research-article

Design-based properties of some small-area estimators in forest inventory with two-phase sampling

Publication: Canadian Journal of Forest Research28 February 2013https://doi.org/10.1139/cjfr-2012-0381

Abstract

We consider the small-area estimation problem for forest inventories with two-phase sampling schemes. We propose an improvement to the synthetic estimator, when the true mean of the auxiliary variables over the small area is unknown and must be estimated, and likewise to the residual corrected small-area estimator. We derive the asymptotic design-based variances of these new estimators, the pseudo-synthetic and pseudo-small-area estimators, by also incorporating the design-based variance of the regression coefficients. We then propose a very simple mathematical device that transforms pseudo-small-area estimators into pseudo-synthetic estimators, which is very convenient for deriving asymptotic variances. The results are extended to cluster and two-stage sampling at the plot level. A case study and a simulation illustrate the theory.

Résumé

Nous considèrons le problème de l'estimation pour petits domaines dans le contexte d'inventaires forestiers en deux phases. Nous proposons une amélioration simple de l'estimateur synthétique quand la moyenne des variables auxiliaires dans le petit domaine doit être estimée en premier lieu, de même pour l'estimateur pour petit domaine basé sur les résidus. Nous calculons la variance sous le plan de sondage de ces nouveaux estimateurs en tenant compte de la variance des coefficients de régression. De plus, nous proposons un artifice mathématique qui permet de transformer un estimateur pour petit domaine en un estimateur synthétique, ce qui simplifie le calcul de la variance asymptotique. L'extension aux sondages par satellites et deux degrés au niveau de la placette est aussi traitée. Un exemple concret et une simulation illustrent la théorie.

References

Bafetta F., Corona P., and Fattorini L. 2011. Design-based diagnostics for k-NN estimators of forest resources. Can. J. For. Res. 41(1): 59–72.
Breidenbach J. and Astrup R. 2012. Small area estimation of forest attribute in the Norwegian National Forest Inventory. Eur. J. Forest Res. 131: 1255–1267.
Breidenbach J. and Nothdurft A. 2010. Comparison of nearest neighbours approaches for small area estimation of tree species-specific forest inventory attributes in central Europe using airborne laser scanner data. Eur. J. Forest Res. 129: 833–846.
Finley A.O., Naerjee S., and McRoberts R. 2008. A Bayesian approch to multi-source forest area estimation. Environ. Ecol. Stat. 15: 241–258.
Goerndt M.E., Monleon V.J., and Temesgen H. 2011. A comparison of small-area estimation techniques to estimate selected stand attributes using LIDAR-derived auxiliary variables. Can. J. For. Res. 41(6): 1189–1201.
Gregoire T. and Dyer M. 1989. Model fitting under patterned heterogeineity of variance. Forest Sci. 35: 105–125.
Huber, P.J. 1967. The behaviour of maximum likelihood estimates under non-standard conditions. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Volume 1. University of California Press, Berkeley, California. pp. 221–233.
Koehl, M., Magnussen, S., and Marchetti, M. 2006. Sampling methods, remote sensing and GIS multisource forest inventory. Springer, Berlin, Heidelberg.
Lappi J. 2001. Forest inventory of small areas combining the calibration estimator and a spatial model. Can. J. For. Res. 31(9): 1551–1560.
Mandallaz, D. 1993. Geostatistical methods for double sampling schemes: applications to combined forest inventory. Habilitation thesis, Department of Environmental Systems Science, ETH Zurich, Technical report. Available from http://e-collection.library.ethz.ch.
Mandallaz D. 2000. Estimation of the spatial covariance in universal kriging: application to forest inventory. Environ. Ecol. Stat. 7: 263–284.
Mandallaz, D. 2008. Sampling techniques for forest inventories. Chapman and Hall, Boca Raton, Florida.
Mandallaz, D. 2012. Design-based properties of small-area estimators in forest inventory with two phase sampling. Department of Environmental Systems Science, ETH Zurich, Technical report. Available from http://e-collection.library.ethz.ch.
Mandallaz D. and Massey A. 2012. Comparison of estimators in one-phase two-stage Poisson sampling in forest inventories. Can. J. For. Res. 42(12): 1865–1871.
Mandallaz D. and Ye R. 1999. Forest inventory with optimal two-phase, two-stage sampling schemes based on the anticipated variance. Can. J. For. Res. 29(11): 1691–1708.
McRoberts R.E. 2012. Estimating forest attributes parameters for small areas using nearest neighbors techniques. Forest Ecol. Manag. 272: 3–12.
Rao, J. 2003. Small area estimation. John Wiley and Sons, Hoboken, New Jersey.
Särndal, C., Swenson, B., and Wretman, J. 2003. Model assisted survey sampling. Springer Series in Statistics, New York.

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Canadian Journal of Forest Research cover image
Canadian Journal of Forest Research
Volume 43Number 52013
Pages: 441 - 449

History

Received: 10 September 2012
Accepted: 27 February 2013
Published online: 28 February 2013

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Daniel Mandallaz
Chair of Land Use Engineering, ETH Zurich, CH 8092 Zurich, Switzerland.

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