Many hydrological variables usually show the presence of spatial drifts. Most often they are accounted for by either universal or residual kriging and usually assuming low order polynomials. The Universal Kriging matrix ( M ), which includes in it the values of the polynomials at data locations (matrix F ), in some cases may have a too large condition number and can even be nearly singular due ...

Modelling and estimating spatio-temporal dynamic field are common challenges in much applied research. Most existing interpolation methods require massive prior calculations consistent observational data, resulting low efficiency. This paper presents a flexible state-space model for iteratively fitting time-series from random missing points data sets, namely Flexible Universal Kriging model(FUK...

As the development of earth sciences and cross-disciplinary, it’s more and more meaningful and valuable to analyze and estimate precipitation spatial distribution. Precipitation spatial information is important in many fields, such as water resource management, drought and flood disaster predication, and regional sustainable development. It’s unrealistic to get the accurate predication of a par...

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny d...

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...

Though one of the most significant driving forces behind ecological processessuch as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from othermeteorological data through (geo)statistical models. In this study, spatial and temporalpatterns of monthly average daily solar radiation on a h...

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...

This paper introduces the gstat package for the S language (R, S-PLUS). The package provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions. Gstat (http://www. gstat.org) was started 10 years ago and was released under the GPL in 1996; it is closely linked to several GIS systems. It was not initially written for teaching purposes, b...

27 28 ABSTRACT 29 30 This work explores the application of kriging methods for prediction of average daily traffic 31 counts across the Texas network. Results based on Euclidean distances are compared to those 32 using network distances, and both allow for strategic spatial interpolation of count values while 33 controlling for each roadway's functional classification, lane count, speed limit, ...