Estimating spatial attribute means in a GIS environment

Abstract: The estimation of geographical attributes is a crucial matter for many real-world problems, and the issue of accuracy stands out when the estimation is used for between-regions comparison. In this work, our concern is area attribute estimation in a GIS environment. We estimate the area attribute value with a mean Kriging technique, and the probability distribution of the estimate is derived. This is the best linear unbiased observed spatial population mean estimate and can be used in more relaxed situations than the block Kriging technique. Both theoretical analysis and empirical study show that the mean Kriging technique outperforms the ordinary Kriging, spatial random sampling, and simple random sampling techniques in estimating the observable spatial population mean across space.