Startseite Technik Analysis of different combinations of gravity data types in gravimetric geoid determination over Bali
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Analysis of different combinations of gravity data types in gravimetric geoid determination over Bali

  • Zahroh Arsy Udama , Sten Claessens , Ira Mutiara Anjasmara EMAIL logo und Agustina Nur Syafarianty
Veröffentlicht/Copyright: 8. November 2023
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

Following the Regulation of the Head of the Geospatial Information Agency (BIG) No. 13 of 2021, geoid is used as the Vertical Geospatial Reference System in Indonesia. Applications using the geoid as an ideal reference require a much higher accuracy and resolution than the geoid obtained from models derived solely from satellite data. The Indonesian Geospatial Information Agency considers the geoid ideal if it has reached an accuracy of better than 15 cm. Recent studies have combined satellite and other gravimetric data to produce a combined geoid model with increased resolution. Gravimetric data obtained from measurements close to the Earth’s surface, such as airborne and terrestrial gravity data, are particularly attractive because the high-frequency portion of the signal is more apparent and can contribute to the medium to high frequencies of the gravity field. This study models the geoid over Bali Island by combining satellite, airborne and terrestrial gravity data. Calculations were performed using Least Square Collocation (LSC) and Remove-Compute-Restore (RCR) techniques. The gravimetric geoid model was tested against the geometric geoid profile calculated from a GNSS/Levelling survey. The geoid, calculated by combining the GOCO06S satellite gravity model, the GGMplus gravity model and airborne gravity data at an average flight altitude of 4100 m produces a standard deviation of 14.46 cm along the 125 km validation path. After also adding terrestrial gravity data, the standard deviation increased to 16.37 cm. By comparison, the results of the validation of the geoid model from GOCO06S and INAGEOIDV2 with geometric geoids have standard deviation values of 79.56 cm and 16.40 cm, respectively. However, the results of the statistical tests are strongly influenced by the data quality used as validation, in this case, GNSS/Levelling. It is shown that the GNSS/Levelling data over Bali contains significant errors, which have been reduced based on an analysis of geometric vertical deflections. A geometric geoid profile with higher accuracy is required to test the accuracy of the gravimetric geoid models more reliably.


Corresponding author: Ira Mutiara Anjasmara, Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia, E-mail:

Acknowledgment

The authors thank the Center for Geodesy and Geodynamics Control Network of the Geospatial Information Agency of Indonesia (BIG) for providing data and information. This research is supported by the Geodesy and Geodynamics Laboratory, Department of Geomatics Engineering, Institut Teknologi Sepuluh November, and the School of Earth and Planetary Sciences, Curtin University. Author I.M. Anjasmara was partly funded by the Directorate of Research and Community Service ITS through the Publication Writing-IPR Incentive Program 2023. The authors also thank the three anonymous reviewers whose suggestions helped improve the quality of this manuscript.

  1. Research ethics: Not applicable.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The author(s) state(s) no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: Not applicable.

References

1. Hirt, C, Claessens, S, Fecher, T, Kuhn, M, Pail, R, Rexer, M. New ultrahigh-resolution picture of Earth’s gravity field. Geophys Res Lett 2013;40:4279–83. https://doi.org/10.1002/grl.50838.Suche in Google Scholar

2. Kahar, J, Kasenda, A, Prijatna, K. The Indonesian geoid model 1996. In: Gravity, geoid and Marine geodesy: international symposium no. 117 Tokyo, Japan, September 30–October 5, 1996. Springer; 1997:613–20 pp.10.1007/978-3-662-03482-8_81Suche in Google Scholar

3. Kasenda, A. High precision geoid for modernization of height system in Indonesia. Sydney, Australia: School of Surveying anf Spatial Information System The University of New South Wales; 2009.Suche in Google Scholar

4. Pavlis, NK, Holmes, SA, Kenyon, SC, Factor, JK. The development and evaluation of the Earth gravitational model 2008 (EGM2008). J Geophys Res 2012;117:B04406. https://doi.org/10.1029/2011jb008916.Suche in Google Scholar

