Geostatistical methods provide valuable approaches for analyzing spatial patterns of ecological systems. They allow for both the prediction and visualization of ecological phenomena, a combination that is essential for the conceptual development and testing of ecological theory. Yet, many ecologists remain unfamiliar with the application of these techniques. Here, we apply the methodology of ge...

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...

abstract: converting point data to continuous one is the first step in order to use them in scorpan flowchart. for this purpose, different geostatistic methods are available which at present research regression kriging with local variogram was applied. for mapping apparent electrical conductivity at the area covering 72000ha located in ardakan region, 700 readings in horizontal and vertical mod...

BACKGROUND Cancer mortality maps are used by public health officials to identify areas of excess and to guide surveillance and control activities. Quality of decision-making thus relies on an accurate quantification of risks from observed rates which can be very unreliable when computed from sparsely populated geographical units or recorded for minority populations. This paper presents a geosta...

This paper describes the application of Kriging metamodeling in multiple-objective simulation optimization. An Arenabased simulation model of an (s, S) inventory system is utilized to demonstrate the capabilities of Kriging metamodeling as a simulation tool. Response surface methodology and Kriging metamodeling are compared to determine the situations in which one approach might be preferred ov...

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. ...

The interpolation of spatial data has been considered in many different forms. The various forms of kriging are among the best known in the earth sciences although techniques such as inverse distance weighting were and are in use for spatially located data. In the numerical analysis literature various forms of splines and more recently radial basis functions have been developed and used. Becaus...

One can divide the existing ionospheric methods for SBAS in two categories: tomography and methods relying on the thin shell model. At first sight, tomography appears to be the right choice. Tomography reconstructs the three dimensional density of the ionosphere from the available measurements. However, there are several drawbacks to tomography: the system of equations to be solved is often und...

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...