Integration of satellite geodetic observations for regional geoid modeling using remove‑compute‑restore technique
2021
Advanced satellite geodetic systems have contributed to improving knowledge on changes in global gravity fields in recent years. These systems offer profound opportunities in the determination of a high-precision, high-resolution gravimetric geoid models in data deficient regions. However, due to the absence of research competence in some regions, these conventional datasets have not been implemented to update the obsolete reference frames which have been in use in these regions. This study introduces the well-known Remove-Compute-Restore (RCR) technique in modeling a gravimetric geoid model for a large data deficient region in West Africa (Nigeria) using two sets of long and short wavelength data (a) EGM2008 (long) + Airborne gravimetric observation (AGO) dataset (short) (b) EGM2008 (long) + Terrestrial gravimetric undulation (TGU) dataset (short). This therefore resulted in obtaining two sets of resultant RCR-gravimetric details whose statistics comparative assessments are produced in the body of this work. The RCR-determined gravimetric geoid model showed a strong relationship with the observed terrestrial data. The goodness of fit for the orthometric height correlation between the computed gravimetric geoid and the terrestrial data is 97.87 %. Strong relationships between the computed model and the other height models determined from the primary data are also observed. The difference between the Flury and rummel geoid-based model and the Heiskanen and moritz model in the geoid-quasi geoid separation phase shows the importance of implementing the ‘rigorous modeling technique’ for geoid quasi-geoid separation instead of the approximation method. However, the discrepancy between both models can be overlooked in a case of low accuracy geoidal operations. The RCR-based Fast Fourier Transform (FFT), and the least squares modified stokes (LSMS) was used in the quasi-geoid determination of the study region. Using the 1-parameter fit, the modified Stokes integral (FFT(b)) outperformed the LSMS model with a root mean square (rms) difference of 0.6 cm, while the LSMS outperformed both the unmodified (FFT(a)) and the modified (FFT(b)) Stokes integral using the 4-parameter fit with a rms difference of 0.5 cm. The use of both models in this study created a better perception of the quasi-geoid differential analysis, and a more refined understanding of their interaction with the satellite based quasi geoid.
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