A standard survey of soil salinity in Iran has produced a classified soil salinity map and a data set of about 600 electrical conductivity (EC) measurements of the saturated paste extract determined at three depth intervals (050cm, 50-100cm and 100-150cm). However, since the EC values ranged from 1 to 109 mS/cm, a more detailed quantitative evaluation was desired. The study area covers about 45...

The benefits of an integrated geographical information system (GIS) and a geostatistics approach to accurately model the spatial distribution pattern of precipitation are known. However, the determination of the most appropriate geostatistical algorithm for each case is usually neglected, i.e. it is important to select the best interpolation technique for each study area to obtain accurate resu...

The relationship between soil properties and environmental covariates is mostly nonlinear for human impacted areas. Herein, we proposed a model mapping organic carbon (SOC) total nitrogen (TN) in typical area (a small watershed of Poyang Lake, China), namely radial basis function neural network combined with agricultural land use (RBFNN_ALU). results showed that the RBFNN_ALU performs better th...

Abstract Reference evapotranspiration (ET 0 ) estimates are commonly used in hydrologic planning for water resources and agricultural applications. Last 2 decades, machine learning (ML) techniques have enabled scientists to develop powerful tools study ET patterns the ecosystem. This investigated feasibility effectiveness of three ML techniques, including k -nearest neighbor algorithm, multigen...

Finding a proper estimation method for ore resources/reserves is important in mining engineering. The aim of this work is to compare the Ordinary Kriging (OK) and Advanced Inverse Distance Squared (AIDS) methods based on the correlation between the raw and estimated data in the East-Parvadeh coal deposit, central Iran. The variograms and anisotropic ellipsoids are calculated to estimate the ash...

Kriging is an advanced geostatistical procedure that generates an estimated surface or 3D model from a scattered set of points. This method can be used for estimating resources using a grid of sampled boreholes. However, conventional ordinary kriging (OK) is unable to take locally varying anisotropy (LVA) into account. A numerical approach has been presented that generates an LVA field by calcu...

Methods of Land Use Regression (LUR) modeling and Ordinary Kriging (OK) interpolation have been widely used to offset the shortcomings of PM2.5 data observed at sparse monitoring sites. However, traditional point-based performance evaluation strategy for these methods remains stagnant, which could cause unreasonable mapping results. To address this challenge, this study employs 'information ent...

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...