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The distribution of spatial variations in soil heavy metal is an important factor upon assessment of soil heavy metal. Reasonable sampling intervals and element attribute value evaluation can improve the accuracy of the evaluation models. Different heavy metal elements have different characteristics in spatial distribution. In this paper spatial variability and structure analysis of statistical technology were applied to the agricultural test plots which consist of cinnamon soil in Binzhou, Shandong. Optimal selection about the model was performed by kriging interpolation method. Then, the reasonable sampling spacing could be determinate well. In this research, by means of the sample testing results on five elements of heavy metals: Pb, Cd, Hg, Cu, Cr, which could reflect the levels of the soil pollution, aforementioned geo-statistical analysis process was done. In the sampling densities among them, chromium was the minimum; Mercury and cadmium were the largest, the rest of the middle. The results indicated that, the Spherical Model was more suitable for fitting description of soil heavy metal space distribution. Soil heavy metal variations were a result of comprehensive external effect of topography and land use, also the effects exhibit different at various scales. Due to pollution source, tillage form and other factors, choosing different sampling spacing for different heavy metal elements were more reasonable.