5. Badan Informasi Geospasial. Peraturan Kepala Badan Informasi Geospasial (BIG) Nomor 15 Tahun 2013 tentang Sistem Referensi Geospasial Indonesia; 2013. Available from: https://jdihn.go.id/files/217/4647.Suche in Google Scholar

6. Badan Informasi Geospasial. Peraturan Kepala Badan Informasi Geospasial (BIG) Nomor 13 Tahun 2011 tentang Jaring Kontrol Geodesi Indonesia; 2011. Available from: https://jdihn.go.id/files/217/8856.Suche in Google Scholar

7. Heliani, LS. Evaluation of global geopotential model and its application on local geoid modelling of Java Island, Indonesia. In: AIP conference proceedings, vol 1755. AIP Publishing LLC; 2016:100005 p.10.1063/1.4958534Suche in Google Scholar

8. Badan Informasi Geospasial. Peraturan Kepala Badan Informasi Geospasial (BIG) Nomor 13 Tahun 2021 tentang Sistem Referensi Geospasial Indonesia; 2013. Available from: https://jdihn.go.id/files/217/10156412.Suche in Google Scholar

9. Kelompok Kerja Jaring Kontrol Gayaberat dan Geoid. Dokumen Teknis INAGEOID2020 V2.0. Cibinong: BIG Unpublished Legal Report; 2022.Suche in Google Scholar

10. Kvas, A, Brockmann, JM, Krauss, S, Schubert, T, Gruber, T, Meyer, U, et al.. GOCO06s–a satellite-only global gravity field model. Earth Syst Sci Data 2021;13:99–118. https://doi.org/10.5194/essd-13-99-2021.Suche in Google Scholar

11. Susetyo, DB, Lumban-Gaol, YA, Sofian, I. Prototype of national digital elevation model in Indonesia. Int Arch Photogram Rem Sens Spatial Inf Sci 2018;42:609–13. https://doi.org/10.5194/isprs-archives-xlii-4-609-2018.Suche in Google Scholar

12. Forsberg, R, Tscherning, CC. An overview manual for the GRAVSOFT geodetic gravity field modelling programs. Kuala Lumpur: Contract Report for JUPEM; 2008.Suche in Google Scholar

13. Knudsen, P, Bungham, R, Andersen, O, Rio, MH. Enhanced mean dynamic topography and ocean circulation estimation using GOCE preliminary models. In: 4th international GOCE user workshop, vol 696; 2011:29 p.Suche in Google Scholar

14. Tscherning, CC. The GRAVSOFT package for geoid determination. In: Proc 1st IAG continental workshop of the geoid in Europe. Prague; 1992.Suche in Google Scholar

15. Forsberg, R. A study of terrain reductions, density anomalies and geophysical inversion methods in gravity field modelling. Ohio State Univ Columbus Dept Of Geodetic Science and Surveying; 1984, Technical Report.10.21236/ADA150788Suche in Google Scholar

16. Putra, W. Asesmen Kualitas data Gayaberat Airborne, Studi Kasus: Pulau Bali. Unpublished thesis; 2021.Suche in Google Scholar

17. Badan Informasi Geospasial. Peraturan Badan Informasi Geospasial (BIG) Nomor 18 Tahun 2021 tentang Tata Cara Penyelenggaraan Informasi Geospasial; 2011. Available from: https://jdih.big.go.id/produk-hukum/download/59292464.Suche in Google Scholar

18. Sproule, DM, Featherstone, WE, Kirby, JF. Localised gross-error detection in the Australian land gravity database. Explor Geophys 2006;37:175–9. https://doi.org/10.1071/eg06175.Suche in Google Scholar

19. Heiskanen, WA. Determination of the Geoid from Ground Anomalies. Physical Geodesy 1967;8:325–30.Suche in Google Scholar

