scholarly journals Multi-quadric collocation model of horizontal crustal movement

Solid Earth ◽  
2016 ◽  
Vol 7 (3) ◽  
pp. 817-825
Author(s):  
Gang Chen ◽  
Anmin Zeng ◽  
Feng Ming ◽  
Yifan Jing

Abstract. To establish the horizontal crustal movement velocity field of the Chinese mainland, a Hardy multi-quadric fitting model and collocation are usually used. However, the kernel function, nodes, and smoothing factor are difficult to determine in the Hardy function interpolation. Furthermore, the covariance function of the stochastic signal must be carefully constructed in the collocation model, which is not trivial. In this paper, a new combined estimation method for establishing the velocity field, based on collocation and multi-quadric equation interpolation, is presented. The crustal movement estimation simultaneously takes into consideration an Euler vector as the crustal movement trend and the local distortions as the stochastic signals, and a kernel function of the multi-quadric fitting model substitutes for the covariance function of collocation. The velocities of a set of 1070 reference stations were obtained from the Crustal Movement Observation Network of China, and the corresponding velocity field was established using the new combined estimation method. A total of 85 reference stations were used as checkpoints, and the precision in the north and east component was 1.25 and 0.80 mm yr−1, respectively. The result obtained by the new method corresponds with the collocation method and multi-quadric interpolation without requiring the covariance equation for the signals.

2015 ◽  
Vol 7 (4) ◽  
pp. 3359-3382
Author(s):  
G. Chen ◽  
A. M. Zeng ◽  
F. Ming ◽  
Y. F. Jing

Abstract. To establish the horizontal crustal movement velocity field of the Chinese mainland, a Hardy multi-quadric fitting model and collocation are usually used, but the kernel function, nodes, and smoothing factor are difficult to determine in the Hardy function interpolation, and in the collocation model the covariance function of the stochastic signal must be carefully constructed. In this paper, a new combined estimation method for establishing the velocity field, based on collocation and multi-quadric equation interpolation, is presented. The crustal movement estimation simultaneously takes into consideration an Euler vector as the crustal movement trend and the local distortions as the stochastic signals, and a kernel function of the multi-quadric fitting model substitutes for the covariance function of collocation. The velocities of a set of 1070 reference stations were obtained from the Crustal Movement Observation Network of China (CMONOC), and the corresponding velocity field established using the new combined estimation method. A total of 85 reference stations were used as check points, and the precision in the north and east directions was 1.25 and 0.80 mm yr−1, respectively. The result obtained by the new method corresponds with the collocation method and multi-quadric interpolation without requiring the covariance equation for the signals.


2021 ◽  
Vol 80 (6) ◽  
Author(s):  
Rong He ◽  
Tingye Tao ◽  
Fei Gao ◽  
Yongchao Zhu ◽  
Xiaochuan Qu ◽  
...  

2019 ◽  
Vol 11 (22) ◽  
pp. 2692 ◽  
Author(s):  
Wei Qu ◽  
Hailu Chen ◽  
Shichuan Liang ◽  
Qin Zhang ◽  
Lihua Zhao ◽  
...  

High-precision, high-reliability, and high-density GPS crustal velocity are extremely important requirements for geodynamic analysis. The least-squares collocation algorithm (LSC) has unique advantages over crustal movement models to overcome observation errors in GPS data and the sparseness and poor geometric distribution in GPS observations. However, traditional LSC algorithms often encounter negative covariance statistics, and thus, calculating statistical Gaussian covariance function based on the selected distance interval leads to inaccurate estimation of the correlation between the random signals. An unreliable Gaussian statistical covariance function also leads to inconsistency in observation noise and signal variance. In this study, we present an improved LSC algorithm that takes into account the combination of distance scale factor and adaptive adjustment to overcome these problems. The rationality and practicability of the new algorithm was verified by using GPS observations. Results show that the new algorithm introduces the distance scale factor, which effectively weakens the influence of systematic errors by improving the function model. The new algorithm can better reflect the characteristics of GPS crustal movement, which can provide valuable basic data for use in the analysis of regional tectonic dynamics using GPS observations.


2005 ◽  
Vol 50 (9) ◽  
pp. 939-941 ◽  
Author(s):  
Niu Zhijun ◽  
Wang Min ◽  
Sun Hanrong ◽  
Sun Jianzhong ◽  
You Xinzhao ◽  
...  

2010 ◽  
Vol 24 (8) ◽  
pp. 1737-1741 ◽  
Author(s):  
Dong Hoon Kim ◽  
Sungwook Yang ◽  
Dong-Ik Cheon ◽  
Sangchul Lee ◽  
Hwa-Suk Oh

2004 ◽  
Vol 17 (3) ◽  
pp. 282-286 ◽  
Author(s):  
Wang-qiang Dai ◽  
Jun Ren ◽  
Xiao-mao Zhao ◽  
Hui-cheng Shao ◽  
Gui-zhi Zhu

Sign in / Sign up

Export Citation Format

Share Document