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Detecting zones of abrupt change in soil data, with an application to an agricultural field

机译:检测土壤数据突变区域,并应用于农业领域

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摘要

We propose a new method for estimating and testing the zones where a variable has discontinuities or sharp changes in the mean. Such zones are called Zones of Abrupt Change (ZACs). Our method is based on the statistical properties of the estimated gradient of the variable. The local gradient is first interpolated by kriging. Then we test whether the estimated local gradient exceeds some critical threshold computed under the null hypothesis of a constant mean. The locations where the local test is rejected define the potential ZACs, which are then tested globally. Using this method, we analysed soil data from an agricultural field. The analysis of the main soil components of the ploughed layer (clay, silt and sand particles and calcium carbonate content) reveals the structural variations in the field, linked to boundaries between soil types. Its application to non-permanent variables (soil water and mineral nitrogen content of the soil profile to 120 cm taken at several dates) shows that water content has the same ZACs for all dates, whereas mineral nitrogen has none.
机译:我们提出了一种新方法,用于估计和测试变量不连续或均值急剧变化的区域。这样的区域称为突变区域(ZAC)。我们的方法基于变量的估计梯度的统计属性。首先通过克里金插值法对局部梯度进行插值。然后,我们测试估计的局部梯度是否超出在恒定均值的零假设下计算出的某个临界阈值。拒绝本地测试的位置定义了潜在的ZAC,然后对其进行全局测试。使用这种方法,我们分析了农田的土壤数据。对耕层主要土壤成分(粘土,淤泥和沙粒以及碳酸钙含量)的分析揭示了田间的结构变化,与土壤类型之间的边界有关。将其应用于非永久变量(在多个日期获取的土壤剖面中的土壤水和矿质氮含量达到120 cm)显示,所有日期的水分ZAC均相同,而矿质氮则无。

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