Refining gravity anomaly data of coastal areas by combining XGM2019e-2159 and SRTM/GEBCO_2024 residual terrain model with forward modeling method

Liu, Yixiang; Guo, Jinyun; Guan, Bin; Bian, Shaofeng; Sun, Heping; Liu, Xin

doi:10.5194/gmd-19-3361-2026

Articles | Volume 19, issue 8

https://doi.org/10.5194/gmd-19-3361-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-3361-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 8

Model experiment description paper

|

27 Apr 2026

Model experiment description paper |

| 27 Apr 2026

Refining gravity anomaly data of coastal areas by combining XGM2019e-2159 and SRTM/GEBCO_2024 residual terrain model with forward modeling method

Yixiang Liu, Jinyun Guo, Bin Guan, Shaofeng Bian, Heping Sun, and Xin Liu

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Cited articles

Andersen, O. B., Knudsen, P., and Berry, P. A.: The DNSC08GRA global marine gravity field from double retracked satellite altimetry, J. Geodesy, 84, 191–199, https://doi.org/10.1007/s00190-009-0355-9, 2010.

Claessens, S. J.: Evaluation of gravity and altimetry data in Australian coastal regions, in: Geodesy for Planet Earth: Proceedings of the 2009 IAG Symposium, Buenos Aires, Argentina, 31 August–4 September 2009, edited by: Kenyon, S., Pacino, M., and Marti, U., Springer, Berlin, 435–442, https://doi.org/10.1007/978-3-642-20338-1_52, 2012.

Dubey, C. P. and Roy, A.: Joint inversion of gravity and gravity gradient and its application to mineral exploration, J. Ind. Geophys. Union, 27, 1–18, 2023.

Forsberg, R.: A study of terrain reductions, density anomalies and geophysical inversion methods in gravity field modelling, Report 355, Department of Geodetic Science and Surveying, Ohio State University, Columbus, https://earthsciences.osu.edu/sites/earthsciences.osu.edu/files/report-355.pdf (last access: 21 April 2026)., 1984.

Forsberg, R. and Tscherning, C. C.: The use of height data in gravity field approximation by collocation, J. Geophys. Res., 86, 7843–7854, https://doi.org/10.1029/JB086iB09p07843, 1981.