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VARIANCE ESTIMATION FOR SPATIALLY BALANCED SAMPLES OF ENVIRONMENTAL RESOURCES
Citation:
Stevens, D. L. AND A R. Olsen. VARIANCE ESTIMATION FOR SPATIALLY BALANCED SAMPLES OF ENVIRONMENTAL RESOURCES. ENVIRONMETRICS. John Wiley & Sons, Ltd., Chichester, Uk, 14:593-610, (2003).
Description:
The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. We review a unified strategy for designing probability samples of discrete, finite resource populations, such as lakes within some geographical region; linear populations, such as a stream network in a drainage basin; and continuous, two-dimensional populations, such as forests. The strategy can be viewed as a generalization of spatial stratification. In this paper, we develop a local neighborhood variance estimator based on that perspective, and examine its behavior via simulation. The simulations indicate that the local neighborhood estimate is unbiased and stable. The Horvitz-Thompson IRS variance estimate may be two times the magnitude of the local neighborhood estimate. An example using data from a generalized random-tessellation stratified design on the Oahe Reservoir resulted in local variance estimates being 22 to 58 percent smaller than Horvitz-Thompson IRS variance estimates. Variables with stronger spatial patterns had greater reductions in variance, as expected.