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, ...

Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used...

BACKGROUND Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimatio...

This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 ...

Ž . Using spatial simulated annealing SSA , spatial sampling schemes can be optimised for minimal kriging variance. Two optimisation criteria are presented in this paper. The first criterion minimises the average kriging variance, the second the maximum kriging variance. In a simple case with 23 observations, performances of a sampling scheme obtained with SSA were compared with performances of...

Leaf area index (LAI) is a key parameter used to describe vegetation structures and is widely used in ecosystem biophysical process and vegetation productivity models. Many algorithms have been developed for the estimation of LAI based on remote sensing images. Our goal was to produce accurate and timely predictions of grassland LAI for the meadow steppes of northern China. Here, we compare the...

Kriging is a spatial prediction method, which can predict at any location and return a measure of prediction confidence (the kriging standard error). There exist many variations of kriging, some of which can be complex, especially those that allow many of its parameters to vary spatially. To calibrate such a kriging model and to be able to interpret its results can therefore be quite daunting. ...

Various statistical methods were applied to spatially discrete data from 14 intensively sampled small estuarine systems in the mid-Atlantic U.S. The number of sites per system ranged from 6 to 37. The surface area of the systems ranged from 1.9 to 193.4 km 2 . Parameters examined were depth, bottom temperature, bottom salinity, surface chlorophyll a, bottom dissolved oxygen, lead concentration ...

Kriging is one of the most frequently used prediction methods in spatial data analysis. This paper examines which steps of the underlying algorithms can be performed in parallel on a PVM cluster. It will be shown, that some properties of the so called kriging equations can be used to improve the parallelized version of the algorithm. The implementation is based on R and PVM (Parallel Virtual Ma...

within-field variation of wheat yield and spatial pattern of weed density and soil nitrogen were evaluated by geostatistical methods. samples were taken from a 90×120 m area located in a 3.8 ha wheat field. soil nitrogen content and weed density at tillering and wheat yield at maturity were measured in 1 m2 plots located at the center of 10×10 m grids. grain yield was varied between 1.5-4.9 t h...