This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions in an environmental risk mapping context. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations and shows good performances in reconstructing local PDF. The data sets used for this comparison are parts of the digital elevat...

ABSTRACT-Determining hydraulic conductivity of soil is difficult, expensive, and time-consuming. In this study, Algorithm Genetic and geostatistical analysis and Neural Networks method are used to estimate soil saturated hydraulic conductivity using the properties of particle size distribution. The data were gathered from 134soil profiles from soil and lander form studies of the Ardabil Agricul...

Abstract This article describes two R packages for probabilistic weather forecasting, ensembleBMA, which offers ensemble postprocessing via Bayesian model averaging (BMA), and ProbForecastGOP, which implements the geostatistical output perturbation (GOP) method. BMA forecasting models use mixture distributions, in which each component corresponds to an ensemble member, and the form of the compo...

Data from the acoustic surveys of MV SA ‘‘Agulhas’’ and FRV ‘‘Walther Herwig’’, and the 1981 RRS ‘‘John Biscoe’’ South Georgia acoustic survey were analysed by geostatistical methods. Estimates of mean density (g m) of krill and their variances are compared with published results from statistical analyses based on random sampling theory. A further high-resolution geostatistical analysis of the ...

Most spatial analysis computer programs are available on the ‘World Wide Wait’ leading this framework to a new GIS platform. Ultimately, this world expects fast answers because if it works then it is obsolete. To review and to evaluate the present spatial geostatistical analysis software and withdraw major conclusions regarding its implementation status are the major goal of th...

The purpose of this study is to evaluate the spatial changes of groundwater nitrate concentrations by using geostatistical methods based on data from 119 groundwater wells. Geostatistical methods have been used widely as a convenient tool to make decision on the management of behavior of hydrochemical parameters in groundwater. To evaluate the spatial changes nitrate concentrations in groundwat...

This paper describes a geostatistical approach for environmental data modeling based on value descriptive analysis, variographic analysis, estimation method and validation. It shows an application related to atmospheric pollutant dispersion (ozone) detected by active biomonitoring in the province of Livorno (Italy). This work proposes a two-stage approach based on: the computation of an index o...

The Shenhua Carbon Capture and Storage (CCS) project at the Shenbei Slope injection site in North Yulin is the first 100,000 tonper-year scale CCS pilot project in China with an injection operation lasting nearly 3 years. In this study, we investigate various geostatistical methods and their impact on the respective geologic models on which simulation is performed to understand the phenomena ob...

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...