The newest version of the ITC GIS and Remote Sensing software ILWIS offers an integrated set of modules to perform geostatistics. Its functionality for image processing, geographic analysis and digital mapping combined with extensive geostatistical tools make it a modern product for education and research in the field of G.I.S. It incorporates spatial correlation tools like semi-and cross vario...

This paper investigates the use of Kriging in random simulation when the simulation output variances are not constant. Kriging gives a response surface or metamodel that can be used for interpolation. Because Ordinary Kriging assumes constant variances, this paper also applies Detrended Kriging to estimate a non-constant signal function, and then standardizes the residual noise through the hete...

There is increasing interest in the spatial aspects of many policy decisions. To be valid decision-malung tools it is important that maps not only convey what is known, but also where the uncertainties lie. This paper reports the results of tests conducted to assess the ability of various methods of error representation to accurately assist interpretation of maps. The work uses the predicted su...

ABSTRACT The metallicity of diffuse ionized gas (DIG) cannot be determined using strong emission line diagnostics, which are calibrated to calculate the H ii regions. Because this, resolved maps from integral field spectroscopy (IFS) data remain largely incomplete. In this paper (the second a series), we introduce geostatistical technique universal kriging, allows complete 2D distribution galax...

In the context of the use of remote sensed data for monitoring land cover it is very important to develop methodologies to obtain reliable maps. In order to achieve this objective a possible approach is to combine both “spectral” and “spatial” features to characterizing each ground class. In this paper we propose the integration of a spectral classifier for remote sensed data at medium resoluti...

Abst r Ac t A comprehensive overview of numerical methodologies currently available for analyzing and building understanding of complex processes is presented. Both equation-free and equation-based methods are discussed. Many multi-scale techniques, including the use of reduced order models, lifting-restricting methods, averaging strategies such as molecular dynamics, Monte Carlo simulation and...

This paper describes a combination approach of a digital finite element modeling technique and the Kriging method for structural optimization. Since the digital modeling technique includes some inaccuracies in a modeling process, applicability of the Kriging method to noisy data is investigated. An estimated surface generated by the conventional Kriging method will be wavy and not appropriate t...

“Kriging” is the name of a parametric regression method used by hydrologists and mining engineers, among others. Features of the kriging approach are that it also provides an error estimate and that it can conveniently be employed also to estimate the integral of the regression function. In the present work, the kriging method is described and some of its statistical characteristics are explore...

Abstract Groundwater-level trends over the past 40 years in Mimbres Basin of southwest New Mexico (USA) were characterized with sequential water-level maps and change generated via spatiotemporal kriging. In region most abundant irrigated agriculture, water levels have declined up to 24 m cones depression expanded greatly. Increases area land groundwater withdrawals 10 are coeval declines near ...

Kriging is one of the most often used prediction methods in spatial data analysis. This paper examines which steps of the underlying algorithms can be performed in parallel on a PVM cluster. It will be shown, that some properties of the so called kriging equations can be used to improve the parallelized version of the algorithm. The implementation is based on R and PVM. An example will show the...