Image inpainting is the art of predicting damaged regions of an image. The manual way of image inpainting is a time consuming. Therefore, there must be an automatic digital method for image inpainting that recovers the image from the damaged regions. In this paper, a novel statistical image inpainting algorithm based on Kriging interpolation technique was proposed. Kriging technique automatical...

Spatial disagregation is needed when environmental models of climate, air quality, hydrology, etc. require input data at a finer scale than available or when models produce outputs at a coarser scale than required by users. Area-to-Point Kriging is a common geostatistical framework to address the problem of spatial disaggregation from block to point support. Spatial disaggregation using Area-to...

abstract soil invertebrate and their spatial pattern are affected strongly by environmental factors. spatial variability of soil properties is one of the most important reasons of the macrofauna variability. this study was conducted to investigate the spatial variability of soil properties and soil macrofauna biomass in the riparian forest landscape of karkhe river. soil macro fauna were sample...

The article describes the R package constrainedKriging, a tool for spatial prediction problems that involve change of support. The package provides software for spatial interpolation by constrained (CK), covariance-matching constrained (CMCK) and customary universal (UK) kriging. CK and CMCK yield approximately unbiased predictions of nonlinear functionals of target quantities under change of s...

The economic assessment of mining projects includes many factors and resource classification is critical at any stage of mining. The quality of resource classification is a key requirement for accurate economic and environmental risk evaluation. The results of economic assessment are usually reported by companies in order to attract investors. Mineral resource classification standards were crea...

This paper addresses the issue of modelling the uncertainty about the value of continuous soil Ž . attributes, at any particular unsampled location local uncertainty as well as jointly over several Ž . locations multiple-point or spatial uncertainty . Two approaches are presented: kriging-based and Ž . simulation-based techniques that can be implemented within a parametric e.g. multi-Gaussian o...

Nowadays, kriging has been accepted as the most common method of grade estimation in mineral resource evaluation stage. Access to the crisp assay data and a variogram model are the necessary means for the utilization of this method. Since fitting a crisp variogram model is generally difficult, if not impossible, the fitted theoretical model is usually tainted with uncertainty due to various rea...

Upscaling in situ soil moisture observations (ISMO) to multiscale pixel estimations with kriging is a key step in the comprehensive usage of ISMO and remote sensing (RS) soil moisture data. Scale effects occur and introduce uncertainties during upscaling processes because of spatial heterogeneity and the kriging method. A nested hierarchical scale series was established at the field level, and ...

VESPER 1.5 is a shareware software program, written to provide rigourous spatial prediction techniques for the precision agriculture industry. It offers a range of options to deal with data sets of varying data density, spatial distribution, and observation uncertainty. Such data sets are now gathered from a range of realtime yield, soil and crop sensors and through manual sampling regimes. Spe...