" Kriging " (after the South African mining engineer Danie Krige) is a term used for a family of methods for minimum error variance estimation. Consider a linear estimatê z 0 = ˆ z(r 0) at a location r 0 based on N measurements z = [z(r 1),. .. , z(r N)] T = [z 1 ,. .. , z N ] T ˆ z 0 = w 0 + N i=1 w i z i = w 0 + w T z, (1) where w i are the weights applied to z i. We consider z i as particula...

Estimating the amount of variation due to spatial dependence at different scales provides a basis for designing effective experiments. Accurate knowledge of spatial structures is needed to inform silvicultural guidelines and management decisions for long term sustainability of forests. Furthermore, geostatistics is a useful tool to describe and draw map the spatial variability and estimation o...

BACKGROUND Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) residual kriging is a geostatistical method that can be used to create a spatiotemporal exposure model ...

In this paper, we applied the support vector machine (SVM) to the spatial interpolation of the multi-year average annual precipitation in the Three Gorges Region basin. By combining it with the inverse distance weighting and ordinary kriging method, we constructed the SVM residual inverse distance weighting, as well as the SVM residual kriging precipitation interpolation model and compared them...

Variograms are used to describe the spatial variability of environmental variables. In this study, the parameters that characterize the variogram are obtained from a variogram in a different but comparably polluted area. A procedure is presented for improving the variogram modelling when data become available from the area of interest. Interpolation is carried out by means of a Bayesian form of...

The high computational cost of population based optimization methods, such as multiobjective genetic algorithms (MOGAs), has been preventing applications of these methods to realistic engineering design problems. The main challenge is to devise methods that can significantly reduce the number of simulation (objective/constraint functions) calls. We present a new multi-objective design optimizat...

High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used theModerate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuousmaps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were d...

and Applied Analysis 3 2.2. Universal Kriging for Computing Water Depth in Any Position The basic premise of Kriging interpolation is that every unknown point can be estimated by the weighted sum of the known points: Z∗ 0 n ∑ i 1 λi Zi, 2.1 where Z∗ 0 represents the unknown point, Zi refers to each known point, and λ 0 i is the weight given to it. The Kriging algorithm body is involved in the a...

estimation and mapping of forest resources are preconditions for management, planning and research. in this study, we applied kriging interpolation of geostatistics for estimation and mapping of forest stock at-tributes in a natural, uneven-aged, unmanaged forest in the caspian region of northern iran. the site of the study has an area of 516 ha and an elevation that ranges from 1100 to 1450 m ...