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AFRGDB_V2.0: The Gravity Database for the Geoid Determination in Africa
The available gravity data set for Africa consists of land point gravity data as well as shipborne and altimetry derived gravity anomalies data, but suffers from a lot of significant large gaps. The establishment of the AFRGDB_V2.0 gravity database for Africa has been carried out using a weighted least-squares prediction technique. The land gravity data got the highest precision, while the shipborne and altimetry gravity data got a moderate precision. The data gaps are filled by an underlying grid utilizing the GOCE Dir_R5 model, getting the lowest precision within the prediction technique. The window technique has been used to produce the best reduced anomalies before the interpolation process. The AFRGDB_V2.0 gravity database on a uniform 5′ × 5′ grid has been established by the developed process and has been validated using real data. This validation proved that the established gravity database for Africa has an internal precision of about 5.5 mgal, and an external accuracy of about 7 mgal.
KeywordsAfrica Geoid determination Gravity Least-squares prediction Window technique
This project was supported financially by the Science and Technology Fund (STDF), Egypt, Grant No. 7944. The authors would like to thank Dr. Sylvain Bonvalot, Director of the Bureau Gravimétrique International (BGI), for providing part of the used data set for Africa. The support by the International Association of Geodesy (IAG) and the International Union of Geodesy and Geophysics (IUGG) is kindly acknowledged. The authors would like to thank the editor of the current paper and two anonymous reviewers for their useful comments.
- Abd-Elmotaal HA (2015) Validation of GOCE models in Africa. Newton’s Bull 5:149–162Google Scholar
- Abd-Elmotaal HA, Kühtreiber N (2014) Automated gross error detection technique applied to the gravity database of Africa. In: General Assembly of the European Geosciences Union, Vienna, 27 April–2 May 2014Google Scholar
- Abd-Elmotaal HA, Kühtreiber N (2016) Effect of the curvature parameter on least-squares prediction within poor data coverage: case study for Africa. In: General Assembly of the European Geosciences Union, Vienna, April 17–22, 2016Google Scholar
- Abd-Elmotaal HA, Makhloof A (2013) Gross-errors detection in the shipborne gravity data set for Africa. Geodetic Week, Essen, 8–10 October 2013. www.uni-stuttgart.de/gi/research/Geodaetische_Woche/2013/session02/Abd-Elmotaal-Makhloof.pdf Google Scholar
- Abd-Elmotaal HA, Makhloof A (2014) Combination between altimetry and shipborne gravity data for Africa. In: 3rd International Gravity Field Service (IGFS) General Assembly, Shanghai, 30 June–6 July 2014Google Scholar
- Abd-Elmotaal HA, Seitz K, Kühtreiber N, Heck B (2015) Establishment of the gravity database AFRGDB_V1.0 for the African geoid. In: International association of geodesy symposia, vol 144, pp 131–138. https://doi.org/10.1007/1345_2015_51
- Abd-Elmotaal HA, Makhloof A, Abd-Elbaky M, Ashry M (2017) The African 3″ × 3″ DTM and its validation. In: International association of geodesy symposia. https://doi.org/10.1007/1345_2017_19
- Kraiger G (1988) Influence of the curvature parameter on least-squares prediction. Manuscr Geodaet 13(3):164–171Google Scholar
- Moritz H (1976) Covariance functions in least-squares collocation. Ohio State University, Department of Geodetic Science and Surveying, Rep 240Google Scholar
- Moritz H (1980) Advanced physical geodesy. Wichmann, KarlsruheGoogle Scholar
- Pavlis N, Holmes S, Kenyon S, Factor J (2012) The development and evaluation of the earth gravitational model 2008 (EGM2008). J Geophys Res 117(B04406). https://doi.org/10.1029/2011JB008916