm/s² in north, east, down direction for the kinematical test period. Obviously, errors come from both the carrier-phase method and DGPS velocity and acceleration results derived directly by the position differentiation. In addition, better accuracy of positions than that before KF has been got by means of velocities and accelerations derived by the carrier-phase method after KF.     

Vertical motions in Thailand after the 2004 Sumatra–Andaman Earthquake from GPS observations and its geophysical modelling

Following previous findings from ongoing GPS research in Thailand since 2004 we continue to exploit the GPS technique to monitor and model land motions induced by the Sumatra–Andaman Earthquake. Our latest results show that up to the end of 2010, Thailand has been co-seismically displaced and is subsequently undergoing a post-seismic horizontal deformation with total displacements (co-seismic plus post-seismic) ranging from 10.5 to 74.7 cm. We observed the largest horizontal displacements in the southern part of Thailand and moderate and small displacements in the central and northern parts. In addition to horizontal displacements throughout Thailand, continuous GPS measurements show that large parts of Thailand are subsiding at rates up to 1 cm/yr. It is the first time that such vertical post-seismic deformations at large distances (650–1500 km away from the Earthquake’s epicentre) have been recorded. We have investigated the physical processes leading to the observed subsidence. While after-slip on the subduction interface induces negligible or even slightly positive vertical motions, relaxation in the asthenosphere is associated with a sizable subsidence. Predictions from a 3D finite element model feature an asthenosphere with an effective viscosity of the order of 3 * 10¹⁸ Pas, fit the horizontal post-seismic data and the observed subsidence well. This model is then used to predict the subsidence over the whole seismic cycle. The subsidence should go on with a diminishing rate through the next two decades and its final magnitude should not exceed 10 cm in the Bangkok area.     

An Integer Precise Point Positioning technique for sea surface observations using a GPS buoy

GPS data dedicated to sea surface observation are usually processed using differential techniques. Unfortunately, the precision of resulting kinematic positions is baseline-length dependent. So, high precision sea surface observations using differential GPS techniques are limited to coasts, lakes, and rivers. Recent improvements in GPS satellite products (orbits, clocks, and phase biases) make phase ambiguity fixing at the zero difference level achievable and opens up the observation of the sea surface without geographical constraints. This paper recalls the concept of the Integer Precise Point Positioning technique and discusses the precision of GPS buoy positioning. A sequential version of the GINS software has been implemented to achieve single epoch GPS positioning. We used 1 Hz data from a two week GPS campaign conducted in the Kerguelen Islands. A GPS buoy has been moored close to a radar gauge and 90 m away from a permanent GPS station. This infrastructure offers the opportunity to compare both kinematic Integer Precise Point Positioning and classical differential GPS positioning techniques to in situ radar gauge data. We found that Precise Point Positioning results are not significantly biased with respect to radar gauge data and that horizontal time series are consistent with differential processing at the sub-centimetre precision level. Nevertheless, standard deviations of height time series with respect to radar gauge data are typically [4–5] cm. The dominant driver for noise at this level is attributed to errors in tropospheric estimates which propagate into position solutions.     

Noise analysis of continuous GPS coordinate time series for CMONOC

The Crustal Movement Observation Network of China (CMONOC) is one of the major scientific infrastructures, mainly using Global Positioning System (GPS) measurements, to monitor crustal deformation in the Chinese mainland. In this paper, decade-long coordinate time series of 26 continuous GPS sites of CMONOC are analyzed for their noise content using maximum likelihood estimation (MLE). We study the noise properties of continuous GPS time series of CMONOC for the unfiltered, filtered solutions and also the common mode signals in terms of power law plus white noise model. In the spatial filtering, we remove for every time series a common mode error that was estimated from a modified stacking of position residuals from other sites within ∼1000 km of the selected site. We find that the common mode signal in our network has a combination of spatially correlated flicker noise and a common white noise with large spatial extent. We demonstrate that for the unfiltered solutions of CMONOC continuous GPS sites the main colored noise is a flicker process, with a mean spectral index of ∼1. For the filtered solutions, the main colored noise is a general power law process, indicating that a major number of the filtered regional solutions have a combination of noise sources or local effects. The velocity uncertainties from CMONOC continuous GPS coordinate time series may be underestimated by factors of 8–16 if a pure white noise model is assumed. In addition, using a white plus flicker noise model, the median values of velocity errors for the unfiltered solutions are 0.16 (north), 0.17 (east) and 0.58 (vertical) mm/yr, and the median values for the filtered solutions are 0.09 (north), 0.10 (east) and 0.40 (vertical) mm/yr.     

