Qualification and refinement of the gravity database based on cross-validation approach — A case study of Iran

Kiamehr, Ramin

doi:10.1556/ageod.42.2007.3.3

Cited by 13 publications

(11 citation statements)

References 7 publications

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“…The Leaveone-out cross validation (LOOCV) is used in this study to predict new gravity values. A procedure for applying LOOCV has been addressed by Kiamehr (2007). In this study, 389 points were detected as outliers (cf.…”

Section: R a F Tmentioning

confidence: 99%

Implementation of a rigorous least-squares modification of Stokes’ formula to compute a gravimetric geoid model over Saudi Arabia (SAGEO13)

Abdalla

Mogren

2015

Can. J. Earth Sci.

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A gravimetric geoid model (SAGEO13) is computed for the Kingdom of Saudi Arabia using a rigorous stochastic computational method. The computational methodology is based on a combination of least-squares (LS) modification of Stokes’ formula and the additive corrections for topographic, ellipsoidal, atmospheric, and downward continuation effects on the geoid solution. In this study, we used terrestrial gravity data, a digital elevation model (SRTM3), and seven global geopotential models (GGMs) to compute a new geoid model for Saudi Arabia. The least-squares coefficients are derived based on the optimisation of the input modification parameters. The gravimetric solution and its additive corrections are computed based on the optimum LS coefficients. Compared to GPS-levelling data, SAGEO13 shows a fit of 18 cm (RMS) after using a 4-parameter fitting model.

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Section: R a F Tmentioning

confidence: 99%

Implementation of a rigorous least-squares modification of Stokes’ formula to compute a gravimetric geoid model over Saudi Arabia (SAGEO13)

Abdalla

Mogren

2015

Can. J. Earth Sci.

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“…Kiamehr (2007) created a more complete and also refined new gravity database for Iran and all possible outliers were detected and removed from database by using the Least Squares Collocation (LSC) approach. A total number of 26,125 point and mean gravity data were collected from different data sources in order to create gravity database.…”

Section: Terrestrial Gravity Anomaliesmentioning

confidence: 99%

“…A special method was used for the interpolation of free-air gravity anomalies (for more details, see Kiamehr 2007) in order to include the effect of topography in gridding of data. The free-air gravity anomalies are interpolated on a grid with a unit cell size of 80″ × 90″.…”

Section: Terrestrial Gravity Anomaliesmentioning

confidence: 99%

“…Since the publication of the IRG04 gravimetric geoid model (Kiamehr, 2007), the quantity and quality of the terrestrial and altimetric gravity data were increased and high resolution global geopotential model EGM2008 was released. On the other hand, some critical assumptions in determination of geoid model for Iran, encouraged us to compute a quasi-geoid model.…”

Section: Introductionmentioning

confidence: 99%

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The new quasi-geoid model IRQG09 for Iran

Kiamehr

2011

Journal of Applied Geophysics

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“…The discretisation error occurs due to the loss of short wavelength gravity information when estimating the mean gravity anomalies g ∆ from point gravity data. The following technique is proposed to reduce the discretisation error (Kiamehr 2005a). First a topographic correction (e.g., using the RTM method / Forsberg-1984) is made, that results into reduced gravity anomalies, which are assumed to be smoother than the original ones.…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%