A Comparison of Different Downward Continuation Methods for Airborne Gravity Data

2004 ◽  
Vol 47 (6) ◽  
pp. 1143-1149 ◽  
Author(s):  
Xing-Tao WANG ◽  
Zhe-Ren XIA ◽  
Pan SHI ◽  
Zhong-Miao SUN
2020 ◽  
Author(s):  
Xiaopeng Li ◽  
Jianliang Huang ◽  
Cornelis Slobbe ◽  
Roland Klees ◽  
Martin Willberg ◽  
...  

<p>The topic of downward continuation (DWC) has been studied for many decades without very conclusive answers on how different methods compare with each other. On the other hand, there are vast amounts of airborne gravity data collected by the GRAV-D project at NGS NOAA of the United States and by many other groups around the world. These airborne gravity data are collected on flight lines where the height of the aircraft actually varies significantly, and this causes challenges for users of the data. A downward continued gravity grid either on the topography or on the geoid is still needed for many applications such as improving the resolution of a local geoid model. Four downward continuation methods, i.e., Residual Least Squares Collocation (RLSC), the Inverse Poisson Integral, Truncated Spherical Harmonic Analysis, and Radial Basis Functions (RBF), are tested on both simulated data sets and real GRAV-D airborne gravity data in a previous joint study between NGS NOAA and CGS NRCan. The study group is further expanded by adding the TU Delft group on RBF and the TUM group on RLSC to incorporate more updated knowledge in the theoretical background and more in-depth discussion on the numerical results. A formal study group will be established inside IAG for providing the best answers for downward continuing airborne gravity data for local gravity field improvement. In this presentation, we review and compare the four methods theoretically and numerically. Simulated and real airborne and terrestrial data are used for the numerical comparison over block MS05 of the GRAV-D project in Colorado, USA, where the 1cm geoid experiment was performed by 15 international teams. The conclusion drawn from this study will advance the use of GRAV-D data for the new North American-Pacific Geopotential Datum of 2022 (NAPGD2022).</p>


2018 ◽  
Vol 10 (12) ◽  
pp. 1951 ◽  
Author(s):  
Qilong Zhao ◽  
Xinyu Xu ◽  
Rene Forsberg ◽  
Gabriel Strykowski

An airborne gravity survey was carried out to fill gaps in the gravity data for the mountainous areas of Taiwan. However, the downward continuation error of airborne gravity data is a major issue, especially in regions with complex terrain, such as Taiwan. The root mean square (RMS) of the difference between the downward continuation values and land gravity was approximately 20 mGal. To improve the results of downward continuation we investigated the inverse Poisson’s integral, the semi-parametric method combined with regularization (SPR) and the least-squares collocation (LSC) in this paper. The numerically simulated experiments are conducted in the Tibetan Plateau, which is also a mountainous area. The results show that as a valuable supplement to the inverse Poisson’s integral, the SPR is a useful approach to estimate systematic errors and to suppress random errors. While the LSC approach generates the best results in the Tibetan Plateau in terms of the RMS of the downward continuation errors. Thus, the LSC approach with a terrain correction (TC) is applied to the downward continuation of real airborne gravity data in Taiwan. The statistical results show that the RMS of the differences between the downward continuation values and land gravity data reduced to 11.7 mGal, which shows that an improvement of 40% is obtained.


2010 ◽  
Vol 439-440 ◽  
pp. 674-678
Author(s):  
Yi Cheng ◽  
Jin Luo ◽  
Chun Bo Xiu

Based on the remove-restore technique, the application of the Tikhonov regularization algorithm to reduce the effect of measurement error in the airborne gravity dada in researched. By the experiments of two kinds airborne gravity data, which having constant system error and casual system error, the compare of different downward continuation algorithm is performed. According to the results of simulations, the Tikhonov regularization algorithm can effectively reduce the effect of height and the measurement error in the airborne gravity data downward continuation compared to other algorithm.


Author(s):  
Haipeng Yu ◽  
Guobin Chang ◽  
Nijia Qian ◽  
Shubi Zhang ◽  
Wenyuan Zhang

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