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首页> 外文会议>International symposium on spatial accuracy assessment in natural resources and environmental science >The Effects of Sampling on the Accuracy of Predictions of Soil Properties in Precision Agriculture
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The Effects of Sampling on the Accuracy of Predictions of Soil Properties in Precision Agriculture

机译：抽样对精密农业土壤性质预测准确性的影响

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Precision agriculture aims to take account of the spatial variation of soil nutrient concentrations and other properties within fields. Sample information is used to predict values at unsampled places, and maps of these values represent the variation. Such maps will often appear convincing but their accuracy will depend on whether the initial sampling has resolved the variation present. The effect of sample intensity and sample design on the accuracy of predictions and maps is illustrated by sub-sampling a dense grid of data. Using the geostatistical methods of kriging and simulation predictions were made at sampling points from which the known values had been removed. The resulting maps show that the detail is degraded as sampling becomes less intensive, and that the location of the sample points is important, especially with sparse data. The results indicate that if accurate maps and estimates are required then the initial sampling must be sound. The kriged predictions were more accurate than those from simulation in general. Simulation, however, preserved the variability present and may be more appropriate for management.
机译：精密农业旨在考虑土壤养分浓度和田地内其他性能的空间变化。示例信息用于预测未夹杂地点的值，并且这些值的映射表示变化。这些地图通常会令人信服，但它们的准确性取决于初始采样是否已解决存在的变化。通过子采样数据的密集网格来说明样本强度和样本设计对预测和映射精度的影响。使用Kriging和模拟预测的地质统计方法是在取样点进行的，从中移除已知值。结果图表明，随着采样变得更少的，样本点的位置尤其具有稀疏数据，细节会降低。结果表明，如果需要准确的映射和估计，则初始采样必须为声音。 Kriged预测通常比仿真的预测更准确。然而，仿真保留了存在的可变性，并且可能更适合管理。

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