An accurate estimation of soil organic matter (SOM) content for spatial non-point prediction is an important driving force for the agricultural carbon cycle and sustainable productivity. This study proposed a hybrid geostatistical method of extreme learning machine-ordinary kriging (ELMOK), to predict the spatial variability of the SOM content. To assess the feasibility of ELMOK, a case study w...

Keeping the water table at a favorable level is quite significant for a sustainable management of groundwater plans. Various management measures need to know the spatial and temporal behavior of groundwater. Therefore, the measurement of groundwater levels are generally carried out at spatially random locations in the field; whereas, most of the groundwater models requires these measurement at ...

Reservoir model needs to be constrained by various data, including dynamic production data. Reservoir heterogeneities are usually described using geostatistical approaches. Constraining geologicaljgeostatistical mode! realizations by dynamic data is generally performed through history matching, which is a complex inversion process and requires a parameterization of the geostatistical realizatio...

Being able to provide a quick and accurate pollutant maps from readings at isolated measurement stations is becoming more important today in light of the European norms on air quality and the public’s demand to be informed. Commonly used algorithms for cartography are quick but their accuracy remains to be determined. Firstly, the choice of method is arbitrary and based on user's subjective per...

In studies of irrigation and drainage projects for drainage, it is necessary to extend the data from the sampling point to the network. Therefore, based on available data from observational wells, estimating the state of hydraulic conductivity (K) in the surrounding area. The estimation process values for locations where there is no information for them based on viewing areas called wells spati...

Of the many climatic events that influence the Earth’s environment, drought is perhaps the one that is most linked with desertification. Drought is the consequence of a natural reduction in the amount of precipitation received over an extended period, usually a season or more in length. Drought monitoring is an essential component of drought risk management. It is normally performed using vario...

Keeping the water table at a favorable level is quite significant for a sustainable management of groundwater plans. Various management measures need to know the spatial and temporal behavior of groundwater. Therefore, the measurement of groundwater levels are generally carried out at spatially random locations in the field; whereas, most of the groundwater models requires these measurement at ...

In this study we evaluated the diffusion of nitrous oxide in a few operating rooms, using spatial data modelling techniques, in order to assess hospital staff exposure and to promote risk management. Indoor air sampling was carried out, during routine operating activity, by means of transportable infrared spectrometer, with geostatistical techniques. We detected high average concentrations of n...

INTRODUCTION A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. METHODS A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. RESULTS Parameters Range...