This study work deals with the determination of the gravimetric geoid model for Kazakhstan by using the KTH-method. A number of data sets were collected for this work, such as the gravity anomalies, high-resolution Digital Elevation Model (DEM), Global Geopotential Models (GGMs) and GPS/Levelling data. These data has been optimally combined through the KTH approach, developed at the Royal Institute of Technology (KTH) in Stockholm. According to this stochastic method, Stokes’ formula is being used with the original surface gravity anomaly, which combine with a GGM yields approximate geoid heights. The corrected geoid heights are then obtained by adding the topographic, downward continuation, atmospheric and ellipsoidal corrections to the approximate geoid heights. To compute the geoid model for Kazakhstan as accurately as possible with available data set different numerical tests have been performed: Choice of the best fit geopotential model in the computation area Investigations for the best choice of the initial condition for determination of the least-squares parameters Selection of the best parametric model for reducing the effect of the systematic error and data inconsistencies between computed geoid heights and GPS/Levelling heights.  Finally, 5'x5' Kazakh gravimetric geoid (KazGM2010) has been modelled.

Iran is one of the most complicated areas in the world from the view of rough topography, tectonic activity, large lateral density and geoidal height variations. The computation of a regional gravimetric geoid model with high accuracy in mountainous regions, especially with sparse data, is a difficult task that needs a special attention to obtain reliable results which can meet the needs of the today geodetic community. In this research different heterogeneous data has been used, which includes gravity anomalies, the high-resolution SRTM Digital Elevation Model (DEM), recently published GRACE Global Geopotential Models (GGMs), geological maps and GPS/levelling data. The above data has been optimally combined through the least-squares modification of Stokes formula with additive corrections. Regarding the data evaluation and refinement, the cross-validation technique has been used for detection of outliers. Also, several GGMs and DEMs are evaluated with GPS/levelling data. The impact of utilizing a high resolution SRTM DEM to improve the accuracy of the geoid model has been studied. Also, a density variation model has been established, and its effect on the accuracy of the geoid was investigated. Thereafter a new height datum for Iran was established based on the corrective surface idea. Finally, it was found that there is a significant correlation between the lateral geoid slope and the tectonic activities in Iran. We show that our hybrid gravimetric geoid model IRG04 agrees considerably better with GPS/levelling than any of the other recent local geoid models in the area. Its RMS fit with GPS/levelling is 27 cm and 3.8 ppm in the absolute and relative senses, respectively. Moreover, the relative accuracy of the IRG04 geoid model is at least 4 times better than any of the previously published global and regional geoid models in the area. Also, the RMS fit of the combined surface model (IRG04C) versus independent precise GPS/levelling is almost 4 times better compared to the original gravimetric geoid model (IRG04). These achievements clearly show the effect of the new gravity database and the SRTM data for the regional geoid determination in Iran based on the least-squares modification of Stokes’ formula. / <p>QC 20100906</p>