Physical Sciences and Mathematics Commons^™

A Comparison Of Spatial Prediction Techniques Using Both Hard And Soft Data, Megan L. Liedtke Tesar

Department of Statistics: Dissertations, Theses, and Student Work

The overall goal of this research, which is common to most spatial studies, is to predict a value of interest at an unsampled location based on measured values at nearby sampled locations. To accomplish this goal, ordinary kriging can be used to obtain the best linear unbiased predictor. However, there is often a large amount of variability surrounding the measurements of environmental variables, and traditional prediction methods, such as ordinary kriging, do not account for an attribute with more than one level of uncertainty. This dissertation addresses this limitation by introducing a new methodology called weighted kriging. This prediction technique …