Accuracy assessment of the PGM17 global geopotential model: a case study of Egypt and Northeast Africa

  • Gomaa M. DawodEmail author
  • Hoda F. Mohamed
  • Essam M. Al-Krargy
Original Paper


Global geopotential models play a fundamental role in height transformation to convert the Global Navigation Satellite Systems (GNSS)-based ellipsoidal heights into orthometric heights in several geosciences applications. The U.S. National Geospatial-Intelligence Agency (NGA) is preparing to release the Earth Geopotential Model 2020 (EGM2020) in the near future. Prior to that official release, two primary geopotential models (PGM17 and PGM18) will be distributed to selective members for assessment in different regions worldwide. Within the activities of that working group, the new PGM17 geopotential model has been obtained and judged over a regional scale in northeast Africa, and over a national basis of Egypt. The assessment has been carried out using terrestrial gravity and GPS/leveling datasets within a GIS environment. The utilized dataset consists of 231 terrestrial gravity points in northeast Africa, 247 measured gravity points in Egypt, and 978 GNSS/leveling stations in Egypt. Three other GGMs have been included in the comparison stage, namely GECO, EIGEN-6C4, and EGM2008. For each model, grids of gravity anomalies and geoidal undulations have been computed and, then, compared against the corresponding values at known terrestrial data. Next, statistical measures of mean, range, and standard deviations of the discrepancies have been analyzed. For northeast Africa area, the accomplished results indicated that the PGM17 attains 100% improvements over the old EGM2008, while the GECO, and EIGEN-6C4 models resulted in improvements of 11%, and 1% respectively. Accordingly, it can be concluded that PGM17 represents the gravitational field over northeast Africa in a more enhanced manner. On a national scale, the GGMs assessment has been performed, over Egypt, in two steps: using gravity data, and using GNSS/leveling data. The findings emphasize that PGM17 noticeably enhance the performance of EGM2008, when compared against terrestrial gravity stations in Egypt, by almost 55%. Furthermore, the assessment over GPS/leveling stations concluded that the overall improvements of PGM17 are approximately 54%. Other GGMs did not produce a comparable improvement level in both case studies. Thus, it can be concluded that PGM17 is significantly precise than the other investigated GGMs in representing the gravitational field over Egypt in particular and northeast Africa in general.


PGM17 GGM Geoid Gravity GNSS Egypt 



The authors acknowledge the truthful cooperation of the U.S. National Geospatial-Intelligence Agency (NGA), the U.S National Geodetic Survey (NGS), and Dr. Srinivas Bettadpur, the head of Center of Space Research, University of Texas at Austin, and the chair of the EGM2020 Evaluation Working Group. Also, the authors express honest gratitude to the International Gravimetric Bureau (BGI) for providing the gravity datasets of Northeast Africa.


