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Spatial simulation of soil attribute based on principle of soil science

机译:基于土壤科学原理的土壤属性空间模拟

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Presently, the research of soil attribute space simulation for improving simulation accuracy focus on the two facts; one is to get enough sample point as far as possible for improving simulation accuracy, which is by the mean of half variant function and covariance function accuracy. Another is to embody the geographic environmental information (elevation, land use, vegetation type, etc.) to the soil attributes space simulation for improving simulation accuracy. In this article, according to general principles of soil science, which is that the relationship between the soils attributes, the author puts forward the soil attribute space simulation based on the general principles of soil science. And then the author chose the soil organic matter (SOM) as simulation object to simulate the SOM space distribution by using of the relationship between STN and SAK. The methods included Ordinary kriging and Cokriging to predict soil space distribute. The cross-validations results showed that the Cokriging method predicted values and measured values are more consistent (regression line closer to 45 ° line). At the same time, the regression coefficients between the Cokriging predicted values and the measured values were 0.7342. The regression coefficients between the ordinary kriging predicted values and the measured values was 0.2488. Test data sets validations results showed that the predicted values and measured values were more consistent from the Cokriging method (regression line closer to 45 ° line). At the same time, the regression coefficients by Cokriging predicted value and measured value was 0.2283. The regression coefficients by ordinary kriging predicted values and measured values was 0.2098. Through cross-validation and test data sets validations, the method of Cokriging by the use of soil attribute auxiliary parameter was better for improving simulation accuracy. Therefore, the method of regarding soil sampling point related attributes as auxilia- y parameter is a simple and efficient method to improve prediction accuracy, which has extensive application in the spatial simulation of soil attribute.
机译:目前,为提高模拟精度而进行的土壤属性空间模拟研究主要集中在两个方面。一种是通过半变函数和协方差函数的准确度,尽可能地获取足够的采样点以提高仿真精度。另一个是将地理环境信息(海拔,土地用途,植被类型等)体现到土壤属性空间模拟中,以提高模拟精度。本文根据土壤科学的一般原理,即土壤属性之间的关系,提出了基于土壤科学的一般原理的土壤属性空间模拟。然后,作者利用STN和SAK之间的关系,选择土壤有机质(SOM)作为模拟对象,模拟了SOM的空间分布。这些方法包括普通克里格法和共同克里格法来预测土壤空间分布。交叉验证的结果表明,Cokriging方法的预测值和测量值更加一致(回归线接近45°线)。同时,Cokriging预测值和测量值之间的回归系数为0.7342。普通克里金法预测值与实测值之间的回归系数为0.2488。测试数据集的验证结果表明,与Cokriging方法相比,预测值和测量值更加一致(回归线更接近45°线)。同时,通过Cokriging预测值和测量值得出的回归系数为0.2283。普通克里金法预测值和实测值的回归系数为0.2098。通过交叉验证和测试数据集验证,使用土壤属性辅助参数进行协同克里格法的方法更好地提高了仿真精度。因此,将土壤采样点相关属性作为辅助参数的方法是一种提高预测精度的简单有效的方法,在土壤属性的空间模拟中有着广泛的应用。

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