Disaggregation of legacy soil data using area to point kriging for mapping soil organic carbon at the regional scale.
Disaggregation of legacy soil data using area to point kriging for mapping soil organic carbon at the regional scale.
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DOI：
10.1016/j.geoderma.2011.10.007
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发表时间：
2012-01-15
期刊：
影响因子：
6.1
通讯作者：
Marchant BP
中科院分区：
文献类型：
--
作者：
Kerry R;Goovaerts P;Rawlins BG;Marchant BP
土壤图形式的遗留数据通常具有与每个多边形相关的典型属性测量值，可以成为数字土壤制图（DSM）的重要信息来源。需要分解这些信息的方法，并使用回归克里金（RK）等方法对土壤性质进行定量估计。研究了几种分解过程；首选的方法包括那些包括考虑到scorpan因素的方法和那些质量保存（pycnophylactic）的方法，这些方法使不同研究尺度之间的转换在理论上更合理。区域到点克里格（顶部克里格）是积层的，在这里我们研究了它的优点，从土壤多边形地图分解遗留数据。本文还采用了将辅助数据纳入分解过程的面积到点回归克里格法（AtoP RK）。AtoP kriging和AtoP RK方法不涉及收集新的土壤测量数据，并与简单的栅格化分解方法进行了比较。在研究的分解方法中，AtoP RK对整个北爱尔兰土壤多边形数据的分解给出了最准确的土壤有机碳（SOC）浓度预测（交叉验证的平均绝对误差（MAEs）较小）。利用来自北爱尔兰Tellus调查的土壤样本数据和其他协变量（海拔高度和空气辐射测量钾），在RK框架中使用了由AtoP kriging和简单栅格化分解的遗留土壤多边形数据来估算整个北爱尔兰的土壤有机碳（SOC）浓度。这可以与之前对Tellus调查数据的分析进行直接比较。与之前对Tellus数据的分析相比，结合遗留数据，无论是简单的多边形栅格化还是AtoP kriging，都大大降低了RK的MAEs。然而，在RK中使用AtoP kriging分解的遗留数据会导致MAEs的更大减少。根据辅助数据的可用性，还进行了一项折叠刀程序，以确定整个北爱尔兰的有机碳RK需要收集的适当数量的额外土壤样品。我们建议我)如果遗留土壤多边形地图数据是可用的,他们应该使用在克里格分解,2)如果还可以使用辅助数据遗留数据应该分解使用在RK和iii)如果新的土壤测量可用除了辅助和遗留土壤地图数据,遗留土壤地图数据应该首先分解使用在克里格和使用这些数据以及辅助数据作为RK的固定效应的新土壤测量。
Legacy data in the form of soil maps, which often have typical property measurements associated with each polygon, can be an important source of information for digital soil mapping (DSM). Methods of disaggregating such information and using it for quantitative estimation of soil properties by methods such as regression kriging (RK) are needed. Several disaggregation processes have been investigated; preferred methods include those which include consideration of scorpan factors and those which are mass preserving (pycnophylactic) making transitions between different scales of investigation more theoretically sound. Area to point kriging (AtoP kriging) is pycnophylactic and here we investigate its merits for disaggregating legacy data from soil polygon maps. Area to point regression kriging (AtoP RK) which incorporates ancillary data into the disaggre-gation process was also applied. The AtoP kriging and AtoP RK approaches do not involve collection of new soil measurements and are compared with disaggregation by simple rasterization. Of the disaggregation methods investigated, AtoP RK gave the most accurate predictions of soil organic carbon (SOC) concentrations (smaller mean absolute errors (MAEs) of cross-validation) for disaggregation of soil polygon data across the whole of Northern Ireland. Legacy soil polygon data disaggregated by AtoP kriging and simple rasterization were used in a RK framework for estimating soil organic carbon (SOC) concentrations across the whole of Northern Ireland, using soil sample data from the Tellus survey of Northern Ireland and with other covariates (altitude and airborne radiometric potassium). This allowed direct comparison with previous analysis of the Tellus survey data. Incorporating the legacy data, whether from simple rasterization of the polygons or AtoP kriging, substantially reduced the MAEs of RK compared with previous analyses of the Tellus data. However, using legacy data disaggregated by AtoP kriging in RK resulted in a greater reduction in MAEs. A jack-knife procedure was also performed to determine a suitable number of additional soil samples that would need to be collected for RK of SOC for the whole of Northern Ireland depending on the availability of ancillary data. We recommend i) if only legacy soil polygon map data are available, they should be disaggregated using AtoP kriging, ii) if ancillary data are also available legacy data should be disaggregated using AtoP RK and iii) if new soil measurements are available in addition to ancillary and legacy soil map data, the legacy soil map data should be first disaggregated using AtoP kriging and these data used along with ancillary data as the fixed effects for RK of the new soil measurements.
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影响因子：
3.1
作者：
McBratney, AB
通讯作者：
McBratney, AB
影响因子：
6.1
作者：
de Bruin, S;Wielemaker, WG;Molenaar, M
通讯作者：
Molenaar, M
影响因子：
2.9
作者：
Yoo, E. -H.;Kyriakidis, P. C.
通讯作者：
Kyriakidis, P. C.
DOI：
10.1080/13658810701492225
发表时间：
2008-01-01
影响因子：
5.7
作者：
Liu, X. H.;Kyriakidis, P. C.;Goodchild, M. F.
通讯作者：
Goodchild, M. F.
在土壤特性的空间插值中结合脉络膜图和现场数据的连贯的地统计方法。
影响因子：
4.2
作者：
Goovaerts P
通讯作者：
Goovaerts P