Acoustic and traditional excavation methods were used in consecutive summers to conduct two geospatial surveys of distributions of white grubs and other soil invertebrates in two forage fields. Indicator variables were constructed from listener- and computer-based assessments of sounds detected at each recording site and then applied in geostatistical analysis, contingency analysis, and spatial...

BACKGROUND Artemisinin-resistant Plasmodium falciparum malaria parasites are now present across much of mainland Southeast Asia, where ongoing surveys are measuring and mapping their spatial distribution. These efforts require substantial resources. Here we propose a generic 'smart surveillance' methodology to identify optimal candidate sites for future sampling and thus map the distribution of...

Seismic site effects are influenced mainly by geospatial uncertainties corresponding to geological or geotechnical spatial variance. Therefore, the development of a geospatial database is essential to characterize site-specific geotechnical information in multiscale areas and to optimize geospatial zonation methods with potentially high degrees of spatial variability based on trial-and-error ge...

In this report the main focuses are geostatistical Gaussian Markov random field (GMRF) models and parallel exact sampling of GMRFs. There are also brief overviews of parallel computing and Markov chain Monte Carlo (MCMC) methods, and a literature review of parallel MCMC. The geostatistical GMRF models are constructed by discretising the domain region using a lattice. Instead of giving this latt...

Sporisorium reilianum has caused significant economical damages in Mexico, in temperate and relatively dry areas, where maize is cultivated. The knowledge about the spatial distribution of this pathogen is basic to elaborate integrated management programs, and precise and eff icient the development of sampling methods and control techniques. Unfortunately, in Mexico there are no studies on spat...

BACKGROUND The success of genome-wide selection (GS) approaches will depend crucially on the availability of efficient and easy-to-use computational tools. Therefore, approaches that can be implemented using mixed models hold particular promise and deserve detailed study. A particular class of mixed models suitable for GS is given by geostatistical mixed models, when genetic distance is treated...

This paper describes one solution to the problem of constraining geostatistical models by well-test results which has been obtained within the frame of the HELIOS research project conduced by Elf and IFP in the field of reservoir engineering. To do so, a numerical simulation program devoted to the simulation of well-tests has been coupled with a nonlinear constrained optimization program to mak...

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. No...

Determination of Geostatistical Parameters Using Well Test Data — In this paper we describe a new method to obtain estimations of the geostatistical parameters (GPs) such as the correlation length, lc and the permeability variance, σln from well test data. In practical studies, the GPs are estimated using geological and petrophysical data, but often, these data are too scarce to give precise re...