  1. Abd-Allah A (2015) Assessment of GOCE models in Egypt, Master thesis, Faculty of engineering, Cairo University, EgyptGoogle Scholar
  2. Abd-Elmotaal H (2015) Egyptian geoid using best estimated response of the Earth’s crust due to the topographic loads. Presented at the International Association of Geodesy Symposium, Switzerland. Google Scholar
  3. Abd-Elmtaal H (2015) Validation of GOCE models in Africa. Newton’s Bulletin No. 5, pp 149–162Google Scholar
  4. Ahmed R, Singh R (2016) Seismic hazard assessment of Syria using seismicity, DEM, slope, active faults and GIS. Remote Sensing Applications: Society and Environment (RSASE). CrossRefGoogle Scholar
  5. Al-Karagy E, Doma M, Dawod G (2014) Towards an accurate discrimination of the local geoid model in Egypt using GPS/levelling data: A case study at Rosetta area. The International Journal of Innovative Science and Modern Engineering (IJISME) 2(11):10–15Google Scholar
  6. Al-Krargy E (2016) Development of a national geoid for Egypt using recent surveying data, PhD dissertation, Faculty of Engineering, Minufiya university, EgyptGoogle Scholar
  7. Al-Krargy E, Hosny M, Dawod G (2015) Investigating the precision of recent global geoid models and global digital elevation models for geoid modelling in Egypt, Regional Conference on Surveying and Development, Sharm El-Sheikh, Egypt, Oct. 3–6Google Scholar
  8. Alnaggar D (1986) Determination of the geoid in Egypt using heterogeneous geodetic data, PhD dissertation, Faculty of Engineering, Cairo University, EgyptGoogle Scholar
  9. Ashry M (2016) Towards optimal combination of gravity field wavelengths in geoid determination for Egypt, Master thesis, Faculty of engineering, Minia university, EgyptGoogle Scholar
  10. Barzaghi R, Carrion D, Pepe M, Prezioso G (2016) Computing the deflection of the vertical for improving aerial surveys: a comparison between EGM2008 and ITALGEO05 estimates. Sensors 16. CrossRefGoogle Scholar
  11. Berber M, Wright W (2016) Online kinematic GNSS data processing for small hydrographic surveys. Ocean Eng 112:335–339CrossRefGoogle Scholar
  12. BGI (International Gravimetric Bureau) (2018) Accessed Jan. 2018
  13. Casula G (2016) Geodynamics of the Calabrian Arc area (Italy) inferred from a dense GNSS network observations. Geodesy and Geodynamics 7(1):76–86. CrossRefGoogle Scholar
  14. Dawod G (1998) A national gravity standardization network for Egypt. PhD dissertation, Faculty of Engineering at Shoubra, Zagazig University, EgyptGoogle Scholar
  15. Dawod G, Hosny M (2017) Toward a centimeter-geoid model for engineering surveying in Egypt: status and undergoing activities. J Sci Eng Res 4(10):312–319Google Scholar
  16. Dawod G, Mandoer M (2016) Optimum sites for solar energy harvesting in Egypt based on multi-criteria GIS, the first Future University international conference on new energy and environmental engineering, April 11–14, Cairo, Egypt, pp 450–456Google Scholar
  17. Dawod G, Mohamed H, Ismail S (2010) Evaluation and adaptation of the EGM2008 geopotential model along the northern Nile Valley, Egypt: case study, ASCE. J Surv Eng, V 136(1):36–40CrossRefGoogle Scholar
  18. Deng X, Hua X, You Y (2013) Transfer of height datum across seas using GPS leveling, gravimetric geoid and corrections based on a polynomial surface. Comput Geosci 51:135–142CrossRefGoogle Scholar
  19. El-Ashquer M (2016) An improved hybrid local geoid model for Egypt, PhD dissertation, Faculty of Engineering, Zagazig University, EgyptGoogle Scholar
  20. Fazilova D (2017) The review and development of a modern GNSS network and datum in Uzbekistan. Geodesy and Geodynamics 8(2):187–192. CrossRefGoogle Scholar
  21. Förste C, Bruinsma S, Abrikosov O, Lemoine J, Marty J, Charles F, Frank B, Barthelmes F, Biancale R (2014) EIGEN-6C4: the latest combined global gravity field model including GOCE data up to degree and order 2190 of GFZ Potsdam and GRGS Toulouse, presented in the 5th GOCE user workshop, Paris, France, Nov. 25-28.
  22. Ghoniem I, Mousa A, El-Fiky G (2017) Distribution of the GNSS-LEO occultation events over Egypt. NRIAG J Astron Geophys 6:97–103. CrossRefGoogle Scholar
  23. Gilardoni M, Reguzzoni M, Sampietro D (2016) GECO: a global gravity model by locally combining GOCE data and EGM2008. Stud Geophys Geod 60:228–247CrossRefGoogle Scholar
