In environmental sciences it is relatively common to encounter certain problems that require specific experimental data treatment by means of spatial estimation methods, for example mapping the spatial distribution of a contaminant concentration exceeding a limit level, an ‘alarm problem’. In such situations the real problem is not directly related to the estimation of the variable at any parti...

6 The eruption of Novarupta within the Katmai Volcanic Cluster, south-west Alaska, in June 1912 was the 7 most voluminous eruption of the 20 Century but the distal distribution of tephra deposition is 8 inadequately quantified. We present new syntheses of published tephrostratigraphic studies and a large 9 quantity of previously un-investigated historical records. For the first time we apply a ...

In this paper we study the ability of the Cokriging method to represent functions with multiple local minima and sharp discontinuities for use in the multidimensional design of a low-boom supersonic business jet wing-body-canard configuration. Cokriging approximation models are an extension of the original Kriging method which incorporate secondary information such as the values of the gradient...

A crop height model (CHM) can be an important element of the decision making process in agriculture, because it relates well with many agronomic parameters, e.g., crop height, plant biomass or crop yield. Today, CHMs can be inexpensively obtained from overlapping imagery captured from unmanned aerial vehicle (UAV) platforms or from proximal sensors attached to ground-based vehicles used for reg...

yazd province is one of the most arid regions of iran and its agriculture particularly pistachio cultivation depends on groundwater resources. in the recent decades, natural factors (drought and severe evaporation) and human activities (over- exploitation of groundwater) caused a sharp decline in the quality and quantity of groundwater in this province. in the present study, the spatial and tem...

In numerical dosimetry, the recent advances in high performance computing led to a strong reduction of the required computational time to assess the specific absorption rate (SAR) characterizing the human exposure to electromagnetic waves. However, this procedure remains time-consuming and a single simulation can request several hours. As a consequence, the influence of uncertain input paramete...

Image interpolation has been used spaciously by customary interpolation techniques. Recently, Kriging technique has been widely implemented in simulation area and geostatistics for prediction. In this article, Kriging technique was used instead of the classical interpolation methods to predict the unknown points in the digital image array. The efficiency of the proposed technique was proven usi...

Kriging or Gaussian Process Regression is applied in many fields as a non-linear regression model as well as a surrogate model in the field of evolutionary computation. However, the computational and space complexity of Kriging, that is cubic and quadratic in the number of data points respectively, becomes a major bottleneck with more and more data available nowadays. In this paper, we propose ...

Image denoising is a critical issue in the field of digital image processing. This paper proposes a novel Salt & Pepper noise suppression by developing a Kriging Interpolation Filter (KIF) for image denoising. Gray-level images degraded with Salt & Pepper noise have been considered. A sequential search for noise detection was made using kk window size to determine nonnoisy pixels only. The non...

Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational burden when the data set is large. We focus on a class of methods aiming at decreasing this computational cost, consisting in aggregating Kriging predictors based on smaller data subsets. We prove that aggregations based...