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The interpolation accuracy for seven soil properties at various sampling scales on the Loess Plateau, China

机译:黄土高原地区不同采样尺度下七种土壤属性的插值精度

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Purpose Knowledge of the changes in interpolation accuracy with changing sampling scales is important when designing an appropriate sampling strategy. The objectives of this study were (1) to analyze the changes in interpolation accuracy with changing sampling scales for seven soil properties and (2) to find a suitable index that could predict the interpolation accuracy well.Materials and methods Nine hundred sixty-one samples were collected from a 30 × 30-m area. Seven soil properties were measured for each sample. Using a re-sampling analysis method, we grouped the samples under 16 subscales. Then, we divided the 16 subscales into two subsets, the first consisting of eight scales used as training sets and the second having the other eight scales as validation sets. Using the training sets, the interpolation accuracy and the contribution rate (CR) for the seven soil properties were compared and the relations of the interpolation accuracy to the coefficient of variation (CV), or to the ratio of sampling spacing to correlated range (S/R), or to the extent and spacing (E & S) were determined, the accuracy of prediction of which were then tested using the validation sets Results and discussion The results showed that the mean interpolation accuracies varied greatly for different soil properties, with mean G values of training sets ranging from 2.4% for soil organic carbon, to 62.1% for sand content. With increasing sampling spacing or decreasing sampling extent, the interpolation accuracy decreased for all soil properties. The scales with the largest CR were not consistent with those with the highest interpolation accuracies. The interpolation accuracy was predicted better by E & S than by CV or by S/R.Conclusions The measurement and analysis gave insight into the changes of interpolation accuracy and CR at various sampling scales. Predicting interpolation accuracy based on the scale parameters of sampling spacing and sampling extent was feasible, which provided a useful means by which to determine appropriate sample size and sampling strategy.
机译:目的在设计适当的采样策略时,了解随着插值比例的变化而内插精度的变化非常重要。这项研究的目的是(1)分析七种土壤属性随采样尺度变化的插值精度变化,以及(2)找到一个可以很好地预测插值精度的合适指标。材料和方法961个样本从30×30米的区域收集。每个样品测量了七个土壤特性。使用重新抽样分析方法,我们将样本分为16个子量表。然后,我们将16个子量表分为两个子集,第一个子量表由八个量表组成,第二个子量表将其他八个量表作为验证集。使用训练集,比较了七个土壤属性的插值精度和贡献率(CR),并且插值精度与变异系数(CV)或采样间距与相关范围之比(S)的关系/ R),或者确定程度和间距(E&S),然后使用验证集测试预测的准确性。结果和讨论结果表明,不同土壤特性的平均插值精度差异很大,训练集的平均G值范围从土壤有机碳的2.4%到沙子含量的62.1%不等。随着采样间隔的增加或采样范围的减小,所有土壤属性的插值精度都会降低。 CR最高的比例与内插精度最高的比例不一致。用E&S预测插值精度比用CV或S / R更好。结论通过测量和分析,可以洞察插值精度和CR在各种采样比例下的变化。基于采样间隔和采样范围的尺度参数预测内插精度是可行的,这为确定合适的样本量和采样策略提供了有用的手段。

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  • 来源
    《Journal of soil & sediments》 |2012年第2期|p.128-142|共15页
  • 作者

    Lei Gao; Mingan Shao;

  • 作者单位

    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100 Shaanxi, People's Republic of China ,Graduate University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China;

    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, People's Republic of China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    interpolation accuracy; loess plateau; re-sampling analysis; sampling scales; soil properties;

    机译:插补精度黄土高原重新抽样分析;抽样秤;土壤性质;

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