期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Spatial Modeling of Soil Lime Requirements with Uncertainty Assessment Using Geostatistical Sequential Indicator Simulation
1
作者 Jussara de Oliveira Ortiz Carlos Alberto Felgueiras +2 位作者 eduardo celso gerbi camargo Camilo Daleles Rennó Manoel Jimenez Ortiz 《Open Journal of Soil Science》 2017年第7期133-148,共16页
This work presents and analyses a geostatistical methodology for spatial modelling of Soil Lime Requirements (SLR) considering punctual samples of Cation Exchange Capacity (CEC) and Base Saturation (BS) soil propertie... This work presents and analyses a geostatistical methodology for spatial modelling of Soil Lime Requirements (SLR) considering punctual samples of Cation Exchange Capacity (CEC) and Base Saturation (BS) soil properties. Geostatistical Sequential Indicator Simulation is used to draw realizations from the joint uncertainty distributions of the CEC and the BS input variables. The joint distributions are accomplished applying the Principal Component Analyses (PCA) approach. The Monte Carlo method for handling error propagations is used to obtain realization values of the SLR model which are considered to compute and store statistics from the output uncertainty model. From these statistics, it is obtained predictions and uncertainty maps that represent the spatial variation of the output variable and the propagated uncertainty respectively. Therefore, the prediction map of the output model is qualified with uncertainty information that should be used on decision making activities related to the planning and management of environmental phenomena. The proposed methodology for SLR modelling presented in this article is illustrated using CEC and BS input sample sets obtained in a farm located in Ponta Grossa city, Paraná state, Brazil. 展开更多
关键词 SPATIAL Modeling of SOIL Attributes INDICATOR GEOSTATISTICS Joint Simulation Principal Component ANALYSES SPATIAL UNCERTAINTY ANALYSES
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部