An annual variation analysis of the ionospheric spatial gradient over a regional area for GNSS applications

An ionospheric spatial gradient represents the ionosphere delay difference between different locations, and its variation over a specific area is important for implementing differential GNSS systems. An estimation method for the ionospheric spatial gradient over a small regional area is proposed. A plate map model is implemented for the direct estimation of the gradients. Nine years of GPS data were processed to figure out the annual variation of the mean gradient at the mid-geomagnetic latitude of 30° N. Gradients along the north–south direction have a mean of 0.65 mm/km and follow solar-cycle variations.     

The realization and convergence analysis of combined PPP based on raw observation

In order to speed up Precise Point Positioning (PPP)’s convergence, a combined PPP method with GPS and GLONASS which is based on using raw observations is proposed, and the positioning results and convergence time have been compared with that of single system. The ionospheric delays and receiver’s Differential Code Bias (DCB) corrections are estimated as unknown parameters in this method. The numerical results show that the combined PPP has not caused significant impacts on the final solutions, but it greatly improved Position Dilution of Precision (PDOP) and convergence speed and enhanced the reliability of the solution. Meanwhile, the convergence speed is greatly influenced by the receiver’s DCB, positioning results in horizontal which are better than 10 cm can be realized within 10 min. In addition, the ionosphere and DCB products can be provided with high precision.     

Calibration of Envisat radar altimeter over Lake Issykkul

This study presents the results of calibration/validation (C/V) of Envisat satellite radar altimeter over Lake Issykkul located in Kyrgyzstan, which was chosen as a dedicated radar altimetry C/V site in 2004. The objectives are to estimate the absolute altimeter bias of Envisat and its orbit based on cross-over analysis with TOPEX/Poseidon (T/P), Jason-1 and Jason-2 over the ocean. We have used a new method of GPS data processing in a kinematic mode, developed at the Groupe de Recherche de Geodesie Spatiale (GRGS), which allows us to calculate the position of the GPS antenna without needing a GPS reference station. The C/V is conducted using various equipments: a local GPS network, a moving GPS antenna along the satellites tracks over Lake Issykkul, In Situ level gauges and weather stations. The absolute bias obtained for Envisat from field campaigns conducted in 2009 and 2010 is between 62.1 and 63.4 ± 3.7 cm, using the Ice-1 retracking algorithm, and between 46.9 and 51.2 cm with the ocean retracking algorithm. These results differ by about 10 cm from previous studies, principally due to improvement of the C/V procedure. Apart from the new algorithm for GPS data processing and the orbit error reduction, more attention has been paid to the GPS antenna height calculation, and we have reduced the errors induced by seiche over Lake Issykkul. This has been assured using cruise data along the Envisat satellite track at the exact date of the pass of the satellite for the two campaigns. The calculation of the Envisat radar altimeter bias with respect to the GPS levelling is essential to allow the continuity of multi-mission data on the same orbit, with the expected launch of SARAL/Altika mission in 2012. Implications for hydrology in particular, will be to produce long term homogeneous and reliable time series of lake levels worldwide.     

Validation of space-born Moderate Resolution Imaging Spectroradiometer remote sensors aerosol products using application of ground-based Multi-wavelength Radiometer

The measurements of aerosol optical properties were carried out during April 2006 to March 2011 over Mohal (31.9°N, 77.12°E) in the northwestern Indian Himalaya, using the application of ground-based Multi-wavelength Radiometer (MWR) and space-born Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensors. The average (±standard deviation) values of aerosol optical depth (AOD) at 500 nm, Ångström exponent and turbidity coefficient during the entire measurement period were 0.25 ± 0.09, 1.15 ± 0.42 and 0.12 ± 0.06 respectively. About 86% AOD values retrieved from MODIS remote sensor were found within an uncertainty limit (Δτ_pλ = ±0.05 ± 0.15τ_pλ). In general, the MWR derived AOD values were higher than that of MODIS retrieval with absolute difference ∼0.02. During the entire period of measurement space-born MODIS remote sensor and ground-based MWR observation showed good correspondence with significant correlation coefficient ∼0.78 and root mean square difference ∼0.06. For daily observations the relative difference between these two estimates stood less than 9%. However, satellite-based and ground-based observation showed good correspondence, but further efforts still needed to eliminate systematic errors in the existing MODIS algorithm.     

