We discuss Kriging Interpolation on high-performance computers as a method for spatial data interpolation. We analyse algorithms for implementing Kriging on high-performance and distributed architectures. In addition to a number of test problems, we focus on an application of comparing rainfall measurements with satellite imagery. We discuss our hardware and software system and the resulting pe...

This study presents a method to estimate land surface temperature (LST) by calibrating spatial interpolation using satellite-derived surface emissivity. Four spatial interpolation methods including Inverse Distance Weighting (IDW), Spline, Kriging, and Cokriging were tested to interpolate LST in southern New England using ground temperatures measured at national weather stations (NWS) in summer...

Kriging is a spatial interpolation algorithm which provides the best unbiased linear prediction of an observed phenomena by taking a weighted average of samples within a neighbourhood. It is widely used in areas such as geo-statistics where, for example, it may be used to predict the quality of mineral deposits in a location based on previous sample measurements. Kriging has been identified as ...

SAKWeb pretends to be the first E-Learning research development of spatial autocorrelation and Kriging interpolation for geostatisticiens. It is expected to be available in 2009 as a worldwide Web platform (named myGeoOffice.org) for all research institutes and universities that needs to carried out truly spatial stochastic and deterministic interpolation analysis. This will include simulation,...

In simulation, Median Polish Kriging is a technique used to predict unobserved data points in two-dimensional space. The linear behavior of the traditional Median Polish Kriging in the estimation of the mean function in a high grid makes the interpolation of O(1) which has a low order in the prediction and that leads to a high prediction error. Therefore, an improvement in the estimation of the...

Kriging interpolation is largely used in geostatistics to characterise the spatial structure of data and it is established in general based upon the stationary or intrinsic assumptions; however, the consequence of this second-order approximation is that the local singularities (or extremes) could be smoothed off. This drawback could be magnified as a finerscale phenomenon is being investigated,...

Eight interpolation methods are implemented and tested over a 60 km × 60 km region in Korea, using the results from automatic stereo-matching of SPOT images. First, with the simulated elevation data from digitised contours of paper maps, Kriging and Multiquadric methods show higher performance: with the accuracy better than 3 m than other methods and the speed of ~400 s on a Sparc 20 machine. S...

In optical metrology the final experimental result is normally an image acquired with a CCD camera. Owing to the sampling at the image, an interpolation is usually required. For determining the error in the measured parameters with that image, knowledge of the uncertainty at the interpolation is essential. We analyze how kriging, an estimator used in spatial statistics, can generate convolution...

An important problem between specialists is the interpolation of the surfaces determined by classics or modern techniques. Choosing the proper technique is practically a rigorous study regarding all the interpolation methods and using that method according to the needs of the project. The determination of the Digital terrain model, the digital surface model from GNSS, LiDAR or classic measureme...

This paper is continuation work of a research started in 2005. In the previous research, variety of fuzzy digital elevation models was constructed and the best fit model was selected in order to present an alternative in modelling height information. The previous study revealed that fuzzy digital elevation model gave satisfied result compared with the result from TIN (Triangulated Irregular Net...