Modeling and inferring spatial relationships predicting missing values of environmental data are some the main tasks geospatial statisticians. These routine accomplished using multivariate models cokriging technique. The latter requires evaluation expensive Gaussian log-likelihood function, which has impeded adoption for large datasets. However, this large-scale challenge provides a fertile gro...

the performance of geostatistical and spatial interpolation techniques for estimation of spatial variability of heavy metals and water quality mapping of groundwater resources in ramiyan district (golestan province- iran) were investigated. 24 spring/well water samples were collected and the concentration of heavy metals (ni, co, pb, cd and cu) was determined using differential pulse polarograp...

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