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 ...

ABSTRACT Estimation of mineral resources and reserves with low values of error is essential in mineral exploration. The aim of this study is to estimate and model a vein type deposit using disjunctive kriging method. Disjunctive Kriging (DK) as an appropriate nonlinear estimation method has been used for estimation of Cu values. For estimation of Cu values and modelling of the distributio...

Classical geostatistical methods face serious computational challenges if they are confronted with large spatial datasets. The stochastic local interaction (SLI) approach does not require matrix inversion for parameter estimation, prediction, and uncertainty estimation. This leads to better scaling of complexity storage requirements data size than standard (i.e., without size-reducing modificat...

the present study was carried out to evaluate three interpolation methods including weighted moving average (wma) with the power of 2 and 3, kriging and cokriging methods. data of 23 wells in mazandaran province were collected in fall and spring 2006. seven parameters including electrical conductivity (ec), ph, total dissolved solids (tds), sodium adsorption ratio (sar), total hardness (th), ch...

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...

abstract precipitation as the most important factor plays the main role in many application researches which are based on climatic parameters. many researches in the field of hydrology, hydrometeorology and agriculture employs rain-gauges (such as synoptic and climatologic stations) data. precipitation characteristics, such as rainfall intensity and duration, usually exhibit significant spatial...

When analysing data from computationally expensive simulation codes or process measurements, surrogate modelling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualisation and optimisation. Kriging is a popular surrogate modelling technique for data based on deterministic computer experiments. There exist several types of Kriging, mostly dif...

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 ...