The minimum estimation variance (MEV) spatial sampling strategy is compared with some further strategies based on systematic designs and the sample mean. Since in environmental surveys data are usually collected repeatedly in time at sites whose selection is based on practical circumstances only, it seems worth measuring the efficiency of spatial sampling strategies through the expectation of design mean square errors under several superpopulation models assumed about the fixed population generating process. Relating the study to specific superpopulations,MEVefficiencies can be calculated and a quantitative evaluation is made possible by the use of scenario analyses for several sample sizes and different models of spatial drift and correlations. The MEV strategy revealed itself to be the relatively more efficient one under realistic conditions of nonstationary spatial drifts and bounded sample sizes.
Efficiency evaluation of MEV spatial sampling strategies: a scenario analysis
LAFRATTA, Giovanni
2006-01-01
Abstract
The minimum estimation variance (MEV) spatial sampling strategy is compared with some further strategies based on systematic designs and the sample mean. Since in environmental surveys data are usually collected repeatedly in time at sites whose selection is based on practical circumstances only, it seems worth measuring the efficiency of spatial sampling strategies through the expectation of design mean square errors under several superpopulation models assumed about the fixed population generating process. Relating the study to specific superpopulations,MEVefficiencies can be calculated and a quantitative evaluation is made possible by the use of scenario analyses for several sample sizes and different models of spatial drift and correlations. The MEV strategy revealed itself to be the relatively more efficient one under realistic conditions of nonstationary spatial drifts and bounded sample sizes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.