Geostatistical Analysis of Soil Nutrients Based on GIS and Geostatistics in the Typical Plain and Hilly-Ground Area of Zhongxiang, Hubei Province
- 1 State Key Laboratory of Coal Resources and Safe Mining, China University of Mining & Technology, Beijing, China
- 2 College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, China
- 3 State Key Laboratory of Coal Resources and Safe Mining, China University of Mining & Technology, Beijing, China
- 4 State Key Laboratory of Coal Resources and Safe Mining, China University of Mining & Technology, Beijing, China;College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, China
- 5 State Key Laboratory of Coal Resources and Safe Mining, China University of Mining & Technology, Beijing, China; College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, China;
- 6 College of Resources and Environment, Huazhong Agricultural University, Wuhan, China.
Abstract
Techniques of geostatistics are used to perform traditional statistical analysis and spatial structural analysis with ArcGIS, geostatistical software GS+ and statistical software SPSS in order to obtain the knowledge of characteristics of distribution and spatial variability of soil nutrients in different parts of Zhongxiang, Hubei Province. Some skewed values appeared during the analyses. To decrease the influence of those skewed values, domain processing and Box-Cox transformation were used. The results indicated spatial variability of Total N, Avail. P, rapidly-available potassium (R-Avail. K) and effective zinc (Effect. Zn) was strong, that of organic carbon (Org. C), effective molybdenum (Effect. Mo) and effective copper (Effect. Cu) was medium while that of others was weak. Fitted model of Total N, R-Avail. K and Effect. Mo was spherical model, that of Org. C and Effect. Zn was exponential model, while fitted model of Avail. P and Effect. Cu was Gaussian model. Ratio of variability caused by random factors to overall variability was large. What’s more, the ranges of spatial autocorrelation of soil nutrients had much difference. The smallest value was 3600 m in Effect. Zn while the largest was 77970 m in Org. C. Other characteristics were also included. The study is helpful to soil sampling design, to make people realize the influence of Han River to spatial variability of soil nutrients in this area, and to spatial interpolation and mapping.
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