Mapping Heavy Metal Content in Soils with Multi-Kernel SVR and LiDAR Derived Data

Abstract

Support vector regression (SVR) is a powerful machine learning technique in the framework of the statistical learning theory; while Kriging is a well-established prediction method traditionally used in the spatial statistics field. However, the two techniques share the same background of reproducing kernel Hilbert space (RKHS).