The empirical variogram is a standard tool in the investigation and modelling of spatial covariance. However, its properties can be difficult to identify and exploit in the context of exploring the characteristics of individual datasets. This is particularly true when seeking to move beyond description towards inferential statements about the structure of the spatial covariance which may be pre...

Method for reducing the number of wild animal monitors is proposed by means of Kriging. Through wild animal route of simulations with 128 by 128 cells, the required number of wild animal monitors is clarified. Then it is found that the number of wild animal monitors can be reduced based on Kriging by using variograms and semi-variograms among the neighboring monitors. Also, it is found that the...

This paper concerns the second order marginals of biphased random media. We give discriminating necessary conditions for a bivariate function to be such a valid marginal, and illustrate our study with two practical applications: (1) the spherical variograms are valid indicator variograms if and only if they are multiplied by a sufficiently small constant, which upper bound is estimated, and (2)...

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were use...

Use of precision farming technologies requires better understanding of soil variability in physical, hydraulic and chemical properties. Some of that variation is natural, some is the result of the management history of the field. So, to match agricultural inputs and practices to site-specific conditions, the factorial kriging algorithm (FKA) was used to analyze spatial variability in some soil ...