Effects of physical correlations on long-distance GPS positioning and zenith tropospheric delay estimates

The global positioning system (GPS) has become an essential tool for the high precision navigation and positioning. The quality of GPS positioning results mainly depends on the model’s formulations regarding GPS observations, including both a functional model, which describes the mathematical relationships between the GPS measurements and unknown parameters, and a stochastic model, which reflects the physical properties of the measurements. Over the past two decades, the functional models for GPS measurements have been investigated in considerable detail. However, the stochastic models of GPS observation data are simplified, assuming that all the GPS measurements have the same variance and are statistically independent. Such assumptions are unrealistic. Although a few studies of GPS stochastic models were performed, they are restricted to short baselines and short time session lengths. In this paper, the stochastic modeling for GPS long-baseline and zenith tropospheric delay (ZTD) estimates with a 24-h session is investigated using the residual-based and standard stochastic models. Results show that using the different stochastic modelling methods, the total differences can reach as much as 3–6 mm in the baseline component, especially in the height component, and 10 mm in the ZTD estimation. Any misspecification in the stochastic models will result in unreliable GPS baseline and ZTD estimations. Using the residual-based stochastic model, not only the precision of GPS baseline and ZTD estimation is obviously improved, but also the baseline and ZTD estimations are closer to the reference value.     

Optimal combination of InSAR and GPS for measuring interseismic crustal deformation

High spatial resolution measurements of interseismic deformation along major faults are critical for understanding the earthquake cycle and for assessing earthquake hazard. We propose a new remove/filter/restore technique to optimally combine GPS and InSAR data to measure interseismic crustal deformation, considering the spacing of GPS stations in California and the characteristics of interseismic signal and noise using InSAR. To constrain the longer wavelengths (>40 km) we use GPS measurements, combined with a dislocation model, and for the shorter wavelength information we rely on InSAR measurements. Expanding the standard techniques, which use a planar ramp to remove long wavelength error, we use a Gaussian filter technique. Our method has the advantage of increasing the signal-to-noise ratio, controlling the variance of atmosphere error, and being isotropic. Our theoretical analysis indicates this technique can improve the signal-to-noise ratio by up to 20%. We test this method along three segments of the San Andreas Fault (Southern section near Salton Sea, Creeping section near Parkfield and Mojave/Big Bend section near Los Angeles), and find improvements of 26%, 11% and 8% in these areas, respectively. Our data shows a zone of uplift to the west of the Creeping section of the San Andreas Fault and an area of subsidence near the city of Lancaster. This work suggests that after only 5 years of data collection, ALOS interferograms will provide a major improvement in measuring details of interseismic deformation.     

Measuring atmospheric density using GPS–LEO tracking data

We present a method to estimate the total neutral atmospheric density from precise orbit determination of Low Earth Orbit (LEO) satellites. We derive the total atmospheric density by determining the drag force acting on the LEOs through centimeter-level reduced-dynamic precise orbit determination (POD) using onboard Global Positioning System (GPS) tracking data. The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000. We apply the method to GPS tracking data from CHAMP, GRACE, SAC-C, Jason-2, TerraSAR-X and COSMIC satellites, spanning 12 years (2001–2012) and covering orbital heights from 400 km to 1300 km. Errors in the estimates, including those introduced by deficiencies in other modeled forces (such as solar radiation pressure and Earth radiation pressure), are evaluated and the signal and noise levels for each satellite are analyzed. The estimated density data from CHAMP, GRACE, SAC-C and TerraSAR-X are identified as having high signal and low noise levels. These data all have high correlations with anominal atmospheric density model and show common features in relative residuals with respect to the nominal model in related parameter space. On the contrary, the estimated density data from COSMIC and Jason-2 show errors larger than the actual signal at corresponding altitudes thus having little practical value for this study. The results demonstrate that this method is applicable to data from a variety of missions and can provide useful total neutral density measurements for atmospheric study up to altitude as high as 715 km, with precision and resolution between those derived from traditional special orbital perturbation analysis and those obtained from onboard accelerometers.     

GPS total electron content and surface latent heat flux variations before the 11 March 2011 M9.0 Sendai earthquake

The present paper describes the variations of the GPS total electron content (TEC) from the International GNSS service network and surface latent heat flux (SLHF) from the Scientific Computing Division of the National Center for Atmospheric Research (NCAR) before the 11 March 2011 M9.0 Sendai earthquake, respectively. The analysis shows pronounced enhancements in the GPS TEC and SLHF a few days prior to the earthquake event. The maximum increase in the GPS TEC was about 30 TECu with an extended spatial distribution on a geomagnetically quiet day (Dst ? −20 nT, between two moderate geomagnetic storms), 8 March, 3 days prior to the earthquake. This giant positive disturbance was possibly associated with the impending disastrous earthquake and contributed from the enhanced solar radiation. Moreover, there were several anomalous regions of SLHF on the global map, but an area of enhanced SLHF very close to the epicenter. The purpose of this paper is to report the existence of the changes in surface and ionosphere, and show the potential application of multi-source data to identify seismic precursors.     