20. Slater, JA, Malys, S. WGS 84—past, present and future. In: Advances in positioning and reference frames: IAG scientific assembly Rio de Janeiro, Brazil, September 3–9, 1997. Springer; 1998:1–7 pp.10.1007/978-3-662-03714-0_1Suche in Google Scholar

21. Featherstone, WE, Kirby, JF. The reduction of aliasing in gravity observations using digital terrain data and its effect upon geoid computation. Geophys J Int 2000;141:204–12. https://doi.org/10.1046/j.1365-246x.2000.00082.x.Suche in Google Scholar

22. Hwang, C, Hsiao, YY-S, Shih, H-C, Yang, M, Chen, K-H, Forsberg, R, et al.. Geodetic and geophysical results from a Taiwan airborne gravity survey: data reduction and accuracy assessment. J Geophys Res Solid Earth 2007;112:B04407. https://doi.org/10.1029/2005jb004220.Suche in Google Scholar

23. Hwang, C, Hsiao, Y-S, Shih, H-C. Data reduction in scalar airborne gravimetry: theory, software and case study in Taiwan. Comput Geosci 2006;32:1573–84. https://doi.org/10.1016/j.cageo.2006.02.015.Suche in Google Scholar

24. Wessel, P, Smith, WHF, Scharroo, R, Luis, JF, Wobbe, F. GMT 5: a major new release of the Generic Mapping Tools. Trans Am Geophys Union 2013;94:409–10. https://doi.org/10.1002/2013eo450001.Suche in Google Scholar

25. Hwang, C, Parsons, B. Gravity anomalies derived from Seasat, Geosat, ERS-1 and TOPEX/POSEIDON altimetry and ship gravity: a case study over the Reykjanes Ridge. Geophys J Int 1995;122:551–68. https://doi.org/10.1111/j.1365-246x.1995.tb07013.x.Suche in Google Scholar

26. Moritz, H. Advanced physical geodesy. Karlsruhe Wichmann: Tunbridge Wells Kent; 1980.Suche in Google Scholar

27. Willberg, M, Zingerle, P, Pail, R. Residual least-squares collocation: use of covariance matrices from high-resolution global geopotential models. J Geodesy 2019;93:1739–57. https://doi.org/10.1007/s00190-019-01279-1.Suche in Google Scholar

28. Tscherning, CC, Rapp, RH. Closed covariance expressions for gravity anomalies, geoid undulations, and deflections of the vertical implied by anomaly degree variance models. Ohio: Scientific Interim Report Ohio State Univ; 1974.Suche in Google Scholar

29. Sampietro, D, Capponi, M, Mansi, AH, Gatti, A, Marchetti, P, Sansò, F. Space-Wise approach for airborne gravity data modelling. J Geodesy 2017;91:535–45. https://doi.org/10.1007/s00190-016-0981-y.Suche in Google Scholar

30. Burša, M. Report of special commission SC3, Fundamental constants. Boulder, Colorado: 21st General Assembly of the International Association of Geodesy; 1995:2–14 pp.Suche in Google Scholar

31. Smith, DA, Roman, DR. GEOID99 and G99SSS: 1-arc-minute geoid models for the United States. J Geodesy 2001;75:469–90. https://doi.org/10.1007/s001900100200.Suche in Google Scholar

32. Foroughi, I, Tenzer, R. Comparison of different methods for estimating the geoid-to-quasi-geoid separation. Geophys J Int 2017;210:1001–20. https://doi.org/10.1093/gji/ggx221.Suche in Google Scholar

33. Udama, ZA, Anjasmara, IM, Pahlevi, AM, Osman, ASM. Geoid modelling of Kalimantan Island using airborne gravity data and global geoid model (EGM2008). In: IOP conference series: Earth and environmental science, vol 936. IOP Publishing; 2021:012029 p.10.1088/1755-1315/936/1/012029Suche in Google Scholar

34. Zingerle, P, Pail, R, Gruber, T, Oikonomidou, X. The combined global gravity field model XGM2019e. J Geodesy 2020;94:1–12. https://doi.org/10.1007/s00190-020-01398-0.Suche in Google Scholar

