Using data of Pb concentrations within soil samples from the Tongling mining district area as an example, Kriging and Sequential Gaussian Simulation were used to determine the local singularity exponent within a dataset with low spatial density sampling. The results indicate that, for the datasets with low spatial density sampling, calculation of a singularity exponent based on Sequential Gaussian Simulation could produce significantly improved results, and therefore improved interpretation, than using the data of raw or Kriged during the identification of anomalies within soil geochemical data.