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地理研究  2001 

Characteristics of spatial variability of soil thickness in China
中国土壤土层厚度的空间变异性特征

Keywords: soil thickness,semi,variogram,spatial variability,kriging
土壤厚度
,变异函数,空间变异性,克里格插值法,中国,土层厚度

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Abstract:

The spatial variability of soil properties is very important to agriculture, soil quality assessment, sustainable development and global change research. Geostatistics is a means of spatial variability, spatial structures and spatial prediction that is used widely for soil properties overseas.However, this kind of research was started relatively late in China. On the other hand, our research on soils paid more attention to chemical and biological properties than to physical properties. This paper aimed to study spatial distribution characteristics of soil depth in China, especially that of physical ones using Geostatistics and Geographic Information System, and provide raster data for global change research.This paper built the China Soil Geographic Database which includes soil physical and chemical properties database and 1627 soil samplers database by data from the second national soil surveys and primarily studied the spatial distribution characteristics of the thickness of soil layer using GIS and Geostatistics. The spatial distribution features were quantitatively described by semi-variogram. Based on the semi-variogram, the maps illustrating soil thickness are made by ordinary Kriging with cell of 30km×30km.   Soil thickness being studied has relatively good spatial structures, and their experimental semi-variogram could be fitted by exponential model with nuggets. And optimal interpolation could be done depended on the semi-variogram features. Basically, the experimental semi-variogram of soil properties being studied increases with increasing lag distance to approach or attain a maximum. The range of soil thickness semi-variogram is up to 680km, which is consistent with average distances among patches with the same feature in the distribution maps. This indicates the significant trend known as “drift” in distribution maps.

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