  Kriging is a widely recognized method for making spatial predictions. On the
sphere, popular methods such as ordinary kriging assume that the spatial
process is intrinsically homogeneous. However, intrinsic homogeneity is too
strict in many cases. This research uses intrinsic random function (IRF) theory
to relax the homogeneity assumption. A key component of modeling IRF processes
is estimating the degree of non-homogeneity. A graphical approach is proposed
to accomplish this estimation. With the ability to estimate non-homogeneity, an
IRF universal kriging procedure can be developed. Results from simulation
studies are provided to demonstrate the advantage of using IRF universal
kriging as opposed to ordinary kriging when the underlying process is not
intrinsically homogeneous.