35. Miyahara, B, Kodama, T, Kuroishi, Y. Development of new hybrid geoid model for Japan,“GSIGEO2011”. Bulletin of the Geospatial Information Authority of Japan 2014;62:12.Suche in Google Scholar

36. Featherstone, WE. Refinement of gravimetric geoid using GPS and leveling data. J Survey Eng 2000;126:27–56. https://doi.org/10.1061/(asce)0733-9453(2000)126:2(27).10.1061/(ASCE)0733-9453(2000)126:2(27)Suche in Google Scholar

37. Smith, WHF, Wessel, P. Gridding with continuous curvature splines in tension. Geophysics 1990;55:293–305. https://doi.org/10.1190/1.1442837.Suche in Google Scholar

38. Gilardoni, M, Reguzzoni, M, Sampietro, D. A least-squares collocation procedure to merge local geoids with the aid of satellite-only gravity models: the Italian/Swiss geoids case study. Boll Geofis Teor Appl 2013;54:303–19. https://doi.org/10.4430/bgta0111.Suche in Google Scholar

39. Dayoub, N, Edwards, SJ, Moore, P. The Gauss–Listing geopotential value W0 and its rate from altimetric mean sea level and GRACE. J Geodesy 2012;86:681–94. https://doi.org/10.1007/s00190-012-0547-6.Suche in Google Scholar

40. Knudsen, P, Andersen, OB. A global mean ocean circulation estimation using GOCE gravity models—the DTU12MDT mean dynamic topography model. In: 20 years of progress in radar altimetry symposium. European Space Agency; 2012:123 p.Suche in Google Scholar

41. Featherstone, WE, Filmer, MS. The north-south tilt in the Australian Height Datum is explained by the ocean’s mean dynamic topography. J Geophys Res: Oceans 2012;117:C08035. https://doi.org/10.1029/2012jc007974.Suche in Google Scholar

42. Hwang, C, Hsiao, YS. Orthometric corrections from leveling, gravity, density and elevation data: a case study in Taiwan. J Geodesy 2003;77:279–91. https://doi.org/10.1007/s00190-003-0325-6.Suche in Google Scholar

Received: 2023-06-08
Accepted: 2023-10-09
Published Online: 2023-11-08
Published in Print: 2024-07-26

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Original Research Articles
  3. Ionospheric TEC modeling using COSMIC-2 GNSS radio occultation and artificial neural networks over Egypt
  4. Regional GPS orbit determination using code-based pseudorange measurement with residual correction model
  5. Analysis of different combinations of gravity data types in gravimetric geoid determination over Bali
  6. Assessment of satellite images terrestrial surface temperature and WVP using GNSS radio occultation data
  7. GNSS positioning accuracy performance assessments on 1st and 2nd generation SBAS signals in Thailand
  8. Differential synthetic aperture radar (SAR) interferometry for detection land subsidence in Derna City, Libya
  9. Advanced topographic-geodetic surveys and GNSS methodologies in urban planning
  10. Detection of GNSS ionospheric scintillations in multiple directions over a low latitude station
  11. Spatiotemporal postseismic due to the 2018 Lombok earthquake based on insar revealed multi mechanisms with long duration afterslip
  12. Practical implications in the interpolation methods for constructing the regional mean sea surface model in the eastern Mediterranean Sea
  13. Validation of a tailored gravity field model for precise quasigeoid modelling over selected sites in Cameroon and South Africa
  14. Evaluation of ML-based classification algorithms for GNSS signals in ocean environment
  15. Development of a hybrid geoid model using a global gravity field model over Sri Lanka
  16. Implementation of GAGAN augmentation on smart mobile devices and development of a cooperative positioning architecture
  17. On the GPS signal multipath at ASG-EUPOS stations
Heruntergeladen am 17.1.2026 von https://www.degruyterbrill.com/document/doi/10.1515/jag-2023-0042/html
Button zum nach oben scrollen