The effect of geocenter motion on Jason-2 orbits and the mean sea level

We compute a series of Jason-2 GPS and SLR/DORIS-based orbits using ITRF2005 and the std0905 standards ( Lemoine et al., 2010). Our GPS and SLR/DORIS orbit data sets span a period of 2 years from cycle 3 (July 2008) to cycle 74 (July 2010). We extract the Jason-2 orbit frame translational parameters per cycle by the means of a Helmert transformation between a set of reference orbits and a set of test orbits. We compare the annual terms of these time-series to the annual terms of two different geocenter motion models where biases and trends have been removed. Subsequently, we include the annual terms of the modeled geocenter motion as a degree-1 loading displacement correction to the GPS and SLR/DORIS tracking network of the POD process. Although the annual geocenter motion correction would reflect a stationary signal in time, under ideal conditions, the whole geocenter motion is a non-stationary process that includes secular trends. Our results suggest that our GSFC Jason-2 GPS-based orbits are closely tied to the center of mass (CM) of the Earth consistent with our current force modeling, whereas GSFC’s SLR/DORIS-based orbits are tied to the origin of ITRF2005, which is the center of figure (CF) for sub-secular scales. We quantify the GPS and SLR/DORIS orbit centering and how this impacts the orbit radial error over the globe, which is assimilated into mean sea level (MSL) error, from the omission of the annual term of the geocenter correction. We find that for the SLR/DORIS std0905 orbits, currently used by the oceanographic community, only the negligence of the annual term of the geocenter motion correction results in a – 4.67 ± 3.40 mm error in the Z-component of the orbit frame which creates 1.06 ± 2.66 mm of systematic error in the MSL estimates, mainly due to the uneven distribution of the oceans between the North and South hemisphere.     

Assessment of precision in ionospheric electron density profiles retrieved by GPS radio occultations

The Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) is a six satellite radio occultation mission that was launched in April 2006. The close proximity of these satellites during some months after launch provides a unique opportunity to evaluate the precision of Global Positioning System (GPS) radio occultation (RO) retrievals of ionospheric electron density from nearly collocated and simultaneous observations. RO data from 30 consecutive days during July and August 2006 are divided into ten groups in terms of daytime or nighttime and latitude. In all cases, the best precision values (about 1%) are found at the F peak height and they slightly degrade upwards. For all daytime groups, it is seen that electron density profiles above about 120 km height exhibit a substantial improvement in precision. Nighttime groups are rather diverse: in particular, the precision becomes better than 10% above different levels between 120 and 200 km height. Our overall results show that up to 100–200 km (depending on each group), the uncertainty associated with the precision is in the order of the measured electron density values. Even worse, the retrieved values tend sometimes to be negative. Although we cannot rely directly on electron density values at these altitudes, the shape of the profiles could be indicative of some ionospheric features (e.g. waves and sporadic E layers). Above 200 km, the profiles of precision are qualitatively quite independent from daytime or latitude. From all the nearly collocated pairs studied, only 49 exhibited a difference between line of sight angles of both RO at the F peak height larger than 10°. After analyzing them we find no clear indications of a significant representativeness error in electron density profiles due to the spherical assumption above 120 km height. Differences in precision between setting and rising GPS RO may be attributed to the modification of the processing algorithms applied to rising cases during the initial period of the COSMIC mission.     

Estimation and analysis of GPS receiver differential code biases using KGN in Korean Peninsula

The total electron content (TEC) estimation by the Global Positioning System (GPS) can be seriously affected by the differential code biases (DCB), referred to as inter-frequency biases (IFB), of the satellite and receiver so that an accuracy of GPS–TEC value is dependent on the error of DCBs estimation. In this paper, we proposed the singular value decomposition (SVD) method to estimate the DCB of GPS satellites and receivers using the Korean GPS network (KGN) in South Korea. The receiver DCBs of about 49 GPS reference stations in KGN were determined for the accurate estimation of the regional ionospheric TEC. They obtained from the daily solution have large biases ranging from +5 to +27 ns for geomagnetic quiet days. The receiver DCB of SUWN reference station was compared with the estimates of IGS and JPL global ionosphere map (GIM). The results have shown comparatively good agreement at the level within 0.2 ns. After correction of receiver DCBs and knowing the satellite DCBs, the comparison between the behavior of the estimated TEC and that of GIMs was performed for consecutive three days. We showed that there is a good agreement between KASI model and GIMs.