A regional approach for high-resolution gravity anomaly recovery from full airborne gravity gradient tensor

Author:

Wu Yihao1ORCID,He Xiufeng1,Shi Hongkai1,Luo Zhicai2,Abulaitijiang Adili3,Wang Haihong4

Affiliation:

1. School of Earth Sciences and Engineering, Hohai University , Nanjing 211100 , China

2. School of Physics, Huazhong University of Science and Technology , Wuhan 430071 , China

3. Institute of Geodesy and Geoinformation, University of Bonn , Bonn 53115 , Germany

4. School of Geodesy and Geomastics, Wuhan University , Wuhan 430079 , China

Abstract

SUMMARY A regional approach is developed for high-resolution gravity anomaly recovery from the full airborne gravity gradient tensor (GGT) based on the radial basis function (RBF) technique. The analytical expressions that link the full GGT to the gravity anomaly based on Poisson wavelets are developed, where the closed formulae of the associated derivatives of Poisson wavelets are deduced. Based on this approach, the gravity anomalies at a mean resolution of ∼0.15 km over the Kauring Test Range in Australia are recovered by using the local airborne GGT. The results show that the solution computed from the vertical component provides the best quality when a single component is used, whereas the model computed from the curvature component performs the worst. Moreover, the incorporation of two components magnifies the gravity anomalies and further improves the fit with the terrestrial and airborne gravity data, compared with the solutions computed from individual components. However, the solutions calculated by additionally merging one or more components provide comparable qualities with the models calculated by fusing two components only. Finally, the solution is computed by merging the full airborne GGT, and the standard deviation of the misfits against the terrestrial gravity data is 0.788 mGal. Further comparisons with the Fourier transformation and equivalent source method demonstrate that the proposed approach has slightly better performance. The proposed method is numerically efficient and offers a better data adaptation, which is useful for high-resolution gravity data recovery in managing huge number of gravity gradient data.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Reference64 articles.

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