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EasyKrig_V3

于 2013-11-27 发布 文件大小:516KB
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  克里金法广泛地应用于地下水模拟、土壤制图等领域,是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布.确定对一个待插点值有影响的距离范围,然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后,为达到线性、无偏和最小估计方差的估计,而对每一个样品赋与一定的系数,最后 进行加权平均来估计块段品位的方法。(Kriging is a technique that provides the Best Linear Unbiased Estimator of the unknown fields (Journel and Huijbregts, 1978 Kitanidis, 1997). It is a local estimator that can provide the interpolation and extrapolation of the originally sparsely sampled data that are assumed to be reasonably characterized by the Intrinsic Statistical Model (ISM). An ISM does not require the quantity of interest to be stationary, i.e. its mean and standard deviation are independent of position, but rather that its covariance function depends on the separation of two data points)

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