一种求解地球物理参数各向异性的新方法一单位步长变异增量法

目前在研究地球物理参数的空间变异特性时常常是基于几何各向异性假设,然而实际中几何各向异性假设常常不成立。本文提出了一种求解地球物理参数各向异性的新方法,首先对各方向上的变异值作归一化处理,然后用拟合的方法得到各方向单位步长上的变异性强度,进而实现对全局各向异性的求解。以上海地区合成孔径雷达干涉测量（InSAR）中差分大气延迟样本数据为例,验证了新方法求解各向异性的优越性：新方法的偏差只有6.4%,而基于几何各向异性假设方法的偏差达到了21.2%,而且新方法的运算效率有非常显著的提高。进一步,通过克里金插值交叉验证实验,证明了基于新算法得到的结构函数的插值效果最好,从而从另外一个角度验证了新算法求解的各向异性更准确,更好地表征了区域化变量的空间结构特征。因此,与几何各向异性假设的方法相比,新方法不仅能更准确的描述地球物理参数的各向异性,而且有更高的运算效率,为更准确地估计出所需的地球物理参数奠定了基础。

A novel method for determining the anisotropy of geophysical parameters: unit range variation increment (URVI)

Geometric anisotropy is commonly assumed in the investigation of the spatial variations of geophysical parameters. However, this assumption is not always satisfied in practice. We propose a novel method to determine the anisotropy of geophysical parameters. In the proposed method, the variograms are first normalized in all directions. Then, the normalized samples are fitted by the unit range variation increment（URVI） function to estimate the intensities of the variograms in each direction, from which the anisotropy can be finally determined. The performance of the proposed method is validated using InSAR atmospheric delay measurements over the Shanghai region. The results show that the deviation of the method is 6.4%, and that of the geometric anisotropy-based method is 21.2%. In addition, the computational efficiency of the new method is much higher. Subsequently, the URVI- and the geometric anisotropy-based methods are cross-validated in the cross-validation experiments by using Kriging interpolation. The results demonstrate that the structure functions generated with the proposed method are more accurate and can better refl ect the spatial characteristics of the random fi eld. Therefore, the proposed method, which is more accurate and effi cient to determine the anisotropy than the conventional geometry anisotropy-based method, provides a better foundation to estimate the geophysical parameters of interest.