The experimental area was selected in Lingxian County of Shandong Province. Based on the GPS positioning data, soil moisture content, chlorophyll content and wheat dry matter production was measured. Geostatistical analysis was conducted combined with geographical information system (GIS) and the semivariogram models were established. It was found that a spherical model fit semivariogram model of soil moisture content better, and a Gaussian model was the better model for wheat chlorophyll content and dry matter production. The results showed soil moisture content and wheat chlorophyll content had the strong spatial autocorrelation, and the ratio of structural variation was 97.3% and 81.3%. Wheat dry matter production has the medium spatial autocorrelation, and the structural variation was 50%. Block Kriging was applied, and the spatial distributing maps and maps of standard deviation of Kriging estimates were drawn. From the distribution types, it was observed that the Kriging estimates maps of soil moisture content and wheat chlorophyll content had obvious slabby and plaques characteristics while the map of wheat dry matter production had ribbon characteristics.