Geostatistical models often require a variogram or covariance model for kriging and krigingbased simulation. Next to the initial decision of stationarity, the choice of an appropriate variogram model is the most important decision in a geostatistical study. Common practice consists of fitting experimental variograms with a nested combination of proven models such as the spherical, exponential, ...

Geostatistical simulations are used to perform a global sensitivity analysis on a model Y = f(X1 ... Xk) where one of the model inputs Xi is a continuous 2D-field. Geostatistics allow specifying uncertainty on Xi with a spatial covariance model and generating random realizations of Xi. These random realizations are used to propagate uncertainty through model f and estimate global sensitivity in...

We propose a novel approach to landmark-based medical image registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistical relation between two images, as estimated using generalpurpose registration algorithms, in order to construct an optimum predictor of the displacement field. High accuracy is achieved by using an estimated spatial model of th...

Contents Summary 4 1 Motivation: time series normalization and adjustment 5 1.

of the many climatic events that influence the earth’s environment, drought is perhaps the one that is most linked with desertification. drought is the consequence of a natural reduction in the amount of precipitation received over an extended period, usually a season or more in length. drought monitoring is an essential component of drought risk management. it is normally performed using vario...

Fundamental to the philosophy of Precision Agriculture (PA) is the concept of matching inputs to needs. Recent research in PA has focused on use of Management Zones (MZ) that are fi eld areas characterised by homogeneous attributes in landscape and soil conditions. Proximal sensing (such as Electromagnetic Induction (EMI), Ground Penetrating Radar (GPR) and X-ray fl uorescence) can complement d...

Current literature dealing with the theory of sampling process flows is limited in scope, a situation addressed by papers presented at conferences author. This paper provides summary methods to quantify variance sound statistical manner. Two calculation are here models for robust estimation covariance/variogram. The strategies acquire data characterisation described. method can be based on spec...

Geostatistics is used to model the spatio-temporal variability in egg volumetric density measured by monitoring surveys performed on a major spawning ground of sole in the Bay of Biscay (France). An approximation formula is proposed for computing the estimation variance of the mean egg density estimated over space and time. The major structural feature is the time invariance in the spatial dist...

[1] Inverse modeling methods have been used to estimate surface fluxes of atmospheric trace gases such as CFCs, CH4, and CO2 on the basis of atmospheric mass fraction measurements. A majority of recent studies use a classical Bayesian setup, in which prior flux estimates at regional or grid scales are specified in order to further constrain the flux estimates. This paper, on the other hand, exp...