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A coherent geostatistical approach for combining choropleth map and field data in the spatial interpolation of soil properties

机译:一种在土壤属性空间插值中结合孔隙度图和野外数据的相干地统计方法

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摘要

Information available for mapping continuous soil attributes often includes point field data and choropleth maps such as soil or geology maps that model the spatial distribution of soil attributes as the juxtaposition of polygons (areas) with constant values. This paper presents two approaches to incorporate both point and areal data in the spatial interpolation of continuous soil attributes. In the first instance, area-to-point kriging is used to map the variability within soil units while ensuring the coherence of the prediction so that the average of disaggregated estimates is equal to the original areal datum. The resulting estimates are then used as local means in residual kriging. The second approach proceeds in one step and capitalizes on (i) a general formulation of kriging that allows the combination of both point and areal data through the use of area-to-area, area-to-point and point-to-point covariances in the kriging system, (ii) the availability of Geographical Information Systems (GIS) to discretize polygons of irregular shape and size and (iii) knowledge of the point-support variogram model that can be inferred directly from point measurements, thereby eliminating the need for deconvolution procedures. The two approaches are illustrated using the geological map and heavy metal concentrations recorded in the topsoil of the Swiss Jura. Sensitivity analysis indicates that the new procedures improve prediction over ordinary kriging and traditional residual kriging based on the assumption that the local mean is constant within each mapping unit.
机译:可用于绘制连续土壤属性的信息通常包括点场数据和诸如土壤或地质图之类的地形图,它们将土壤属性的空间分布建模为具有恒定值的多边形(区域)的并置。本文提出了两种在连续土壤属性的空间插值中合并点和面数据的方法。在第一种情况下,面积对点克里金法用于绘制土壤单位内的变异性,同时确保预测的连贯性,以使分类估计的平均值等于原始面积基准。然后将所得的估计值用作残余克里金法中的局部均值。第二种方法一步一步进行,并利用(i)克里金法的一般表述,该模型允许通过使用区域间,区域间和点对点协方差来组合点数据和面数据在kriging系统中,(ii)可以使用地理信息系统(GIS)来离散不规则形状和大小的多边形,以及(iii)可以直接从点测量中推断出的点支持变异函数模型知识用于反卷积程序。使用地质图和瑞士汝拉州表层土壤中记录的重金属浓度说明了这两种方法。敏感性分析表明,基于本地均值在每个映射单元内都是恒定的假设,新程序比普通克里格法和传统残差克里格法改进了预测。

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