Combining data from multiple years or areas to improve variogram estimation.

Walter III, John F.; Christman, Mary C.; Hoenig, John M.; Mann, Roger

This article examines geostatistical prediction through estimation of the variogram from the data. Often low sample size is a major impediment to elucidating a variogram even for a highly autocorrelated spatial process. This paper presents a methodology for improving variogram estimation when samples exist from multiple years or regions sharing a similar process for generating spatial autocorrelation. Such samples may come from annual monitoring programs for natural resources or from multiple geologic regions. In both simulations and in real datasets of oyster abundance the method proposed reduces the likelihood of failing to obtain a variogram from a set of samples and improves the efficiency of variogram estimation.

GEOLOGICAL statistics; SPACIAL distribution; ANALYSIS of variance; BIOGEOGRAPHY; AUTOCORRELATION (Statistics); SAMPLE size (Statistics); DATA quality; KRIGING

Environmetrics, 2007, Vol 18, Issue 6, p583

1180-4009

Academic Journal

10.1002/env.825