3D spatial distribution of soil pollutants based on geo-shadowing anisotropic RBF-PCA - Wang, Xiaodong; Liao, Juanhua; Gui, Ren; Shu, Meiting; Liu, Jia; Zhang, Dengke; Zhu, Fei; Li, Qiurong (Frontiers in Earth Science, 2024)
Research on soil contamination has become increasingly important, but the sampling space for pollutants is limited. Thus, the need for three-dimensional (3D) spatial interpolation techniques has been promoted in this area of study. However, the application of traditional interpolation methods is limited in geography, especially in the expression of anisotropy, and it is not associated with geographical properties. To address this issue, we used a test site (a factory in Nanjing) to develop a new research method based on the geographical shading radial basis function (RBF) interpolation method, which considers 3D anisotropy and geographical attribute expression.Drilling and uniform sampling were used to sample the contaminated area at this test site. This approach mainly included the following two steps: (i) An ellipsoid with anisotropic properties was constructed. Thus, the first step was to determine the shape of the ellipsoid using PCA to determine the main orientations and construct a rotational and stretched matrix. The second step was to determine the ellipsoid size by computing the range using the variogram method for orientations. (ii) During field measurement, the geospatial direction influences soil attribute values, so a shadowing calculation method was derived to conduct quadratic weight determination. Then, the weight of the attribute value of known points can be assigned to meet the field conditions. Lastly, the model was evaluated using the root mean square error (RMSE). For the 2D space, the RMSE values of Kriging, RBF, and the proposed method are 6.09, 7.12, and 5.02, respectively.The R 2 values of Kriging, RBF, and the proposed method are 0.871, 0.832, and 0.946, respectively. Furthermore, for the 3D space, the RMSE values of Kriging, RBF, and the proposed method are 2.65, 2.23, and 2.58, respectively. The R 2 values of Kriging, RBF, and the proposed method are 0.934, 0.912, and 0.953, respectively. Moreover, the resulting fitted model was relatively smooth and met experimental needs. Thus, we believe that the interpolation method can be applied as a new method to predict the distribution of soil pollutants.