For many practical problems in environmental management, information about soil heavy metals, relative to threshold values that may be of practical importance is needed at unsampled sites. The Hangzhou-Jiaxing-Huzhou (HJH) Plain has always been one of the most important rice production areas in Zhejiang province, China, and the soil heavy metal concentration is directly related to the crop qual...

Drought monitoring is a fundamental component of drought risk management. It is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.In many instances, drought indices are used for monitoring purposes. Geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...

Geostatistics have become the dominant tool for probabilistic estimation of properties of heterogeneous formations at points where data are not available. Ordinary kriging, the starting point in development of other geostatistical techniques, has a number of serious limitations, chief among which is the intrinsic hypothesis of the (second order) stationarity of the underlying random field. Atte...

The study was carried out with 107 measurements of volumetric soil water content (SWC) and electrical conductivity (EC) for soil profile (0-30 cm) and the estimating accuracy of ordinary kriging (OK) and back-propagation neural network (BPNN) was compared. The results showed that BPNN method predicted a slightly better accurate SWC than that of OK, but differences between both methods were not ...

The precision agriculture hopes to manage the variation in soil nutrient status continuously, which requires reliable predictions at places between sampling sites. For the long time, ordinary kriging has been used as one prediction method when the data are spatially dependent and a suitable variogram model exists. However, even if data are spatially correlated, there are often few soil sampling...

Accurate knowledge of spatial distribution of soil physical and chemical properties is needed for suitable management and proper use of rangelands in Masileh plain, Qom, Iran. In present study, for the spatial modeling of chemical and physical parameters such as sodium (Na), calcium (Ca), soluble potassium (K), magnesium (Mg), Electrical Conductivity (EC), Saturation Percentage (SP%), silt, cla...

Direct Neural Network Residual Kriging (DNNRK) is a two step algorithm (Kanevsky et al. 1995). The first step includes estimating large scale structures by using artificial neural networks (ANN) with simple sum of squares error function. ANN, being universal approximators, model overall non-linear spatial pattern fairly well. ANN are model free estimators and depend only on their architecture a...

Ground-based rainfall observations are the primary sources of precipitation data used in most developing countries. However, those observations are frequently damaged or incomplete, thus missing data is always a problem. This comparison study examines a number of spatial interpolation methods used to estimate missing monthly rainfall data in the northeast region of Thailand. The comparison was ...

This work introduces a methodology for reducing the execution time of the kriging interpolationmethod without losing the quality of the model results, as occurs in simplified moving neighborhood solutions. The proposed solution distributes the computation applying parallel programming using MPI (Message Passing Interface) libraries in a HPC (High Performance Computing) environment. For the solu...

One important method to obtain the continuous surfaces of soil properties from point samples is spatial interpolation. In this paper, we propose a method that combines ensemble learning with ancillary environmental information for improved interpolation of soil properties (hereafter, EL-SP). First, we calculated the trend value for soil potassium contents at the Qinghai Lake region in China bas...