Application of Density Anomaly Depth Detection Using Gravity Gradient Eigenvectors and Multiscale Analysis Approach

LIU Jinzhao; LIU Lintao; LIANG Xinghui; YE Zhourun; LI Honglei

doi:10.13203/j.whugis20140235

Volume 41 Issue 3

Mar. 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(3): 322-330. > DOI: 10.13203/j.whugis20140235

LIU Jinzhao, LIU Lintao, LIANG Xinghui, YE Zhourun, LI Honglei. Application of Density Anomaly Depth Detection Using Gravity Gradient Eigenvectors and Multiscale Analysis Approach[J]. Geomatics and Information Science of Wuhan University, 2016, 41(3): 322-330. DOI: 10.13203/j.whugis20140235

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Application of Density Anomaly Depth Detection Using Gravity Gradient Eigenvectors and Multiscale Analysis Approach

1.
First Crust Monitoring and Application Center of China Earthquake Administration, Tianjin 300180, China;
2.
State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China

Funds: The National Natural Science Foundation of China, No. 41304023; the National Major Scientific Instruments and Equipment Development Projects,No.2011YQ120045.

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Received Date: April 26, 2015
Published Date: March 04, 2016

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Abstract

Compared with the conventional gravity measurements,gravity gradient measurements reflect the structural characteristics of the underground density anomaly with higher sensitivity and spatial resolution. Airborne and satellite gravity gradient survey systems have been put into use on account of continuous technological innovation, whilst wide range and high precision gravity gradient measurements are available.Therefore, the main challenge is analysis,processing and interpretation of extensive gravity gradient data. This paper addresses depth detection of underground density anomalies based on eigenvectors corresponding to the principle eigenvalue of the gravity gradient. As density anomalies of different buried depths have different wavelengths,we can split the gravity gradient tensor into different frequency bands taking advantage of the multiscale analysis approach, thereby enhancing the detection ability to detect deeper density anomalies.Through the analysis of the synthetic and measured gravity gradient data, our results show that the gravity gradient eigenvector and multiscale analysis approach can effectively determine the depth information of density anomalies. The proposed methos is robust to interference sources and random noise.
- gravity gradient,
- depth detection,
- eigenvector,
- multiscale

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