  24. Godah W, Krynski J (2013) Evaluation of recent GOCE geopotential models over the area of Poland. Acta Geodyn Geomater 10(3):379–386CrossRefGoogle Scholar
  25. Gomez M, Perdomo R, Cogliano D (2017) Validation of recent geopotential models in Tierra Del Fuego. Acta Geophys 65:931–943CrossRefGoogle Scholar
  26. Hassouna R, Asal F (2016) Using GIS-based digital raster analysis for improving harmonic modelsderived geoidal heights. Appl Geomat 8:151–162. CrossRefGoogle Scholar
  27. Hofmann-Wellenhof B, Moritz H (2005) Physical geodesy. SpringerWien, New YorkGoogle Scholar
  28. Huang Q, Wangm J, Li M, Fei M, Dong J (2017) Modeling the influence of urbanization on urban pluvial flooding: a scenario-based case study in Shanghai, China. Nat Hazards 87:1035–1055CrossRefGoogle Scholar
  29. ICGEM (The International Center for Global Earth Model) (2018) Accessed Jun. 2018
  30. Karpik A, Kanushin V, Ganagina I, Goldobin D, Kosarev N, Kosareva A (2016) Evaluation of recent Earth’s global gravity field models with terrestrial gravity data. Contributions to Geophysics and Geodesy 46(1):1–11. CrossRefGoogle Scholar
  31. Kaya E, Agca M, Adiguzel F, Cetin M (2018). Spatial data analysis with R programming for environment. Journal of Human and Ecological Risk Assessment.
  32. Li H, Fang J (2017) Crustal and upper mantle density structure beneath the Qinghai-Tibet plateau and surrounding areas derived from EGM2008 geoid anomalies. ISPRS Int J Geo-Inf 6(4). CrossRefGoogle Scholar
  33. Mahapatra M, Ratheesh R, Rajawat A (2017) Storm surge vulnerability assessment of Saurashtra coast, Gujarat, using GIS techniques. Nat Hazards 86:821–831CrossRefGoogle Scholar
  34. Mahmoud S (2012) Assessment of the gravitational global models in Egypt, Master thesis, Al-Azhar University, Cairo, EgyptGoogle Scholar
  35. Mohamed A, Radwan A, Sharaf M, Hamimi Z, Hegazy E, Aly N, Gomaa M (2016) Evaluation of the deformation parameters of the northern part of Egypt using global navigation satellite system (GNSS). NRIAG J Astron Geophys 5:65–75CrossRefGoogle Scholar
  36. Odera P, Fukuda Y (2017) Evaluation of GOCE-based global gravity field models over Japan after the full mission using free-air gravity anomalies and geoid undulations. Earth Planets Space 69.
  37. Pavlis NK, Holmes SA, Kenyon SC, Factor JK (2008) An earth gravitational model to degree 2160: EGM2008, presented in the EGU general assembly, Vienna, Austria, April 13-18Google Scholar
  38. QZSS (2018) Accessed June 19, 2018
  39. Rabiu B (2015) State of GNSS in Africa: applications, observational infrastructures, research implications and prospects, presented in the space weather workshop, April 13–17, Boulder, Colorado, USAGoogle Scholar
  40. Sreejith K, Rajesh S, Majumdar T, Rao G, Radhakrishna M, Krishna K, Rajawat A (2013) High-resolution residual geoid and gravity anomaly data of the northern Indian Ocean - an input to geological understanding. J Asian Earth Sci 62:616–626CrossRefGoogle Scholar
  41. Srivastava P, Singh R (2016) GIS based integrated modelling framework for agricultural canal system simulation and management in Indo-Gangetic plains of India. Agric Water Manag 163:37–47CrossRefGoogle Scholar
  42. Stal C, Poppe H, Vandenbulcke A, Wulf A (2016) Study of post-processed GNSS measurements for tidal analysis in the Belgian North Sea. Ocean Eng 118:165–172CrossRefGoogle Scholar
  43. Wu Q, Kang J, Li S, Zhen J, Li H (2015) GNSS positioning by CORS and EGM2008 in Jilin province, China. Sensors 15:30419–30428. CrossRefGoogle Scholar
  44. Yakubu C, Ferreira V, Asante C (2017) Towards the selection of an optimal global geopotential model for the computation of the long-wavelength contribution: a case study of Ghana. Geosciences 7:113. CrossRefGoogle Scholar
  45. Yılmaz M, Turgut B, Güllü M, Yılmaz I (2017) The evaluation of high-degree geopotential models for regional geoid determination in Turkey. AKÜ J Sci Eng (17):147–153. CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  • Gomaa M. Dawod
    • 1
    Email author
  • Hoda F. Mohamed
    • 1
  • Essam M. Al-Krargy
    • 1
  1. 1.Survey Research InstituteNational Water Research CenterGizaEgypt

Personalised recommendations