文献类型： 外文期刊

作者： Pan, Y. C. ¹ ; Lu, A. X. ¹ ; Liu, Q. Q. ² ; Li, S. H. ¹ ; Qin, X. Y. ¹ ; Zhou, Y. B. ¹ ; Lu, Z. ¹ ;

作者机构： 1.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

2.Shijiazhuang Univ Econ, Dept Publ Adm, Shijiazhuang 050031, Peoples R China

关键词： Soil nutrient; sampling scale; statistical parameters estimation; spatial variability analysis

期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.647； 五年影响因子：1.469 ）

ISSN： 1079-8587

年卷期： 2010 年 16 卷 6 期

页码：

收录情况： SCI

摘要： Based on nine soil nutrient datasets from different sampling scale, the effects of sampling scale on spatial variability analysis were analyzed. Results indicated that (i) with the sampling scale decreasing, the estimated mean of regional soil nutrient decreased, the coefficient variation increased, and the global trend of soil nutrient spatial distribution weakened. However, sampling scale did not change the fitting model of spatial variability; (ii) when sampling in a large scale and the weak self-correlation among soil samples, the relatively small number of samples will be enough for the regional statistical analysis to estimate parameters, but insufficient for spatial variability analysis and interpolation; (iii) when the sampling number is larger than the optimum (In the paper, the optimum sampling number is 112), the accuracy of regional statistical parameters, spatial variability characters and interpolation will increase with soil sampling scale decreasing. When sampling scale is lager than 0.2, it will fulfill the demand for the interpolation of soil nutrition; (iv) Spatial pattern of samples have a more significant effect on spatial range and accuracy of spatial interpolation than sampling scale.