Near surface air temperature (NSAT) is a primary descriptor of terrestrial environmental conditions. In recent decades, many efforts have been made to develop various methods for obtaining spatially continuous NSAT from gauge or station observations. This study compared three spatial interpolation (i.e., Kriging, Spline, and Inversion Distance Weighting (IDW)) and two regression analysis (i.e.,...

PCA in a reproducing kernel Hilbert space is analysed as probabilistically optimal procedure of dimension reduction given a covariance structure by the reproducing kernel. It provides a unifying framework for various seemingly disparate and special techniques of dimension reduction applied to splines, in geostatistical “kriging” or in interpolation of data resulting from computer experiments. R...

Four spatial estimation techniques available in commercial computational packages are evaluated and compared, namely: regularized splines interpolation, tension splines interpolation, inverse distance weighted interpolation, and ordinary Kriging estimation, in order to establish the best representation for the shallow stratigraphic configuration in the city of Aguascalientes, in Central Mexico....

and Applied Analysis 3 2.2. Universal Kriging for Computing Water Depth in Any Position The basic premise of Kriging interpolation is that every unknown point can be estimated by the weighted sum of the known points: Z∗ 0 n ∑ i 1 λi Zi, 2.1 where Z∗ 0 represents the unknown point, Zi refers to each known point, and λ 0 i is the weight given to it. The Kriging algorithm body is involved in the a...

The interpolation of spatial data has been considered in many different forms. The various forms of kriging are among the best known in the earth sciences although techniques such as inverse distance weighting were and are in use for spatially located data. In the numerical analysis literature various forms of splines and more recently radial basis functions have been developed and used. Becaus...

A new method is proposed for the classification of data in a spatial context, based on the minimization of a variance-like criterion taking into account the spatial correlation structure of the data. Kriging equations satisfying classification bias conditions are then derived for interpolating the rainfall data while taking into account the classification.

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. In a real-world application we compare spatio-temporal interpolations using these models with a purely spatial kriging approach. The target variable of the...