Evaluation and Comparison of the Processing Methods of Airborne Gravimetry Concerning the Errors Effects on Downward Continuation Results: Case Studies in Louisiana (USA) and the Tibetan Plateau (China).
Evaluation and Comparison of the Processing Methods of Airborne Gravimetry Concerning the Errors Effects on Downward Continuation Results: Case Studies in Louisiana (USA) and the Tibetan Plateau (China).
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DOI：
10.3390/s17061205
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发表时间：
2017-05-25
期刊：
影响因子：
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通讯作者：
Xu X
中科院分区：
文献类型：
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作者：
Zhao Q;Strykowski G;Li J;Pan X;Xu X
目前山区重力资料的空白往往由航空重力测量资料填补。由于航空重力仪传感器引起的误差，以及由于恶劣的飞行条件，这种误差不能完全消除。航空重力测量产生的重力扰动的精度在3-5 mgal左右。航空重力测量的一个主要障碍是向下延拓引起的误差。为了改善结果，外部高精度重力信息，从地面数据可以用于高频校正，而卫星信息可以用于低频校正。在向下延拓中，可以利用地表数据来减小系统误差，而正则化方法可以减小随机误差。航空重力测量有时在山区进行，世界上最极端的地区是青藏高原。由于该地区没有高精度的地面重力数据，无法使用上述涉及外部重力数据的误差最小化方法。我们提出了一种结合正则化的半参数向下延拓方法来抑制青藏高原的系统误差效应和随机误差效应，即，而不需要使用外部高精度重力数据。我们使用路易斯安那州的航空重力数据集从美国国家海洋和大气管理局（NOAA）证明了新方法的有效性。此外，对于青藏高原，我们表明，数值试验也成功地进行了使用合成地球重力模型2008（EGM 08）派生的重力数据与合成误差的污染。该方法产生的系统误差估计值与模拟值接近。此外，我们还研究了向下延拓高度与误差效应之间的关系。分析结果表明，所提出的半参数方法结合正则化是有效的，以解决这样的建模问题。
Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3–5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems.