Uniform expression of variogram nested model and parameter estimation in spatial prediction of soil properties

According to the situation that the current theoretical variogram parameters estimation of the Geostatistics was mostly concentrated in single model parameter estimation, and was short of multi-scale nested model parameters estimation, a unified superimposed expression in computer was put forward based on characteristics of the nested multi-scale model. The model type and range of parameters were determined with the empirical semi-variance plot. Then parameters with genetic algorithm were estimated and the application software was developed using Matlab R2010a, and finally, the software was compared with the current popular statistical software by taking the soil nutrients (organic matter and potassium) as examples. The results showed that this method surpassed the traditional method in accuracy of the theoretical model parameters estimation(compared with R2, increased by 6.32% and 83.47% respectively), and the accuracy of the results of Kriging interpolation in later period was much better than that of the traditional ones, which proved that the method proposed in this paper had advantages in both accuracy and the support of nested structure.