Abstract
This paper studies the contribution of airborne gravity data to improvement of gravimetric geoid modelling across the mountainous area in Colorado, USA. First, airborne gravity data was processed, filtered, and downward-continued. Then, three gravity anomaly grids were prepared; the first grid only from the terrestrial gravity data, the second grid only from the downward-continued airborne gravity data, and the third grid from combined downward-continued airborne and terrestrial gravity data. Gravimetric geoid models with the three gravity anomaly grids were determined using the least-squares modification of Stokes’ formula with additive corrections (LSMSA) method. The absolute and relative accuracy of the computed gravimetric geoid models was estimated on GNSS/levelling points. Results exhibit the accuracy improved by 1.1 cm or 20% in terms of standard deviation when airborne and terrestrial gravity data was used for geoid computation, compared to the geoid model computed only from terrestrial gravity data. Finally, the spectral analysis of surface gravity anomaly grids and geoid models was performed, which provided insights into specific wavelength bands in which airborne gravity data contributed and improved the power spectrum.
Highlights
The Earth’s gravity field data provide fundamental information for the geoscientific community
The main motivation of this study is to explore the potential of airborne gravity data to improve the accuracy of a regional gravimetric geoid model in a complex and mountainous study area
The principle was similar to the validation of Global gravity field models (GGMs), except that validated values were obtained by interpolating geoid undulations Nginetoid from the grid to the position of each
Summary
The Earth’s gravity field data provide fundamental information for the geoscientific community. Apart from GGMs, which are being improved in terms of accuracy and spatial resolution in recent years due to gravity-dedicated satellite missions, terrestrial (land) gravity is the most widely used data type in geoid modelling. It is sufficiently accurate and reliable, but may be time-consuming and laborious for collection. Its wider usage began in the early 1990s due to the full operational capability of the Global Positioning System (GPS) and the implementation of carrier-phase differential GPS (DGPS) techniques This allowed more accurate determination of velocity and acceleration of an airplane, which consequentially enabled the reduction of the
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