基于地统计的土壤养分采样布局优化  

Optimal arrangement of soil nutrient sampling based on geo-statistics

作　　者：陈天恩 陈立平[1,2] 王彦集 郜允兵[1,2] 任仲山 

机构地区：[1]北京农业智能装备工程技术研究中心,北京100097 [2]农业部农业信息技术重点开放实验室,北京100097

出　　处：《农业工程学报》2009年第S2期49-55,共7页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家863计划重大项目课题(2006AA10A306);863计划课题(2007AA10Z234)

摘　　要：传统的土壤养分采样布置方法都是基于采样区土壤特征状态空间随机变异的假设。而地统计学研究表明,土壤特征状态在空间上有关联性,因此利用传统方法来制定采样方案并不是最优的,因为它没有考虑土壤特性的空间相关性,不能反映其局部的变化特征。该文在分析土壤肥力空间变异的基础上,研究利用经典统计学方法确定合理的采样点数目,并基于地统计学的半方差函数拟合与Kriging方法确定合理的采样点布局的方法,选择典型地区的土壤肥力进行空间变异分析和采样点布置的优化设计。研究结果表明:在合理的位置布置14个采样点就可以满足典型基地种植区绘制施肥处方图进行变量施肥决策的要求;利用经典统计学与地统计分析相结合的方法进行农田尺度的土壤肥力采样布点优化分析具有良好的可行性。Traditional arrangement methods of sampling points were established on the hypothesis that spatial characteristics of soil were random variation.But research results of geo-statistics showed that changes in spatial characteristics of soil were not completely random,soil characteristic status had relevance at spatial.So traditional arrangement methods were used for making sampling plan,those did not reflected local variation..In this paper,classical statistical methods were used to determine the optimal number of sampling points,and geo-statistics methods,like semivariogram and Kriging methods,were used to determine the optimal arrangement of sampling points based on the analysis on spatial variation of soil fertility characteristics.Spatial variation of soil fertility was analyzed in typical areas.The results showed that 14 soil sampling points were enough to meet the needs of drawing prescription map for precision fertilization in the field of typical.It is a feasible method that classical statistics and geostatistical analysis were combined for optimal arrangement soil fertility sampling.

关 键 词：土壤 养分 采样 半方差函数 KRIGING插值 布局优化 

分 类 号：S158[农业科学—土壤学]