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中文摘要：
空间插值方法的差异以及采样数量不同对土壤质量评价空间分布的预测精度会产生影响。本文通过随机抽样的方法，以山东省禹城市的土壤质量指数为例，从359个土壤采样点中抽取了340，170，90，50，30五个样本子集，通过普通克里格、简单克里格、反距离加权法和样条函数法4种插值方法，分别对其空间变异和布局进行了解析和预测。结果表明：不同插值方法对预测精度影响不显著，而采样点数量则显著影响了土壤质量指数空间分布预测的精度。本文提出在华北平原县域尺度上，以土壤质量评价作为调查目的的土壤采样中，90个样点是比较适宜的采样数量。同时，将我们的结果与Cochran最佳采样数量计算公式获取的最佳采样量比较后发现，Cochran方法获取的最佳采样数量明显偏低，若不考虑实际的空间变异情况，仅仅使用Cochran公式可能会导致土壤质量空间预测不准确。
英文摘要：
Reasonable sampling sizes or spatial interpolation method is an assurance of the accuracy of soil spatial variability analysis which is important for sustainable use of soil resources. This paper discussed the influence of sampling sizes and spatial interpolation method on spatial prediction accuracy of soil fertility quality using Ordinary Kriging, Simple Kriging, Inverse Distance Weighted and Spline Function method by comparing random samples of 340, 170, 90, 50 and 30 from a total of 359 samples. The results indicated that the differences of prediction accuracy between different interpolation methods were not significant, whereas the differences of prediction accuracy between different sampling sizes were significant. This study suggested that a minimum sampling size of 90 should be used for soil fertility quality evaluate in the North China Plain. Moreover, this study compared this minimum sampling size with the appropriate sampling quantity acquiring by Cochran method, and found that the sampling quantity acquire by Cochran was smaller. So this study suggested using Cochran method without considering the spatial variability would produce inaccurate spatial prediction.
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