geostatistical approaches have great importance because they include spatial correlation of geographic data. present study evaluated the efficiency of geostatistical techniques and demonstrated their capabilities in studying the soil variables(soil texture (sand percent), ec and so4-2) in the important plant community of nitraria schoberi in meighan desert, arak. a regular grid on the map compr...

Whenever simulation requires much computer time, interpolation is needed. There are several interpolation techniques in use (for example, linear regression), but this paper focuses on Kriging. This technique was originally developed in geostatistics by D. G. Krige, and has recently been widely applied in deterministic simulation. This paper, however, focuses on random or stochastic simulation. ...

This paper applies a novel Kriging model to the interpolation of stochastic simulation with high computational expense. The novel Kriging model is developed by using Taylor expansion to construct a drift function for Kriging, thus named Taylor Kriging. The interpolation capability of Taylor Kriging for stochastic simulation is empirically compared with those of Simple Kriging and Ordinary Krigi...

The density of soil observations is a major determinant digital mapping (DSM) prediction accuracy. In this study, we investigated the effect sampling on performance DSM to predict topsoil particle-size distribution in Mayenne region France. We tested two algorithms, namely ordinary kriging (OK) and quantile random forest (QRF). study area ~5000 km2 with highest field France (1 profile per 0.64 ...

Accurately quantifying soil organic carbon (SOC) stocks in soils is considered necessary and important for studying the soil quality and productivity, modeling the global carbon cycle, and assessing the global climate change. The objectives of this chapter are (1) to evaluate the effects of sampling density and interpolation methods on spatial distribution of SOC density (SOCD) and (2) to estim...

Phosphorus enrichment has been of major concern in the Greater Everglades (GE) ecosystem since the early 1980s. Our objectives were to estimate spatio–temporal patterns of soil total phosphorus (TP) in Water Conservation Area 2A (WCA-2A) in the GE ecosystem and to compare two different geostatistical methods: ordinary kriging (OK) and conditional sequential Gaussian simulation (CSGS), addressin...

It is well known that climate and circulation model simulation output are often systematically biased. However, existing bias correction methods typically ignore spatial autocorrelation of the biases correct only overall mean variance, resulting in mismatched variability between bias-corrected simulations observations. In this study, we propose using regression kriging (RK) to for biased patter...

The spatial pattern of precipitation is known to be highly dependent on meteorological conditions and relief. However, the relationships between precipitation and topography in mountainous areas are not very well known, partly because of the complex topography in these regions, and partly because of the sparsity of information available to study such relationships in high elevation areas. The p...

High-precision retrieval of rainfall over large areas is great importance for the research atmospheric detection and social life. With rapid development communication satellite constellations 5G networks, use widely distributed networks earth–space links (ESLs) horizontal microwave (HMLs) to retrieve has potential obtaining high-precision fields complementing traditional instruments measurement...