›› 2011, Vol. 23 ›› Issue (5): 0-1006.

• 环境科学 •    

土壤养分含量的协同克里格法插值研究

李楠,徐东瑞*,吴杨洁

  

  1. 河北师范大学 资源与环境科学学院,河北 石家庄 050016
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-09-25 发布日期:2011-09-25

Spatial distribution with different sampling numbers of soil nutrient using Cokriging

LI Nan;XU Dong-rui*;WU Yang-jie   

  1. College of Resource and Environment Science, Hebei Normal University, Shijiazhuang 050016,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-09-25 Published:2011-09-25

摘要:

土壤养分含量的空间分布是农业领域研究的重要内容,空间插值是获取土壤养分含量空间分布的重要方法。空间插值方法很多,不同的空间插值方法结果精度各不相同。文章以石家庄城乡交错带土壤全氮、速效磷、速效钾三种养分含量为主变量,土壤有机质含量为辅助变量,选取普通克里格法和协同克里格方法,对85个采样点的土壤养分数据进行空间插值分析,获取土壤养分含量空间分布图。采用交叉验证法对其插值结果精度进行分析和评价,结果表明,采样点数量相同时协同克里格方法的结果精度明显高于普通克里格插值法;利用协同克立格法, 主变量数目在减少至70个,辅助变量不变的情况下,精度仍高于普通克里格法,且空间分布高度相似。说明在适当减少土壤样本的情况下,协同克里格法仍能保证插值精度,适合土壤养分空间插值。

关键词: 土壤养分, 空间插值, 普通克里格法, 协同克里格方法, 交叉检验

Abstract:

Spatial interpolation is a main method for obtaining the spatial distribution of soil nutrient which is an important part in agricultural research field. There are many different methods for spatial interpolation with different results. Taking three kinds of soil nutrient elements including total nitrogen, available phosphorus and available potassium in Shijiazhuang rurbania as main variables, soil organic matter as auxiliary variable. We obtained the spatial distribution of soil nutrient content by using two types of representative interpolation method, including Ordinary Kriging and Cokriging. There were 85 samples used for spatial interpolation and we used cross validation to analyze and appraise the results. The results showed that compared with the ordinary Kriging under the same sampling numbers the Cokriging is more suitable for spatial interpolation of soil nutrients. The interpolation accuracy of original data reduced to 70 using Cokriging was still higher than original 85 data using ordinary Kriging and their spatial distributions were quite similar. The results showed that the Cokriging was more suitable for spatial interpolation of soil nutrients. We proposed scientific management measures of soil nutrient content based on the spatial distribution of soil nutrient. It provided scientific theoretical guidance to use and protect land resources rationally and improve economic efficiency of crops.

Key words: soil nutrient, spatial interpolation, ordinary Kriging, Cokriging, cross validation