Spatial Variability Of Soil In Grassland Base On Fractal Geostatistics Theory

Pattern of spatial variability and the problem of scale effect is a hot point in the forefront of the scientific development. Geostatistics (GS) is recognized as an advanced science which can reveal the variability of the space variables. However, when many researchers definite the advantages of the GS, they also discovered some of the disadvantages. For example, it can characterize the structure of the random variables. But from the view of mathematical statistics, it can not revealed strictly which from the physical or the regulation and the structure of nature. Kriging method will have a "smooth effect", while it can not get the characteristics of partial changes between two points. Typically, for the most natural variables, it is not linear or smooth transition between two adjacent points, it exists a partial, non-linear, changes of characteristics. For traditional geostatistics, it can not be well deal with the nonlinear problems, but Fractal Geostatistics (FS) can solve this problem well.From the perspective of the fractal spatial to describe the distribution of characteristically variables, FS reveals partial non-linear changes in variables and realizes the forecast and simulation with the help of self-similar fractal and Unbiased Kriging optimal interpolation. At present, FS has not yet formed theories; this article summarized the development of its history and established a theoretical frame. FS takes soil and vegetation to study and it does research on soil (moisture, salt, organic matter, total nitrogen), the spatial structure and variability of vegetation biomass above ground, and compared with the traditional GS, the conclusions are:(1) FS is the development of traditional GS; the fractal dimension can characterize the complexity of the variable distribution. The valuation of fractal dimension orientation and multi-dimensional fractal are based on Kriging, they can simulate the distribution of the spatial variables better. The result of the valuation of Fractal dimension orientation and the Kriging interpolation are similarly, essentially, it is a Perspective transformation of fractal interpolation, it has less restrictive conditions and a simple calculation, but its estimated variance is bigger than Kriging variance. multi-dimensional fractal Kriging reflect the overall distribution of the trend variables, meanwhile, it can get more variable changes and high-frequency information, and reduce the "smooth effect" of Kriging, essentially ,it is based on the slide which weighted average by adding a correct result of singular.(2) There is an obvious spatial variability and variability with multi-level structure in space of the soil and vegetation of grassland, only with the primary structure , the changes of large-scale can contain the small-scale, even if the structure is at the same level, with the increasing of Random sampling scale, the accuracy of the interpolation will reduce, therefore, we can not be blind to change, the increasing and reducing of the sampling scale which is closely related to the problem that we do.(3) The fractal dimension of particle content and sand content in soil showed a significant linear negative correlation, viscosity content was showed a significant positive correlation, at the same time; it is relevant to the soil nitrogen, organic matter, and salt content. Fractal dimension can characterize the loss of situation of soil particulate matter and chemical element content, as comprehensive and quantitative indicators, it reflects the degree of soil desertification.This study developed the FS theoretical system more perfectly. It contribute to the non-linear development of GS, from the view of fractal, soil and vegetation characteristics of the spatial distribution analysis and simulation, it is possible to create a new point of growth disciplines.